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	<id>https://adapt2.sis.pitt.edu/w/api.php?action=feedcontributions&amp;feedformat=atom&amp;user=Jguerra</id>
	<title>PAWS Lab - User contributions [en]</title>
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	<updated>2026-05-18T17:34:41Z</updated>
	<subtitle>User contributions</subtitle>
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	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Aggregate&amp;diff=3358</id>
		<title>Aggregate</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Aggregate&amp;diff=3358"/>
		<updated>2016-04-04T18:43:20Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[[Image:arch_v2.png|Aggregate Architecture]]&lt;br /&gt;
&lt;br /&gt;
We developed an adaptive social learning architecture Aggregate to support [[Mastery Grids Interface]]. We design this architecture to integrate content from diverse sources. The explanation of the procedures and links to associated resources are given below.&lt;br /&gt;
&lt;br /&gt;
* [[Mastery Grids Interface]] receives all the information to display (this is course structure, links to content and progress levels of the learner and the group of learners) from services hosted in Aggregate (a in the diagram). This information is passed in JSON format. &lt;br /&gt;
&lt;br /&gt;
* To let Mastery Grids know the level of progress of the learners in the topics and the content, Aggregates call services from a User Model (UM in the figure). See point b) in the figure. These services are documented in [https://github.com/PAWSLabUniversityOfPittsburgh/mastery-grids/blob/master/documentation/User_State_protocol.pdf User State Protocol]&lt;br /&gt;
&lt;br /&gt;
* The figure shows several different Content apps (QuizJet, QuizPet, Webex, etc.). Each of these applications are integrated in 2 ways:&lt;br /&gt;
** The content application needs to log information of the learner activity within the content to the User Model (letter c in the diagram). Currently, the content applications are using our ADAPT2 [[CUMULATE protocol|cbum protocols]].&lt;br /&gt;
** The content application provides a service to list all the available content. This service implement the [https://github.com/PAWSLabUniversityOfPittsburgh/mastery-grids/blob/master/documentation/Content_Brokering_API_2016_01_21.pdf content brokering specification], which defines a JSON-format protocol to allow external applications to discover content. Both Aggregate and the User Model use the content brokering to register new content.&lt;br /&gt;
&lt;br /&gt;
Several content application and their respective content brokering are implemented in [http://acos.cs.hut.fi/ ACOS server]. &lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Associated resources ==&lt;br /&gt;
&lt;br /&gt;
* [https://github.com/PAWSLabUniversityOfPittsburgh/mastery-grids Mastery Grids repository] (contains aggregate, mastery grids interface, documentation and course authoring tool)&lt;br /&gt;
* [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices  User State Services repository]&lt;br /&gt;
* [[CUMULATE|user modeling specification]]&lt;br /&gt;
&lt;br /&gt;
== Content application resources ==&lt;br /&gt;
&lt;br /&gt;
* [[Smart Content|Smart content]] : provides an explanation of content applications&lt;br /&gt;
* [http://acos.cs.hut.fi ACOS server] : provides details of ACOS infrastructure, content and protocols&lt;br /&gt;
* [https://github.com/PAWSLabUniversityOfPittsburgh/quizjet QuizJet repository]&lt;br /&gt;
* [https://github.com/PAWSLabUniversityOfPittsburgh/quizpet QuizPet repository]&lt;br /&gt;
* [https://github.com/PAWSLabUniversityOfPittsburgh/annotated-examples Annotated Examples (Webex) repository]&lt;br /&gt;
* [https://github.com/PAWSLabUniversityOfPittsburgh/educational-videos Educational Videos repository]&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Aggregate&amp;diff=3354</id>
		<title>Aggregate</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Aggregate&amp;diff=3354"/>
		<updated>2016-04-04T18:37:14Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[[Image:arch_v2.png|Aggregate Architecture]]&lt;br /&gt;
&lt;br /&gt;
We developed an adaptive social learning architecture Aggregate to support [[Mastery Grids Interface]]. We design this architecture to integrate content from diverse sources. The explanation of the procedures and links to associated resources are given below.&lt;br /&gt;
&lt;br /&gt;
* [[Mastery Grids Interface]] receives all the information to display (this is course structure, links to content and progress levels of the learner and the group of learners) from services hosted in Aggregate (a in the diagram). This information is passed in JSON format. &lt;br /&gt;
&lt;br /&gt;
* To let Mastery Grids know the level of progress of the learners in the topics and the content, Aggregates call services from a User Model (UM in the figure). See point b) in the figure. These services are documented in [https://github.com/PAWSLabUniversityOfPittsburgh/mastery-grids/blob/master/documentation/User_State_protocol.pdf User State Protocol]&lt;br /&gt;
&lt;br /&gt;
* The figure shows several different Content apps (QuizJet, QuizPet, Webex, etc.). Each of these applications are integrated in 2 ways:&lt;br /&gt;
** The content application needs to log information of the learner activity within the content to the User Model (letter c in the diagram). Currently, the content applications are using our ADAPT2 [[CUMULATE protocol|cbum protocols]].&lt;br /&gt;
** The content application provides a service to list all the available content. This service implement the [https://github.com/PAWSLabUniversityOfPittsburgh/mastery-grids/blob/master/documentation/Content_Brokering_API_2016_01_21.pdf content brokering specification], which defines a JSON-format protocol to allow external applications to discover content. Both Aggregate and the User Model use the content brokering to register new content.&lt;br /&gt;
&lt;br /&gt;
Several content application and their respective content brokering are implemented in [http://acos.cs.hut.fi/ ACOS server]. &lt;br /&gt;
&lt;br /&gt;
Associated resources&lt;br /&gt;
&lt;br /&gt;
* [https://github.com/PAWSLabUniversityOfPittsburgh/mastery-grids Mastery Grids repository] (contains aggregate, mastery grids interface, documentation and course authoring tool)&lt;br /&gt;
* [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices  User State Services repository]&lt;br /&gt;
* [[CUMULATE|user modeling specification]]&lt;br /&gt;
&lt;br /&gt;
Content provider applications&lt;br /&gt;
* [[Smart Content|Smart content]] : provides an explanation of content applications&lt;br /&gt;
* [http://acos.cs.hut.fi ACOS server] : provides details of ACOS infrastructure, content and protocols&lt;br /&gt;
* [https://github.com/PAWSLabUniversityOfPittsburgh/quizjet QuizJet repository]&lt;br /&gt;
* [https://github.com/PAWSLabUniversityOfPittsburgh/quizpet QuizPet repository]&lt;br /&gt;
* [https://github.com/PAWSLabUniversityOfPittsburgh/annotated-examples Annotated Examples (Webex) repository]&lt;br /&gt;
* [https://github.com/PAWSLabUniversityOfPittsburgh/educational-videos Educational Videos repository]&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Aggregate&amp;diff=3353</id>
		<title>Aggregate</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Aggregate&amp;diff=3353"/>
		<updated>2016-04-04T18:35:02Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;We developed an adaptive social learning architecture Aggregate to support [[Mastery Grids Interface]]. We design this architecture to integrate content from diverse sources. The explanation of the procedures and links to associated resources are given below.&lt;br /&gt;
&lt;br /&gt;
* [[Mastery Grids Interface]] receives all the information to display (this is course structure, links to content and progress levels of the learner and the group of learners) from services hosted in Aggregate (a in the diagram). This information is passed in JSON format. &lt;br /&gt;
&lt;br /&gt;
* To let Mastery Grids know the level of progress of the learners in the topics and the content, Aggregates call services from a User Model (UM in the figure). See point b) in the figure. These services are documented in [https://github.com/PAWSLabUniversityOfPittsburgh/mastery-grids/blob/master/documentation/User_State_protocol.pdf User State Protocol]&lt;br /&gt;
&lt;br /&gt;
* The figure shows several different Content apps (QuizJet, QuizPet, Webex, etc.). Each of these applications are integrated in 2 ways:&lt;br /&gt;
** The content application needs to log information of the learner activity within the content to the User Model (letter c in the diagram). Currently, the content applications are using our ADAPT2 [[CUMULATE protocol|cbum protocols]].&lt;br /&gt;
** The content application provides a service to list all the available content. This service implement the [https://github.com/PAWSLabUniversityOfPittsburgh/mastery-grids/blob/master/documentation/Content_Brokering_API_2016_01_21.pdf content brokering specification], which defines a JSON-format protocol to allow external applications to discover content. Both Aggregate and the User Model use the content brokering to register new content.&lt;br /&gt;
&lt;br /&gt;
Several content application and their respective content brokering are implemented in [http://acos.cs.hut.fi/ ACOS server]. &lt;br /&gt;
&lt;br /&gt;
Associated resources&lt;br /&gt;
&lt;br /&gt;
* [https://github.com/PAWSLabUniversityOfPittsburgh/mastery-grids Mastery Grids repository] (contains aggregate, mastery grids interface, documentation and course authoring tool)&lt;br /&gt;
* [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices  User State Services repository]&lt;br /&gt;
* [[CUMULATE|user modeling specification]]&lt;br /&gt;
&lt;br /&gt;
Content provider applications&lt;br /&gt;
* [https://github.com/PAWSLabUniversityOfPittsburgh/quizjet QuizJet repository]&lt;br /&gt;
* [https://github.com/PAWSLabUniversityOfPittsburgh/quizpet QuizPet repository]&lt;br /&gt;
* [https://github.com/PAWSLabUniversityOfPittsburgh/annotated-examples Annotated Examples (Webex) repository]&lt;br /&gt;
* [https://github.com/PAWSLabUniversityOfPittsburgh/educational-videos Educational Videos repository]&lt;br /&gt;
* [http://acos.cs.hut.fi ACOS server]&lt;br /&gt;
* [[Smart Content|content]] providing applications&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the following figure.&lt;br /&gt;
&lt;br /&gt;
[[Image:arch_v2.png|Aggregate Architecture]]&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Aggregate&amp;diff=3344</id>
		<title>Aggregate</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Aggregate&amp;diff=3344"/>
		<updated>2016-04-04T18:17:00Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;We developed an adaptive social learning architecture Aggregate to support [[Mastery Grids Interface]]. We design this architecture to integrate content from diverse sources. The explanation of the procedures and links to associated resources are given below.&lt;br /&gt;
&lt;br /&gt;
* [[Mastery Grids Interface]] receives all the information to display (this is course structure, links to content and progress levels of the learner and the group of learners) from services hosted in Aggregate (a in the diagram). This information is passed in JSON format. &lt;br /&gt;
&lt;br /&gt;
* To let Mastery Grids know the level of progress of the learners in the topics and the content, Aggregates call services from a User Model (UM in the figure). See point b) in the figure. These services are documented in [https://github.com/PAWSLabUniversityOfPittsburgh/mastery-grids/blob/master/documentation/User_State_protocol.pdf User State Protocol]&lt;br /&gt;
&lt;br /&gt;
* The figure shows several different Content apps (QuizJet, QuizPet, Webex, etc.). Each of these applications are integrated in 2 ways:&lt;br /&gt;
** The content application needs to log information of the learner activity within the content to the User Model (letter c in the diagram). Currently we are usign our ADAPT2 [[CUMULATE protocol|cbum protocols]].&lt;br /&gt;
** The content application provides a service to list all the available content. This service implement the [https://github.com/PAWSLabUniversityOfPittsburgh/mastery-grids/blob/master/documentation/Content_Brokering_API_2016_01_21.pdf content brokering specification], which defines a JSON-format protocol to allow external applications to discover content.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
This architecture supports several kinds of open student modeling, social comparison, and recommendation. The architecture fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components as follows:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the [[Mastery Grids Interface]]&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices  ==&amp;gt; source code]&lt;br /&gt;
&lt;br /&gt;
*backend [[CUMULATE|user modeling]], [[Personalization|personalization]] (recommendation, navigation support) services&lt;br /&gt;
&lt;br /&gt;
*backend [[Smart Content|content]] providing applications&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the following figure.&lt;br /&gt;
&lt;br /&gt;
[[Image:arch_v2.png|Aggregate Architecture]]&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Aggregate&amp;diff=3342</id>
		<title>Aggregate</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Aggregate&amp;diff=3342"/>
		<updated>2016-04-04T18:15:22Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;We developed an adaptive social learning architecture Aggregate to support [[Mastery Grids Interface]]. We design this architecture to integrate content from diverse sources. The explanation of the procedures and links to associated resources are given below.&lt;br /&gt;
&lt;br /&gt;
* [[Mastery Grids Interface]] receives all the information to display (this is course structure, links to content and progress levels of the learner and the group of learners) from services hosted in Aggregate (a in the diagram). This information is passed in JSON format. &lt;br /&gt;
&lt;br /&gt;
* To let Mastery Grids know the level of progress of the learners in the topics and the content, Aggregates call services from a User Model (UM in the figure). See point b) in the figure. These services are documented in [https://github.com/PAWSLabUniversityOfPittsburgh/mastery-grids/blob/master/documentation/User_State_protocol.pdf User State Protocol]&lt;br /&gt;
&lt;br /&gt;
* The figure shows several different Content apps (QuizJet, QuizPet, Webex, etc.). Each of these applications are integrated in 2 ways:&lt;br /&gt;
** The content application needs to log information of the learner activity within the content to the User Model (letter c in the diagram). Currently we are usign our ADAPT2 protocol and our user model cbum for that. Specification of how &lt;br /&gt;
** The content application provides a service to list all the available content. This service implement the [https://github.com/PAWSLabUniversityOfPittsburgh/mastery-grids/blob/master/documentation/Content_Brokering_API_2016_01_21.pdf content brokering specification], which defines a JSON-format protocol to allow external applications to discover content.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
This architecture supports several kinds of open student modeling, social comparison, and recommendation. The architecture fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components as follows:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the [[Mastery Grids Interface]]&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices  ==&amp;gt; source code]&lt;br /&gt;
&lt;br /&gt;
*backend [[CUMULATE|user modeling]], [[Personalization|personalization]] (recommendation, navigation support) services&lt;br /&gt;
&lt;br /&gt;
*backend [[Smart Content|content]] providing applications&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the following figure.&lt;br /&gt;
&lt;br /&gt;
[[Image:arch_v2.png|Aggregate Architecture]]&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Aggregate&amp;diff=3341</id>
		<title>Aggregate</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Aggregate&amp;diff=3341"/>
		<updated>2016-04-04T18:07:59Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;We developed an adaptive social learning architecture Aggregate to support [[Mastery Grids Interface]]. We design this architecture to integrate content from diverse sources. The explanation of the procedures and links to associated resources are given below.&lt;br /&gt;
&lt;br /&gt;
* [[Mastery Grids Interface]] receives all the information to display (this is course structure, links to content and progress levels of the learner and the group of learners) from services hosted in Aggregate (a in the diagram). This information is passed in JSON format. &lt;br /&gt;
&lt;br /&gt;
* To let Mastery Grids know the level of progress of the learners in the topics and the content, Aggregates call services from a User Model (UM in the figure). See point b) in the figure. These services are documented in [https://github.com/PAWSLabUniversityOfPittsburgh/mastery-grids/blob/master/documentation/User_State_protocol.pdf User State Protocol]&lt;br /&gt;
&lt;br /&gt;
* The figure shows several different Content apps (QuizJet, QuizPet, Webex, etc.). Each of these applications are integrated in 2 ways:&lt;br /&gt;
** The content application provides a service to list all the available content. This service implement the [https://github.com/PAWSLabUniversityOfPittsburgh/mastery-grids/blob/master/documentation/Content_Brokering_API_2016_01_21.pdf content brokering specification], which defines how the content can be discovered in JSON format. &lt;br /&gt;
&lt;br /&gt;
This architecture supports several kinds of open student modeling, social comparison, and recommendation. The architecture fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components as follows:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the [[Mastery Grids Interface]]&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices  ==&amp;gt; source code]&lt;br /&gt;
&lt;br /&gt;
*backend [[CUMULATE|user modeling]], [[Personalization|personalization]] (recommendation, navigation support) services&lt;br /&gt;
&lt;br /&gt;
*backend [[Smart Content|content]] providing applications&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the following figure.&lt;br /&gt;
&lt;br /&gt;
[[Image:arch_v2.png|Aggregate Architecture]]&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Aggregate&amp;diff=3340</id>
		<title>Aggregate</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Aggregate&amp;diff=3340"/>
		<updated>2016-04-04T18:06:51Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;We developed an adaptive social learning architecture Aggregate to support [[Mastery Grids Interface]]. We design this architecture to integrate content from diverse sources. The explanation of the procedures and links to associated resources are given below.&lt;br /&gt;
&lt;br /&gt;
* [[Mastery Grids Interface]] receives all the information to display (this is course structure, links to content and progress levels of the learner and the group of learners) from services hosted in Aggregate (a in the diagram). This information is passed in JSON format. &lt;br /&gt;
&lt;br /&gt;
* To let Mastery Grids know the level of progress of the learners in the topics and the content, Aggregates call services from a User Model (UM in the figure). See point b) in the figure. These services are documented in [https://github.com/PAWSLabUniversityOfPittsburgh/mastery-grids/blob/master/documentation/User_State_protocol.pdf User State Protocol]&lt;br /&gt;
&lt;br /&gt;
* The figure shows several different Content apps (QuizJet, QuizPet, Webex, etc.). Each of these applications are integrated in 2 ways:&lt;br /&gt;
** The cntent application provides a service to list all the available content. This service implement the [https://github.com/PAWSLabUniversityOfPittsburgh/mastery-grids/blob/master/documentation/Content_Brokering_API_2016_01_21.pdf `content brokering]. &lt;br /&gt;
&lt;br /&gt;
This architecture supports several kinds of open student modeling, social comparison, and recommendation. The architecture fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components as follows:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the [[Mastery Grids Interface]]&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices  ==&amp;gt; source code]&lt;br /&gt;
&lt;br /&gt;
*backend [[CUMULATE|user modeling]], [[Personalization|personalization]] (recommendation, navigation support) services&lt;br /&gt;
&lt;br /&gt;
*backend [[Smart Content|content]] providing applications&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the following figure.&lt;br /&gt;
&lt;br /&gt;
[[Image:arch_v2.png|Aggregate Architecture]]&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Aggregate&amp;diff=3339</id>
		<title>Aggregate</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Aggregate&amp;diff=3339"/>
		<updated>2016-04-04T18:03:08Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;We developed an adaptive social learning architecture Aggregate to support [[Mastery Grids Interface]]. We design this architecture to integrate content from diverse sources. The explanation of the procedures and links to associated resources are given below.&lt;br /&gt;
&lt;br /&gt;
* [[Mastery Grids Interface]] receives all the information to display (this is course structure, links to content and progress levels of the learner and the group of learners) from services hosted in Aggregate (a in the diagram). This information is passed in JSON format. &lt;br /&gt;
&lt;br /&gt;
* To let Mastery Grids know the level of progress of the learners in the topics and the content, Aggregates call services from a User Model (UM in the figure). See point b) in the figure. These services are documented in [https://github.com/PAWSLabUniversityOfPittsburgh/mastery-grids/blob/master/documentation/User_State_protocol.pdf User State Protocol]&lt;br /&gt;
&lt;br /&gt;
This architecture supports several kinds of open student modeling, social comparison, and recommendation. The architecture fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components as follows:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the [[Mastery Grids Interface]]&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices  ==&amp;gt; source code]&lt;br /&gt;
&lt;br /&gt;
*backend [[CUMULATE|user modeling]], [[Personalization|personalization]] (recommendation, navigation support) services&lt;br /&gt;
&lt;br /&gt;
*backend [[Smart Content|content]] providing applications&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the following figure.&lt;br /&gt;
&lt;br /&gt;
[[Image:arch_v2.png|Aggregate Architecture]]&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=File:Arch_v2.png&amp;diff=3332</id>
		<title>File:Arch v2.png</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=File:Arch_v2.png&amp;diff=3332"/>
		<updated>2016-04-04T17:54:39Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Aggregate&amp;diff=3331</id>
		<title>Aggregate</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Aggregate&amp;diff=3331"/>
		<updated>2016-04-04T17:54:14Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;We developed an adaptive social learning architecture Aggregate to support [[Mastery Grids Interface]]. This architecture supports several kinds of open student modeling, social comparison, and recommendation. The architecture fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components as follows:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the [[Mastery Grids Interface]]&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices  ==&amp;gt; source code]&lt;br /&gt;
&lt;br /&gt;
*backend [[CUMULATE|user modeling]], [[Personalization|personalization]] (recommendation, navigation support) services&lt;br /&gt;
&lt;br /&gt;
*backend [[Smart Content|content]] providing applications&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the following figure.&lt;br /&gt;
&lt;br /&gt;
[[Image:arch_v2.png|Aggregate Architecture]]&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Adaptive_Navigation_Support_and_Open_Social_Learner_Modeling_for_PAL&amp;diff=3000</id>
		<title>Adaptive Navigation Support and Open Social Learner Modeling for PAL</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Adaptive_Navigation_Support_and_Open_Social_Learner_Modeling_for_PAL&amp;diff=3000"/>
		<updated>2016-03-07T21:21:17Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* Open Social Learner Modeling Interfaces */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;== Description ==&lt;br /&gt;
&lt;br /&gt;
The goal of this project is to leverage the power of [[open social learner modeling]] and [[adaptive navigation support]] in the context of the envisioned Personalized Assistant for Learning (PAL). The project is supported by the [http://adlnet.gov  Advanced Distributed Learning Initiative] contract W911QY13C0032.&lt;br /&gt;
&lt;br /&gt;
== Directions of work ==&lt;br /&gt;
&lt;br /&gt;
The project focuses on both exploration and implementation of adaptive navigation support and open social learner modeling and pursues three directions of work&lt;br /&gt;
&lt;br /&gt;
* Exploring open social learner modeling interface for diverse learning content&lt;br /&gt;
* Enhancing algorithms for personalized guidance using knowledge-based and social approaches &lt;br /&gt;
* Developing architectural solutions and authoring tools to support open social learner modeling&lt;br /&gt;
&lt;br /&gt;
===Open Social Learner Modeling Interfaces===&lt;br /&gt;
&lt;br /&gt;
Our latest implementation of Open Social Learner Modeling (OSLM) is [[Mastery Grids Interface]] system. Mastery Grids is both, a innovative OSML interface and an adaptive E-learning platform with integrated functionalities enabling multi-facet social comparison, open user modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
&lt;br /&gt;
=== The Architecture ===&lt;br /&gt;
The architecture supporting Mastery Grids fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the [[Mastery Grids Interface]],&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services,&lt;br /&gt;
&lt;br /&gt;
*backend user modeling services, and&lt;br /&gt;
&lt;br /&gt;
*backend content providing applications.&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the next figure. &lt;br /&gt;
&lt;br /&gt;
[[Image:architecture_v1.png]]&lt;br /&gt;
&lt;br /&gt;
=== Authoring Tools ===&lt;br /&gt;
&lt;br /&gt;
The set of authoring tools developed for the project include tools for creating several kinds of smart learning content as well as tools to create adaptive courses that use this content&lt;br /&gt;
&lt;br /&gt;
==== Content Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to create and index annotated examples. [[ContentAuthoring|more]]&lt;br /&gt;
&lt;br /&gt;
==== Course Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to create courses for Mastery Grids. [[CourseAuthoring|more]]&lt;br /&gt;
&lt;br /&gt;
==== Group Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to define groups of students who can access the course. [[GroupAuthoring|more]]&lt;br /&gt;
&lt;br /&gt;
==== Authoring Portal ====&lt;br /&gt;
This is the central portal for providing access to the course authoring and group authoring tools. [[AuthoringPortal|more]]&lt;br /&gt;
&lt;br /&gt;
=== JSWebEx ===&lt;br /&gt;
&lt;br /&gt;
The new client for WebEx system. [[JSWebEx|more]]&lt;br /&gt;
&lt;br /&gt;
== Systems ==&lt;br /&gt;
&lt;br /&gt;
=== Mastery Grids ===&lt;br /&gt;
Mastery Grids is a visual-rich, interactive, adaptive E-learning system and framework with integrated functionalities enabling multi-facet social comparison, open social student modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
&lt;br /&gt;
[[Mastery Grids Interface|==&amp;gt;More]]&lt;br /&gt;
&lt;br /&gt;
=== Aggregate ===&lt;br /&gt;
[[Aggregate|More]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Links == &lt;br /&gt;
Software sources and documentation is in GitHub. The Mastery Grids Interface, backend Aggregate and documentation can be found [https://github.com/PAWSLabUniversityOfPittsburgh/MasteryGrids here]. User model services can be found in [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices here].&lt;br /&gt;
&lt;br /&gt;
A demo view of MasteryGrids can be accessed [http://adapt2.sis.pitt.edu/um-vis-adl/index.html?usr=adl01&amp;amp;grp=ADL&amp;amp;sid=test&amp;amp;cid=13&amp;amp;data-top-n-grp=5&amp;amp;def-val-rep-lvl-id=p&amp;amp;def-val-res-id=AVG&amp;amp;ui-tbar-rep-lvl-vis=0&amp;amp;ui-tbar-topic-size-vis=0 here]&lt;br /&gt;
&lt;br /&gt;
== Publications ==&lt;br /&gt;
* Gonzalez-Brenes, J. P., Huang, Y., and Brusilovsky, P. (2013) FAST: Feature-Aware Student Knowledge Tracing. In:  Proceedings of NIPS 2013 Workshop on Data Driven Education, Lake Tahoe, NV, December 10, 2013, ([http://d-scholarship.pitt.edu/20353/ paper])&lt;br /&gt;
* Hosseini, R. and Brusilovsky, P. (2013) JavaParser: A Fine-Grain Concept Indexing Tool for Java Problems. In:  Proceedings of The First Workshop on AI-supported Education for Computer Science (AIEDCS) at the 16th Annual Conference on Artificial Intelligence in Education, AIED 2013, Memphis, TN, USA, July 13, 2013, pp. 60-63. ([https://d-scholarship.pitt.edu/secure/26270/1/AIED2013-workshop-camera_ready_version.pdf paper]) ([http://www.slideshare.net/RoyaHosseini1/java-parser-a-fine-grained-indexing-tool-and-its-application presentation])&lt;br /&gt;
* Hosseini, R., Brusilovsky, P., and Guerra, J. (2013) Knowledge Maximizer: Concept-based Adaptive Problem Sequencing for Exam Preparation. In:  Proceedings of the 16th International Conference on Artificial Intelligence in Education (AIED 2013), Memphis, USA, pp. 848-851.  ([https://d-scholarship.pitt.edu/secure/26271/4/AIED2013-camera-ready-Knowledge_maximizer_.pdf paper]) ([http://www.slideshare.net/RoyaHosseini1/aied-2013 poster])&lt;br /&gt;
* Brusilovsky, P., Baishya, D., Hosseini, R., Guerra, J., and Liang, M. (2013) KnowledgeZoom for Java: A Concept-Based Exam Study Tool  with a Zoomable Open Student Model. In:  Proceedings of 2013 IEEE 13th International Conference on Advanced Learning Technologies, Beijing, China, July 15-18, 2013, pp. 275-279. ([http://dx.doi.org/10.1109/ICALT.2013.86 paper]) ([http://www.slideshare.net/RoyaHosseini1/kowledge-zoom-michelle-48735584 presentation])&lt;br /&gt;
* Brusilovsky, P. (2014) Addictive Links: Engaging Students through Adaptive Navigation Support and Open Social Student Modeling (Keynote talk). In:  Proceedings of WWW 2014 Workshop on Web-based Education Technologies, Seoul, Korea, April 8, 2014. ([http://www.slideshare.net/pbrusilovsky/addictive-links-keynote-talk-at-www-2014-workshop presentation])&lt;br /&gt;
* Huang, Y., Xu, Y., and Brusilovsky, P. (2014) Doing More with Less: Student Modeling and Performance Prediction with Reduced Content Models. In: V. Dimitrova, et al. (eds.) Proceedings of 22nd Conference on User Modeling, Adaptation and Personalization (UMAP 2014), Aalborg, Denmark, July 7-11, 2014, Springer Verlag, pp. 338-349. ([http://www.slideshare.net/pbrusilovsky/umap-v1 presentation][http://link.springer.com/chapter/10.1007%2F978-3-319-08786-3_30 paper])&lt;br /&gt;
* Hosseini, R. and Brusilovsky, P. (2014) Example-Based Problem Solving Support Using concept Analysis of Programming Content. In: S. Trausan-Matu, K. Boyer, M. Crosby and K. Panourgia (eds.) Proceedings of 12th International Conference on Intelligent Tutoring Systems (ITS 2014), Honolulu, HI, USA, June 5-9, 2014, Springer International Publishing, pp. 683-685. ([https://d-scholarship.pitt.edu/secure/26268/1/CameraReady_ITS2014_paper.pdf paper])  ([http://www.slideshare.net/RoyaHosseini1/presentation-48735557 presentation])&lt;br /&gt;
* Hosseini, R., Vihavainen, A., and Brusilovsky, P. (2014) Exploring Problem Solving Paths in a Java Programming Course. In:  Proceedings of Psychology of Programming Interest Group Annual Conference, PPIG 2014, Brighton, UK, June 25-27, 2014, pp. 65-76. ([https://d-scholarship.pitt.edu/secure/26272/1/PPIG_2014_camera_ready.pdf paper]) ([http://www.slideshare.net/RoyaHosseini1/ppig2014-problem-solvingpaths presentation])&lt;br /&gt;
* Huang, Y., González-Brenes, J. P., and Brusilovsky, P. (2014) General Features in Knowledge Tracing to Model Multiple Subskills, Temporal Item Response Theory, and Expert Knowledge. In: J. Stamper, Z. Pardos, M. Mavrikis and B. M. McLaren (eds.) Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014), London, UK, July 4-7,  2014, pp. 84-91. (First two authors contributed equally. Nominated for Best Paper Award) ([http://www.slideshare.net/huangyun/fast-presentation-48711687 presentation][http://educationaldatamining.org/EDM2014/uploads/procs2014/long%20papers/84_EDM-2014-Full.pdf paper][http://www.slideshare.net/huangyun/2015edm-featureaware-student-knowledge-tracing-tutorial tutorial] [http://ml-smores.github.io/fast/ code])&lt;br /&gt;
* Khajah, M. M., Huang, Y., González-Brenes, J. P., Mozer, M. C., and Brusilovsky, P. (2014) Integrating Knowledge Tracing and Item Response Theory: A Tale of Two Frameworks. In: I. Cantador, M. Chi, R. Farzan and R. Jäschke (eds.) Proceedings of Workshop on Personalization Approaches in Learning Environments (PALE 2014) at the 22th International Conference on User Modeling, Adaptation, and Personalization, UMAP 2014, Aalborg, Denmark, July 11, 2014, CEUR, pp. 7-12. (First three authors contributed equally) ([http://www.slideshare.net/huangyun/pale-public-slideshare presentation][http://ceur-ws.org/Vol-1181/pale2014_paper_01.pdf paper]).&lt;br /&gt;
* Yudelson, M., Hosseini, R., Vihavainen, A., and Brusilovsky, P. (2014) Investigating Automated Student Modeling in a Java MOOC. In: J. Stamper, Z. Pardos, M. Mavrikis and B. M. McLaren (eds.) Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014), London, UK, July 4-7,  2014, pp. 261-264. ([https://d-scholarship.pitt.edu/secure/26273/1/EDM2014YudelsonHVB_camready.pdf paper]) ([http://www.slideshare.net/RoyaHosseini1/edm2014-investigating-automated-student-modeling-in-a-java-mooc presentation])&lt;br /&gt;
* Sahebi, S., Huang, Y., and Brusilovsky, P. (2014) Parameterized Exercises in Java Programming: Using Knowledge Structure for Performance Prediction. In:  Proceedings of The second Workshop on AI-supported Education for Computer Science (AIEDCS) at 12th International Conference on Intelligent Tutoring Systems ITS 2014, Honolulu, Hawaii, June 6 2014. ([http://d-scholarship.pitt.edu/21915/ paper])([http://www.slideshare.net/chagh/parameterized-exercises-in-java-programming-using-knowledge-structure-for-performance-prediction presentation])&lt;br /&gt;
* Sahebi, S., Huang, Y., and Brusilovsky, P. (2014) Predicting Student Performance in Solving Parameterized Exercises. In: S. Trausan-Matu, K. Boyer, M. Crosby and K. Panourgia (eds.) Proceedings of 12th International Conference on Intelligent Tutoring Systems (ITS 2014), Honolulu, HI, USA, June 5-9, 2014, Springer International Publishing, pp. 496-503, ([http://d-scholarship.pitt.edu/21916/ paper]) ([http://www.slideshare.net/chagh/its14-pitttemplate presentation])&lt;br /&gt;
* Guerra, J., Sahebi, S., Lin, Y.-R., and Brusilovsky, P. (2014) The Problem Solving Genome: Analyzing Sequential Patterns of Student Work with Parameterized Exercises. In: J. Stamper, Z. Pardos, M. Mavrikis and B. M. McLaren (eds.) Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014), London, UK, July 4-7,  2014, pp. 153-160 ([http://www.slideshare.net/huangyun/guerra-the-problemsolvinggenome presentation][http://educationaldatamining.org/EDM2014/uploads/procs2014/long%20papers/153_EDM-2014-Full.pdf paper]) &lt;br /&gt;
* Loboda, T., Guerra, J., Hosseini, R., and Brusilovsky, P. (2014) Mastery Grids: An Open Source Social Educational Progress Visualization. In: S. de Freitas, C. Rensing, P. J. Muñoz Merino and T. Ley (eds.) Proceedings of 9th European Conference on Technology Enhanced Learning (EC-TEL 2014), Graz, Austria, September 16-19, 2014 (Best paper award). ([http://link.springer.com/chapter/10.1007%2F978-3-319-11200-8_18#page-1 paper]) ([http://www.slideshare.net/pbrusilovsky/ectel2014-mg presentation])&lt;br /&gt;
* Brusilovsky, P., Edwards, S., Kumar, A., Malmi, L., Benotti, L., Buck, D., Ihantola, P., Prince, R., Sirkiä, T., Sosnovsky, S., Urquiza, J., Vihavainen, A., and Wollowski, M. (2014) Increasing Adoption of Smart Learning Content for Computer Science Education. In:  Proceedings of Proceedings of the Working Group Reports of the 2014 on Innovation &amp;amp;amp; Technology in Computer Science Education Conference, Uppsala, Sweden, ACM, pp. 31-57. ([http://dx.doi.org/10.1145/2713609.2713611 paper])&lt;br /&gt;
* Gonzalez-Brenes, J. P., Huang, Y. (2014) The White Method: Towards Automatic Evaluation Metrics for Adaptive Tutoring Systems. In:  Proceedings of NIPS 2014 Workshop on Human Propelled Machine Learning, Montreal, Canada, December 13, 2014 ([http://d-scholarship.pitt.edu/26061/ paper])&lt;br /&gt;
* Huang, Y., González-Brenes, J. P., and Brusilovsky, P. (2015) The FAST toolkit for Unsupervised Learning of HMMs with Features. In: The Machine Learning Open Source Software workshop at the 32nd International Conference on Machine Learning (ICML-MLOSS 2015), Lille, France July 10, 2015. ([http://d-scholarship.pitt.edu/26043/ paper][http://mloss.org/software/view/609/ code])&lt;br /&gt;
* Huang, Y., González-Brenes, J. P., Kumar, R., Brusilovsky, P. (2015) A Framework for Multifaceted Evaluation of Student Models. In: Proceedings of the 8th International Conference on Educational Data Mining (EDM 2015), Madrid, Spain, pp. 203-210. ([http://www.educationaldatamining.org/EDM2015/uploads/papers/paper_164.pdf paper]) ([http://www.slideshare.net/huangyun/2015edm-a-framework-for-multifaceted-evaluation-of-student-models-polygon presentation])&lt;br /&gt;
* Huang, Y., González-Brenes, J. P., Brusilovsky, P. (2015) Challenges of Using Observational Data to Determine the Importance of Example Usage. In: Proceedings of the 17th International Conference on Artificial Intelligence in Education (AIED 2015), Madrid, Spain, pp. 633-637. ([http://d-scholarship.pitt.edu/26056/ paper])&lt;br /&gt;
* Gonzalez-Brenes, J. P., Huang, Y. (2015) Your model is predictive— but is it useful? Theoretical and Empirical Considerations of a New Paradigm for Adaptive Tutoring Evaluation. In: Proceedings of the 8th International Conference on Educational Data Mining (EDM 2015), Madrid, Spain, pp. 187-194. ([https://www.researchgate.net/publication/280805929_The_Value_of_Social_Comparing_Open_Student_Modeling_and_Open_Social_Student_Modeling paper] [http://www.slideshare.net/pbrusilovsky/umap2015-mg presentation])&lt;br /&gt;
* Brusilovsky, P., Somyurek, S., Guerra, J., Hosseini, R., and Zadorozhny, V. (2015) The Value of Social: Comparing Open Student Modeling and Open Social Student Modeling. In: F. Ricci, K. Bontcheva, O. Conlan and S. Lawless (eds.) Proceedings of 23nd Conference on User Modeling, Adaptation and Personalization (UMAP 2015), Dublin, Ireland, , June 29 - July 3, 2015, Springer Verlag, pp. 44-55 ([http://d-scholarship.pitt.edu/26046/ paper] [http://www.slideshare.net/huangyun/2015-edm-leopard-for-adaptive-tutoring-evaluation presentation])&lt;br /&gt;
* Guerra, J., Huang, Y., Hosseini, R., &amp;amp; Brusilovsky, P. (2015, June). Graph Analysis of Student Model Networks. In Proceedings of the Second International Workshop on Graph-Based Educational Data Mining (GEDM 2015). CEUR-WS. ([https://d-scholarship.pitt.edu/secure/25933/1/graph_analysis.pdf paper]) ([http://www.slideshare.net/mallium/graph-analysis-of-student-model-networks presentation])&lt;br /&gt;
* Guerra, J., Huang, Y., Hosseini, R., &amp;amp; Brusilovsky, P. Exploring the Effects of Open Social Student Model Beyond Social Comparison. In ISLG 2015 Fourth Workshop on Intelligent Support for Learning in Groups (p. 19). ([https://d-scholarship.pitt.edu/secure/25931/1/islg_pap4.pdf paper]) ([http://www.slideshare.net/mallium/exploring-the-effects-of-open-social-student-model-beyond-social-comparison poster])&lt;br /&gt;
* Hosseini, R., Hsiao, I.-H., Guerra, J., Brusilovsky, P. (2015) Off the Beaten Path: The Impact of Adaptive Content Sequencing on Student Navigation in an Open Social Student Modeling Interface. In: Proceedings of the 17th International Conference on Artificial Intelligence in Education (AIED 2015), Madrid, Spain, pp. 624-628. ([https://d-scholarship.pitt.edu/secure/25938/1/paper_183.pdf paper]) ([http://www.slideshare.net/RoyaHosseini1/aied-2015-poster-off-the-beaten-path-the-impact-of-adaptive-content-sequencing-on-student-navigation-in-an-open-social-student-modeling-interface poster])&lt;br /&gt;
* Hosseini, R., Hsiao, I.-H., Guerra, J., Brusilovsky, P. (2015) What Should I Do Next? Adaptive Sequencing in the Context of Open Social Student Modeling. Proceedings of 10th European Conference on Technology Enhanced Learning (EC-TEL 2015), Toledo, Spain, September 15-18, 2015, pp. 155-168. ([https://d-scholarship.pitt.edu/secure/26266/1/camera_ready.pdf paper])([http://www.slideshare.net/RoyaHosseini1/ectel-2015 presentation]).&lt;br /&gt;
* Somyürek, S. &amp;amp; Brusilovsky, P. (2015). Impact of Open Social Student Modeling on Self-Assessment of Performance. Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2009 (E-Learn 2015). Kona, Hawaii, United States, October 19-22, 2015&lt;br /&gt;
* Hosseini, R., Sirkiä, T., Guerra, J., Brusilovsky, P., Malmi, L. (2016) Animated Examples as Practice Content in a Java Programming Course. Proceedings of the 47th ACM technical symposium on Computer Science Education (SIGCSE), Memphis, Tennessee, March 2-5, 2016. ([https://d-scholarship.pitt.edu/secure/27083/1/sigcse2016.pdf paper])  ([http://www.slideshare.net/RoyaHosseini1/sigcse-2016 presentation])&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Publications&amp;diff=2985</id>
		<title>Publications</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Publications&amp;diff=2985"/>
		<updated>2016-01-14T15:34:18Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* Mastery Grids */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;===ADVISE===&lt;br /&gt;
{{:Adaptive_VIBE}}&lt;br /&gt;
&lt;br /&gt;
===[[AnnotEx]]===&lt;br /&gt;
* Hsiao, I. and Brusilvsky, P. (2011) '''The Role of Community Feedback in the Student Example Authoring Process: an Evaluation of AnnotEx''', British Journal of Educational Technology, Vol 42, Issue 3, Pages 482 - 499 [http://dx.doi.org/10.1111/j.1467-8535.2009.01030.x DOI]&lt;br /&gt;
* Hsiao, I. &amp;amp; Brusilovsky. P. (2008). '''Modeling Peer Review in Example Annotation'''. ICCE, The 16th International Conference on Computers in Education, Taipei, Taiwan, October 27- 31, 2008, ICCE [http://apsce.net/icce2008/contents/proceeding_0357.pdf URL] [http://www.sis.pitt.edu/~ihsiao/pub/5page_camera%20ready_ICCE_Modeling_Peer_Review_in_Example_Annotation.pdf PDF]&lt;br /&gt;
* Brusilovsky, P., Hsiao, I. &amp;amp; Yuldelson, M. (2008) '''Annotated Program Examples as First Class Objects in an Educational Digital Library''', JCDL 2008 [http://doi.acm.org/10.1145/1378889.1378946 DOI]&lt;br /&gt;
* Hsiao, I. &amp;amp; Brusilovsky, P. (2007) '''Collaborative Example Authoring System: The Value of Re-annotation based on Community Feedback''',In: J. Nall and R. Robson (eds.) Proceedings of World Conference on E-Learning, E-Learn 2007,Quebec City, Canada, October 15-19, 2007, AACE  [http://www.editlib.org/p/26914 URL] [http://www.sis.pitt.edu/~ihsiao/pub/2007ELearn_Collaborative_Example_Authoring_System_final.pdf PDF]&lt;br /&gt;
&lt;br /&gt;
===ASSIST===&lt;br /&gt;
* Freyne, J., Farzan, R., and Coyle, M. (2007). Toward the exploitation of social access patterns for recommendation. RecSys 2007.&lt;br /&gt;
* Farzan, R., Coyle, M., Freyne, J., Brusilovsky, P., and Smyth, P. (2007). ASSIST: Adaptive Social Support for Information Space Traversal. Hypertext 2007.&lt;br /&gt;
* Freyne J., Farzan R., Brusilovsky P., Smyth B., and Coyle M. (2007). Collecting Community Wisdom: Integrating Social Search &amp;amp; Social Navigation. In Proceedings of International Conference on Intelligent User Interfaces&lt;br /&gt;
&lt;br /&gt;
===Conference Navigator===&lt;br /&gt;
* [[User:Clau|López C.]], Farzan R., Sahebi S., and Brusilovsky P. (2013). What Influences the Decision to Participate in Audience-bounded Online Communities. iConference 2013.&lt;br /&gt;
* [[User:Clau|López C.]], Farzan R., and Brusilovsky P. (2012). Personalized Incremental Users' Engagement: Driving Contributions One Step Forward. ACM GROUP 2012.&lt;br /&gt;
* Farzan R., and Brusilovsky P. Where did the Researchers Go? Supporting Social Navigation at a Large Academic Conference. Hypertext 2008.&lt;br /&gt;
&lt;br /&gt;
===[[CourseAgent]]===&lt;br /&gt;
* Farzan, R. and Brusilovsky, P. (2011) Encouraging User Participation in a Course Recommender System: An Impact on User Behavior. Computers in Human Behavior  27 (1), 276-284.&lt;br /&gt;
&lt;br /&gt;
*Farzan R. &amp;amp; Brusilovsky P. (2006). Social Navigation Support in a Course Recommendation System. In proceedings of 4th International Conference on Adaptive Hypermedia and Adaptive Web-based Systems.&lt;br /&gt;
&lt;br /&gt;
===[[CUMULATE]]===&lt;br /&gt;
{{:CUMULATE}}&lt;br /&gt;
&lt;br /&gt;
===[[Eventur]]===&lt;br /&gt;
* Lee, D. H. (2008) PITTCULT: Trust-based Cultural Event Recommender, Proceedings of Doctoral Symposium on the 2nd ACM International Conference on Recommender Systems, Lausanne, Switzerland, October 23 ~ 25, 2008 &lt;br /&gt;
* Lee, D. H. (2008) PITTCULT: Recommender System using Trusted Human Network, Student Research Competition in Hypertext 2008, Pittsburgh PA., USA, June 19 ~ 21, 2008, Third Prize Winner of ACM Student Research Competition in Hypertext 2008 &amp;amp; Finalist for the Grand Prize of ACM SRC sponsored by Microsoft Research [http://pittcult.sis.pitt.edu/help.jsp Presentation], [http://www.sigweb.org/ht08/srcposters/lee.pdf pdf]&lt;br /&gt;
&lt;br /&gt;
===[[Knowledge Sea II]] and [[AnnotatEd]]===&lt;br /&gt;
* Lin, Y., Brusilovsky, P., and He, D. (2011) Improving Self-Organizing Information Maps as Navigational Tools: A Semantic Approach. Online Information Review  35 (3), 401-424.&lt;br /&gt;
* Farzan, R. and Brusilovsky P. (2008). AnnotatEd: A Social Navigation and Annotation Service for Web-based Educational Resources. Journal of the New Review of Hypermedia and Multimedia (NRHM)&lt;br /&gt;
* Ahn, J., Farzan, R., and Brusilovsky, P. (2006) Social Search in the Context of Social Navigation. Journal of the Korean Society for Information Management 23(2):147-165.&lt;br /&gt;
* Bateman S., Farzan R., Brusilovsky P., and McCalla G. (2006) OATS: The Open Annotation and Tagging System. In Proceedings 3rd annual e-learning conference on Intelligent Interactive Learning Object Repositories&lt;br /&gt;
* Farzan R. &amp;amp; Brusilovsky P. (2006). AnnotatEd: A Social Navigation and Annotation Service for Web-based Educational Resources. In Proceedings of E-Learn 2006--World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education.Winner of outstanding paper award.  &lt;br /&gt;
* Mertens R., Farzan R.,and Brusilovsky P. (2006) Social Navigation in Web Lectures. In proceedings of Seventeenth ACM Conference on Hypertext and Hypermedia(short paper).&lt;br /&gt;
* Farzan, R. &amp;amp; Brusilovsky P. (2005). Social Navigation Support through Annotation-Based Group Modeling.  In proceedings of 10th International Conference on User Modeling.&lt;br /&gt;
* Brusilovsky P., Farzan R. &amp;amp; Ahn J. (2005). Comprehensive Personalized Information Access in an Educational Digital Library. In proceedings of Joint Conference on Digital Libraries.&lt;br /&gt;
* Brusilovsky, P., Chavan, G., Farzan, R. (2004). Social Adaptive Navigation Support for Open Corpus Electronic Textbooks  - In: P.De Bra (ed.) Proceedings of the Third International Conference on Adaptive Hypermedia and Adaptive Web-based Systems (AH'2004), Eindhoven, the Netherlands&lt;br /&gt;
&lt;br /&gt;
===Mastery Grids===&lt;br /&gt;
* Guerra, J., Hosseini, R.,  Somyurek, S., Brusilovsky, P. (2016). An Intelligent Interface for Learning Content: Combining an Open Learner Model and Social Comparison to Support Self-Regulated Learning and Engagement. I press (available [http://columbus.exp.sis.pitt.edu/jguerra/files/intelligent-interface-learning.pdf here]). IUI 2016.&lt;br /&gt;
* Loboda, T., Guerra, J., Hosseini, R., Brusilovsky, P. (2014). Mastery Grids: An Open Source Social Educational Progress Visualization. Paper accepted in ECTEL 2014&lt;br /&gt;
&lt;br /&gt;
===[[NameSieve]]===&lt;br /&gt;
{{:NameSieve}}&lt;br /&gt;
&lt;br /&gt;
===[[NavEx]]===&lt;br /&gt;
{{:NavEx}}&lt;br /&gt;
&lt;br /&gt;
===[[PERSEUS]]===&lt;br /&gt;
{{:PERSEUS}}&lt;br /&gt;
&lt;br /&gt;
===[[Proactive]]===&lt;br /&gt;
* Lee, D. H. &amp;amp; Brusilovsky, P. (2007) Fighting Information Overflow with Personalized Comprehensive Information Access: A Proactive Job Recommender, Proceedings of the Third International Conference on Autonomic and Autonomous Systems (ICAS '07), Athens, Greece, June 19 ~ 25, 2007 &lt;br /&gt;
* Lee, D. and Brusilovsky, P. (2012) Proactive: Comprehensive Access to Job Information. Journal of Information Processing Systems  8 (4), 707-724.&lt;br /&gt;
&lt;br /&gt;
===[[Progressor]]===&lt;br /&gt;
{{:Progressor}}&lt;br /&gt;
===[[ProgressorPlus]]===&lt;br /&gt;
{{:ProgressorPlus}}&lt;br /&gt;
&lt;br /&gt;
===[[QuizJET]] and [[JavaGuide]]===&lt;br /&gt;
* Sahebi, S., Huang, Y., and Brusilovsky, P. (2014) '''Predicting Student Performance in Solving Parameterized Exercises''', ITS 2014.&lt;br /&gt;
* Sahebi, S., Huang, Y., and Brusilovsky, P. (2014) '''Parameterized Exercises in Java Programming: using Knowledge Structure for Performance Prediction''', The second Workshop on AI-supported Education for Computer Science (AIEDCS) 2014.&lt;br /&gt;
* Guerra, J., Sahebi, S., Lin, Y., Brusilovsky, P. The Problem Solving Genome: Analyzing Sequential Patterns of Student Work with Parameterized Exercises. Paper accepted in EDM 2014&lt;br /&gt;
{{:QuizJET}}&lt;br /&gt;
&lt;br /&gt;
===[[TaskSieve]]===&lt;br /&gt;
{{:TaskSieve}}&lt;br /&gt;
&lt;br /&gt;
===[[YourNews]]===&lt;br /&gt;
{{:YourNews}}&lt;br /&gt;
&lt;br /&gt;
===[[Others]]===&lt;br /&gt;
* Sahebi, S. and Brusilovsky, P. (2013) '''Cross-Domain Recommendation in a Cold-Start Context: The impact of User Profile Size on the Quality of Recommendation''', UMAP 2013, Springer Berlin Heidelberg, p. 289-295.&lt;br /&gt;
* Brusilovsky, P., Hsiao, I-H. and Folajimi, Y., (2011) '''QuizMap: Open Social Student Modeling and Adaptive Navigation Support with TreeMaps''', In: Proceedings of 6th European Conference on Technology Enhanced Education (ECTEL), ECTEL 2011, Palermo, Italy, September 20-23, 2011, Springer-Verlag, Volume 6964/2011, pp.71-82&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Publications&amp;diff=2984</id>
		<title>Publications</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Publications&amp;diff=2984"/>
		<updated>2016-01-14T15:33:59Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* Mastery Grids */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;===ADVISE===&lt;br /&gt;
{{:Adaptive_VIBE}}&lt;br /&gt;
&lt;br /&gt;
===[[AnnotEx]]===&lt;br /&gt;
* Hsiao, I. and Brusilvsky, P. (2011) '''The Role of Community Feedback in the Student Example Authoring Process: an Evaluation of AnnotEx''', British Journal of Educational Technology, Vol 42, Issue 3, Pages 482 - 499 [http://dx.doi.org/10.1111/j.1467-8535.2009.01030.x DOI]&lt;br /&gt;
* Hsiao, I. &amp;amp; Brusilovsky. P. (2008). '''Modeling Peer Review in Example Annotation'''. ICCE, The 16th International Conference on Computers in Education, Taipei, Taiwan, October 27- 31, 2008, ICCE [http://apsce.net/icce2008/contents/proceeding_0357.pdf URL] [http://www.sis.pitt.edu/~ihsiao/pub/5page_camera%20ready_ICCE_Modeling_Peer_Review_in_Example_Annotation.pdf PDF]&lt;br /&gt;
* Brusilovsky, P., Hsiao, I. &amp;amp; Yuldelson, M. (2008) '''Annotated Program Examples as First Class Objects in an Educational Digital Library''', JCDL 2008 [http://doi.acm.org/10.1145/1378889.1378946 DOI]&lt;br /&gt;
* Hsiao, I. &amp;amp; Brusilovsky, P. (2007) '''Collaborative Example Authoring System: The Value of Re-annotation based on Community Feedback''',In: J. Nall and R. Robson (eds.) Proceedings of World Conference on E-Learning, E-Learn 2007,Quebec City, Canada, October 15-19, 2007, AACE  [http://www.editlib.org/p/26914 URL] [http://www.sis.pitt.edu/~ihsiao/pub/2007ELearn_Collaborative_Example_Authoring_System_final.pdf PDF]&lt;br /&gt;
&lt;br /&gt;
===ASSIST===&lt;br /&gt;
* Freyne, J., Farzan, R., and Coyle, M. (2007). Toward the exploitation of social access patterns for recommendation. RecSys 2007.&lt;br /&gt;
* Farzan, R., Coyle, M., Freyne, J., Brusilovsky, P., and Smyth, P. (2007). ASSIST: Adaptive Social Support for Information Space Traversal. Hypertext 2007.&lt;br /&gt;
* Freyne J., Farzan R., Brusilovsky P., Smyth B., and Coyle M. (2007). Collecting Community Wisdom: Integrating Social Search &amp;amp; Social Navigation. In Proceedings of International Conference on Intelligent User Interfaces&lt;br /&gt;
&lt;br /&gt;
===Conference Navigator===&lt;br /&gt;
* [[User:Clau|López C.]], Farzan R., Sahebi S., and Brusilovsky P. (2013). What Influences the Decision to Participate in Audience-bounded Online Communities. iConference 2013.&lt;br /&gt;
* [[User:Clau|López C.]], Farzan R., and Brusilovsky P. (2012). Personalized Incremental Users' Engagement: Driving Contributions One Step Forward. ACM GROUP 2012.&lt;br /&gt;
* Farzan R., and Brusilovsky P. Where did the Researchers Go? Supporting Social Navigation at a Large Academic Conference. Hypertext 2008.&lt;br /&gt;
&lt;br /&gt;
===[[CourseAgent]]===&lt;br /&gt;
* Farzan, R. and Brusilovsky, P. (2011) Encouraging User Participation in a Course Recommender System: An Impact on User Behavior. Computers in Human Behavior  27 (1), 276-284.&lt;br /&gt;
&lt;br /&gt;
*Farzan R. &amp;amp; Brusilovsky P. (2006). Social Navigation Support in a Course Recommendation System. In proceedings of 4th International Conference on Adaptive Hypermedia and Adaptive Web-based Systems.&lt;br /&gt;
&lt;br /&gt;
===[[CUMULATE]]===&lt;br /&gt;
{{:CUMULATE}}&lt;br /&gt;
&lt;br /&gt;
===[[Eventur]]===&lt;br /&gt;
* Lee, D. H. (2008) PITTCULT: Trust-based Cultural Event Recommender, Proceedings of Doctoral Symposium on the 2nd ACM International Conference on Recommender Systems, Lausanne, Switzerland, October 23 ~ 25, 2008 &lt;br /&gt;
* Lee, D. H. (2008) PITTCULT: Recommender System using Trusted Human Network, Student Research Competition in Hypertext 2008, Pittsburgh PA., USA, June 19 ~ 21, 2008, Third Prize Winner of ACM Student Research Competition in Hypertext 2008 &amp;amp; Finalist for the Grand Prize of ACM SRC sponsored by Microsoft Research [http://pittcult.sis.pitt.edu/help.jsp Presentation], [http://www.sigweb.org/ht08/srcposters/lee.pdf pdf]&lt;br /&gt;
&lt;br /&gt;
===[[Knowledge Sea II]] and [[AnnotatEd]]===&lt;br /&gt;
* Lin, Y., Brusilovsky, P., and He, D. (2011) Improving Self-Organizing Information Maps as Navigational Tools: A Semantic Approach. Online Information Review  35 (3), 401-424.&lt;br /&gt;
* Farzan, R. and Brusilovsky P. (2008). AnnotatEd: A Social Navigation and Annotation Service for Web-based Educational Resources. Journal of the New Review of Hypermedia and Multimedia (NRHM)&lt;br /&gt;
* Ahn, J., Farzan, R., and Brusilovsky, P. (2006) Social Search in the Context of Social Navigation. Journal of the Korean Society for Information Management 23(2):147-165.&lt;br /&gt;
* Bateman S., Farzan R., Brusilovsky P., and McCalla G. (2006) OATS: The Open Annotation and Tagging System. In Proceedings 3rd annual e-learning conference on Intelligent Interactive Learning Object Repositories&lt;br /&gt;
* Farzan R. &amp;amp; Brusilovsky P. (2006). AnnotatEd: A Social Navigation and Annotation Service for Web-based Educational Resources. In Proceedings of E-Learn 2006--World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education.Winner of outstanding paper award.  &lt;br /&gt;
* Mertens R., Farzan R.,and Brusilovsky P. (2006) Social Navigation in Web Lectures. In proceedings of Seventeenth ACM Conference on Hypertext and Hypermedia(short paper).&lt;br /&gt;
* Farzan, R. &amp;amp; Brusilovsky P. (2005). Social Navigation Support through Annotation-Based Group Modeling.  In proceedings of 10th International Conference on User Modeling.&lt;br /&gt;
* Brusilovsky P., Farzan R. &amp;amp; Ahn J. (2005). Comprehensive Personalized Information Access in an Educational Digital Library. In proceedings of Joint Conference on Digital Libraries.&lt;br /&gt;
* Brusilovsky, P., Chavan, G., Farzan, R. (2004). Social Adaptive Navigation Support for Open Corpus Electronic Textbooks  - In: P.De Bra (ed.) Proceedings of the Third International Conference on Adaptive Hypermedia and Adaptive Web-based Systems (AH'2004), Eindhoven, the Netherlands&lt;br /&gt;
&lt;br /&gt;
===Mastery Grids===&lt;br /&gt;
* Loboda, T., Guerra, J., Hosseini, R., Brusilovsky, P. (2014). Mastery Grids: An Open Source Social Educational Progress Visualization. Paper accepted in ECTEL 2014&lt;br /&gt;
* Guerra, J., Hosseini, R.,  Somyurek, S., Brusilovsky, P. (2016). An Intelligent Interface for Learning Content: Combining an Open Learner Model and Social Comparison to Support Self-Regulated Learning and Engagement. I press (available [http://columbus.exp.sis.pitt.edu/jguerra/files/intelligent-interface-learning.pdf here]). IUI 2016.&lt;br /&gt;
&lt;br /&gt;
===[[NameSieve]]===&lt;br /&gt;
{{:NameSieve}}&lt;br /&gt;
&lt;br /&gt;
===[[NavEx]]===&lt;br /&gt;
{{:NavEx}}&lt;br /&gt;
&lt;br /&gt;
===[[PERSEUS]]===&lt;br /&gt;
{{:PERSEUS}}&lt;br /&gt;
&lt;br /&gt;
===[[Proactive]]===&lt;br /&gt;
* Lee, D. H. &amp;amp; Brusilovsky, P. (2007) Fighting Information Overflow with Personalized Comprehensive Information Access: A Proactive Job Recommender, Proceedings of the Third International Conference on Autonomic and Autonomous Systems (ICAS '07), Athens, Greece, June 19 ~ 25, 2007 &lt;br /&gt;
* Lee, D. and Brusilovsky, P. (2012) Proactive: Comprehensive Access to Job Information. Journal of Information Processing Systems  8 (4), 707-724.&lt;br /&gt;
&lt;br /&gt;
===[[Progressor]]===&lt;br /&gt;
{{:Progressor}}&lt;br /&gt;
===[[ProgressorPlus]]===&lt;br /&gt;
{{:ProgressorPlus}}&lt;br /&gt;
&lt;br /&gt;
===[[QuizJET]] and [[JavaGuide]]===&lt;br /&gt;
* Sahebi, S., Huang, Y., and Brusilovsky, P. (2014) '''Predicting Student Performance in Solving Parameterized Exercises''', ITS 2014.&lt;br /&gt;
* Sahebi, S., Huang, Y., and Brusilovsky, P. (2014) '''Parameterized Exercises in Java Programming: using Knowledge Structure for Performance Prediction''', The second Workshop on AI-supported Education for Computer Science (AIEDCS) 2014.&lt;br /&gt;
* Guerra, J., Sahebi, S., Lin, Y., Brusilovsky, P. The Problem Solving Genome: Analyzing Sequential Patterns of Student Work with Parameterized Exercises. Paper accepted in EDM 2014&lt;br /&gt;
{{:QuizJET}}&lt;br /&gt;
&lt;br /&gt;
===[[TaskSieve]]===&lt;br /&gt;
{{:TaskSieve}}&lt;br /&gt;
&lt;br /&gt;
===[[YourNews]]===&lt;br /&gt;
{{:YourNews}}&lt;br /&gt;
&lt;br /&gt;
===[[Others]]===&lt;br /&gt;
* Sahebi, S. and Brusilovsky, P. (2013) '''Cross-Domain Recommendation in a Cold-Start Context: The impact of User Profile Size on the Quality of Recommendation''', UMAP 2013, Springer Berlin Heidelberg, p. 289-295.&lt;br /&gt;
* Brusilovsky, P., Hsiao, I-H. and Folajimi, Y., (2011) '''QuizMap: Open Social Student Modeling and Adaptive Navigation Support with TreeMaps''', In: Proceedings of 6th European Conference on Technology Enhanced Education (ECTEL), ECTEL 2011, Palermo, Italy, September 20-23, 2011, Springer-Verlag, Volume 6964/2011, pp.71-82&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Publications&amp;diff=2983</id>
		<title>Publications</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Publications&amp;diff=2983"/>
		<updated>2016-01-14T15:33:45Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* Mastery Grids */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;===ADVISE===&lt;br /&gt;
{{:Adaptive_VIBE}}&lt;br /&gt;
&lt;br /&gt;
===[[AnnotEx]]===&lt;br /&gt;
* Hsiao, I. and Brusilvsky, P. (2011) '''The Role of Community Feedback in the Student Example Authoring Process: an Evaluation of AnnotEx''', British Journal of Educational Technology, Vol 42, Issue 3, Pages 482 - 499 [http://dx.doi.org/10.1111/j.1467-8535.2009.01030.x DOI]&lt;br /&gt;
* Hsiao, I. &amp;amp; Brusilovsky. P. (2008). '''Modeling Peer Review in Example Annotation'''. ICCE, The 16th International Conference on Computers in Education, Taipei, Taiwan, October 27- 31, 2008, ICCE [http://apsce.net/icce2008/contents/proceeding_0357.pdf URL] [http://www.sis.pitt.edu/~ihsiao/pub/5page_camera%20ready_ICCE_Modeling_Peer_Review_in_Example_Annotation.pdf PDF]&lt;br /&gt;
* Brusilovsky, P., Hsiao, I. &amp;amp; Yuldelson, M. (2008) '''Annotated Program Examples as First Class Objects in an Educational Digital Library''', JCDL 2008 [http://doi.acm.org/10.1145/1378889.1378946 DOI]&lt;br /&gt;
* Hsiao, I. &amp;amp; Brusilovsky, P. (2007) '''Collaborative Example Authoring System: The Value of Re-annotation based on Community Feedback''',In: J. Nall and R. Robson (eds.) Proceedings of World Conference on E-Learning, E-Learn 2007,Quebec City, Canada, October 15-19, 2007, AACE  [http://www.editlib.org/p/26914 URL] [http://www.sis.pitt.edu/~ihsiao/pub/2007ELearn_Collaborative_Example_Authoring_System_final.pdf PDF]&lt;br /&gt;
&lt;br /&gt;
===ASSIST===&lt;br /&gt;
* Freyne, J., Farzan, R., and Coyle, M. (2007). Toward the exploitation of social access patterns for recommendation. RecSys 2007.&lt;br /&gt;
* Farzan, R., Coyle, M., Freyne, J., Brusilovsky, P., and Smyth, P. (2007). ASSIST: Adaptive Social Support for Information Space Traversal. Hypertext 2007.&lt;br /&gt;
* Freyne J., Farzan R., Brusilovsky P., Smyth B., and Coyle M. (2007). Collecting Community Wisdom: Integrating Social Search &amp;amp; Social Navigation. In Proceedings of International Conference on Intelligent User Interfaces&lt;br /&gt;
&lt;br /&gt;
===Conference Navigator===&lt;br /&gt;
* [[User:Clau|López C.]], Farzan R., Sahebi S., and Brusilovsky P. (2013). What Influences the Decision to Participate in Audience-bounded Online Communities. iConference 2013.&lt;br /&gt;
* [[User:Clau|López C.]], Farzan R., and Brusilovsky P. (2012). Personalized Incremental Users' Engagement: Driving Contributions One Step Forward. ACM GROUP 2012.&lt;br /&gt;
* Farzan R., and Brusilovsky P. Where did the Researchers Go? Supporting Social Navigation at a Large Academic Conference. Hypertext 2008.&lt;br /&gt;
&lt;br /&gt;
===[[CourseAgent]]===&lt;br /&gt;
* Farzan, R. and Brusilovsky, P. (2011) Encouraging User Participation in a Course Recommender System: An Impact on User Behavior. Computers in Human Behavior  27 (1), 276-284.&lt;br /&gt;
&lt;br /&gt;
*Farzan R. &amp;amp; Brusilovsky P. (2006). Social Navigation Support in a Course Recommendation System. In proceedings of 4th International Conference on Adaptive Hypermedia and Adaptive Web-based Systems.&lt;br /&gt;
&lt;br /&gt;
===[[CUMULATE]]===&lt;br /&gt;
{{:CUMULATE}}&lt;br /&gt;
&lt;br /&gt;
===[[Eventur]]===&lt;br /&gt;
* Lee, D. H. (2008) PITTCULT: Trust-based Cultural Event Recommender, Proceedings of Doctoral Symposium on the 2nd ACM International Conference on Recommender Systems, Lausanne, Switzerland, October 23 ~ 25, 2008 &lt;br /&gt;
* Lee, D. H. (2008) PITTCULT: Recommender System using Trusted Human Network, Student Research Competition in Hypertext 2008, Pittsburgh PA., USA, June 19 ~ 21, 2008, Third Prize Winner of ACM Student Research Competition in Hypertext 2008 &amp;amp; Finalist for the Grand Prize of ACM SRC sponsored by Microsoft Research [http://pittcult.sis.pitt.edu/help.jsp Presentation], [http://www.sigweb.org/ht08/srcposters/lee.pdf pdf]&lt;br /&gt;
&lt;br /&gt;
===[[Knowledge Sea II]] and [[AnnotatEd]]===&lt;br /&gt;
* Lin, Y., Brusilovsky, P., and He, D. (2011) Improving Self-Organizing Information Maps as Navigational Tools: A Semantic Approach. Online Information Review  35 (3), 401-424.&lt;br /&gt;
* Farzan, R. and Brusilovsky P. (2008). AnnotatEd: A Social Navigation and Annotation Service for Web-based Educational Resources. Journal of the New Review of Hypermedia and Multimedia (NRHM)&lt;br /&gt;
* Ahn, J., Farzan, R., and Brusilovsky, P. (2006) Social Search in the Context of Social Navigation. Journal of the Korean Society for Information Management 23(2):147-165.&lt;br /&gt;
* Bateman S., Farzan R., Brusilovsky P., and McCalla G. (2006) OATS: The Open Annotation and Tagging System. In Proceedings 3rd annual e-learning conference on Intelligent Interactive Learning Object Repositories&lt;br /&gt;
* Farzan R. &amp;amp; Brusilovsky P. (2006). AnnotatEd: A Social Navigation and Annotation Service for Web-based Educational Resources. In Proceedings of E-Learn 2006--World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education.Winner of outstanding paper award.  &lt;br /&gt;
* Mertens R., Farzan R.,and Brusilovsky P. (2006) Social Navigation in Web Lectures. In proceedings of Seventeenth ACM Conference on Hypertext and Hypermedia(short paper).&lt;br /&gt;
* Farzan, R. &amp;amp; Brusilovsky P. (2005). Social Navigation Support through Annotation-Based Group Modeling.  In proceedings of 10th International Conference on User Modeling.&lt;br /&gt;
* Brusilovsky P., Farzan R. &amp;amp; Ahn J. (2005). Comprehensive Personalized Information Access in an Educational Digital Library. In proceedings of Joint Conference on Digital Libraries.&lt;br /&gt;
* Brusilovsky, P., Chavan, G., Farzan, R. (2004). Social Adaptive Navigation Support for Open Corpus Electronic Textbooks  - In: P.De Bra (ed.) Proceedings of the Third International Conference on Adaptive Hypermedia and Adaptive Web-based Systems (AH'2004), Eindhoven, the Netherlands&lt;br /&gt;
&lt;br /&gt;
===Mastery Grids===&lt;br /&gt;
* Loboda, T., Guerra, J., Hosseini, R., Brusilovsky, P. (2014). Mastery Grids: An Open Source Social Educational Progress Visualization. Paper accepted in ECTEL 2014&lt;br /&gt;
* Guerra, J., Hosseini, R.,  Somy{\&amp;quot;u}rek, S., Brusilovsky, P. (2016). An Intelligent Interface for Learning Content: Combining an Open Learner Model and Social Comparison to Support Self-Regulated Learning and Engagement. I press (available [http://columbus.exp.sis.pitt.edu/jguerra/files/intelligent-interface-learning.pdf here]). IUI 2016.&lt;br /&gt;
&lt;br /&gt;
===[[NameSieve]]===&lt;br /&gt;
{{:NameSieve}}&lt;br /&gt;
&lt;br /&gt;
===[[NavEx]]===&lt;br /&gt;
{{:NavEx}}&lt;br /&gt;
&lt;br /&gt;
===[[PERSEUS]]===&lt;br /&gt;
{{:PERSEUS}}&lt;br /&gt;
&lt;br /&gt;
===[[Proactive]]===&lt;br /&gt;
* Lee, D. H. &amp;amp; Brusilovsky, P. (2007) Fighting Information Overflow with Personalized Comprehensive Information Access: A Proactive Job Recommender, Proceedings of the Third International Conference on Autonomic and Autonomous Systems (ICAS '07), Athens, Greece, June 19 ~ 25, 2007 &lt;br /&gt;
* Lee, D. and Brusilovsky, P. (2012) Proactive: Comprehensive Access to Job Information. Journal of Information Processing Systems  8 (4), 707-724.&lt;br /&gt;
&lt;br /&gt;
===[[Progressor]]===&lt;br /&gt;
{{:Progressor}}&lt;br /&gt;
===[[ProgressorPlus]]===&lt;br /&gt;
{{:ProgressorPlus}}&lt;br /&gt;
&lt;br /&gt;
===[[QuizJET]] and [[JavaGuide]]===&lt;br /&gt;
* Sahebi, S., Huang, Y., and Brusilovsky, P. (2014) '''Predicting Student Performance in Solving Parameterized Exercises''', ITS 2014.&lt;br /&gt;
* Sahebi, S., Huang, Y., and Brusilovsky, P. (2014) '''Parameterized Exercises in Java Programming: using Knowledge Structure for Performance Prediction''', The second Workshop on AI-supported Education for Computer Science (AIEDCS) 2014.&lt;br /&gt;
* Guerra, J., Sahebi, S., Lin, Y., Brusilovsky, P. The Problem Solving Genome: Analyzing Sequential Patterns of Student Work with Parameterized Exercises. Paper accepted in EDM 2014&lt;br /&gt;
{{:QuizJET}}&lt;br /&gt;
&lt;br /&gt;
===[[TaskSieve]]===&lt;br /&gt;
{{:TaskSieve}}&lt;br /&gt;
&lt;br /&gt;
===[[YourNews]]===&lt;br /&gt;
{{:YourNews}}&lt;br /&gt;
&lt;br /&gt;
===[[Others]]===&lt;br /&gt;
* Sahebi, S. and Brusilovsky, P. (2013) '''Cross-Domain Recommendation in a Cold-Start Context: The impact of User Profile Size on the Quality of Recommendation''', UMAP 2013, Springer Berlin Heidelberg, p. 289-295.&lt;br /&gt;
* Brusilovsky, P., Hsiao, I-H. and Folajimi, Y., (2011) '''QuizMap: Open Social Student Modeling and Adaptive Navigation Support with TreeMaps''', In: Proceedings of 6th European Conference on Technology Enhanced Education (ECTEL), ECTEL 2011, Palermo, Italy, September 20-23, 2011, Springer-Verlag, Volume 6964/2011, pp.71-82&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Publications&amp;diff=2982</id>
		<title>Publications</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Publications&amp;diff=2982"/>
		<updated>2016-01-14T15:33:27Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* Mastery Grids */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;===ADVISE===&lt;br /&gt;
{{:Adaptive_VIBE}}&lt;br /&gt;
&lt;br /&gt;
===[[AnnotEx]]===&lt;br /&gt;
* Hsiao, I. and Brusilvsky, P. (2011) '''The Role of Community Feedback in the Student Example Authoring Process: an Evaluation of AnnotEx''', British Journal of Educational Technology, Vol 42, Issue 3, Pages 482 - 499 [http://dx.doi.org/10.1111/j.1467-8535.2009.01030.x DOI]&lt;br /&gt;
* Hsiao, I. &amp;amp; Brusilovsky. P. (2008). '''Modeling Peer Review in Example Annotation'''. ICCE, The 16th International Conference on Computers in Education, Taipei, Taiwan, October 27- 31, 2008, ICCE [http://apsce.net/icce2008/contents/proceeding_0357.pdf URL] [http://www.sis.pitt.edu/~ihsiao/pub/5page_camera%20ready_ICCE_Modeling_Peer_Review_in_Example_Annotation.pdf PDF]&lt;br /&gt;
* Brusilovsky, P., Hsiao, I. &amp;amp; Yuldelson, M. (2008) '''Annotated Program Examples as First Class Objects in an Educational Digital Library''', JCDL 2008 [http://doi.acm.org/10.1145/1378889.1378946 DOI]&lt;br /&gt;
* Hsiao, I. &amp;amp; Brusilovsky, P. (2007) '''Collaborative Example Authoring System: The Value of Re-annotation based on Community Feedback''',In: J. Nall and R. Robson (eds.) Proceedings of World Conference on E-Learning, E-Learn 2007,Quebec City, Canada, October 15-19, 2007, AACE  [http://www.editlib.org/p/26914 URL] [http://www.sis.pitt.edu/~ihsiao/pub/2007ELearn_Collaborative_Example_Authoring_System_final.pdf PDF]&lt;br /&gt;
&lt;br /&gt;
===ASSIST===&lt;br /&gt;
* Freyne, J., Farzan, R., and Coyle, M. (2007). Toward the exploitation of social access patterns for recommendation. RecSys 2007.&lt;br /&gt;
* Farzan, R., Coyle, M., Freyne, J., Brusilovsky, P., and Smyth, P. (2007). ASSIST: Adaptive Social Support for Information Space Traversal. Hypertext 2007.&lt;br /&gt;
* Freyne J., Farzan R., Brusilovsky P., Smyth B., and Coyle M. (2007). Collecting Community Wisdom: Integrating Social Search &amp;amp; Social Navigation. In Proceedings of International Conference on Intelligent User Interfaces&lt;br /&gt;
&lt;br /&gt;
===Conference Navigator===&lt;br /&gt;
* [[User:Clau|López C.]], Farzan R., Sahebi S., and Brusilovsky P. (2013). What Influences the Decision to Participate in Audience-bounded Online Communities. iConference 2013.&lt;br /&gt;
* [[User:Clau|López C.]], Farzan R., and Brusilovsky P. (2012). Personalized Incremental Users' Engagement: Driving Contributions One Step Forward. ACM GROUP 2012.&lt;br /&gt;
* Farzan R., and Brusilovsky P. Where did the Researchers Go? Supporting Social Navigation at a Large Academic Conference. Hypertext 2008.&lt;br /&gt;
&lt;br /&gt;
===[[CourseAgent]]===&lt;br /&gt;
* Farzan, R. and Brusilovsky, P. (2011) Encouraging User Participation in a Course Recommender System: An Impact on User Behavior. Computers in Human Behavior  27 (1), 276-284.&lt;br /&gt;
&lt;br /&gt;
*Farzan R. &amp;amp; Brusilovsky P. (2006). Social Navigation Support in a Course Recommendation System. In proceedings of 4th International Conference on Adaptive Hypermedia and Adaptive Web-based Systems.&lt;br /&gt;
&lt;br /&gt;
===[[CUMULATE]]===&lt;br /&gt;
{{:CUMULATE}}&lt;br /&gt;
&lt;br /&gt;
===[[Eventur]]===&lt;br /&gt;
* Lee, D. H. (2008) PITTCULT: Trust-based Cultural Event Recommender, Proceedings of Doctoral Symposium on the 2nd ACM International Conference on Recommender Systems, Lausanne, Switzerland, October 23 ~ 25, 2008 &lt;br /&gt;
* Lee, D. H. (2008) PITTCULT: Recommender System using Trusted Human Network, Student Research Competition in Hypertext 2008, Pittsburgh PA., USA, June 19 ~ 21, 2008, Third Prize Winner of ACM Student Research Competition in Hypertext 2008 &amp;amp; Finalist for the Grand Prize of ACM SRC sponsored by Microsoft Research [http://pittcult.sis.pitt.edu/help.jsp Presentation], [http://www.sigweb.org/ht08/srcposters/lee.pdf pdf]&lt;br /&gt;
&lt;br /&gt;
===[[Knowledge Sea II]] and [[AnnotatEd]]===&lt;br /&gt;
* Lin, Y., Brusilovsky, P., and He, D. (2011) Improving Self-Organizing Information Maps as Navigational Tools: A Semantic Approach. Online Information Review  35 (3), 401-424.&lt;br /&gt;
* Farzan, R. and Brusilovsky P. (2008). AnnotatEd: A Social Navigation and Annotation Service for Web-based Educational Resources. Journal of the New Review of Hypermedia and Multimedia (NRHM)&lt;br /&gt;
* Ahn, J., Farzan, R., and Brusilovsky, P. (2006) Social Search in the Context of Social Navigation. Journal of the Korean Society for Information Management 23(2):147-165.&lt;br /&gt;
* Bateman S., Farzan R., Brusilovsky P., and McCalla G. (2006) OATS: The Open Annotation and Tagging System. In Proceedings 3rd annual e-learning conference on Intelligent Interactive Learning Object Repositories&lt;br /&gt;
* Farzan R. &amp;amp; Brusilovsky P. (2006). AnnotatEd: A Social Navigation and Annotation Service for Web-based Educational Resources. In Proceedings of E-Learn 2006--World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education.Winner of outstanding paper award.  &lt;br /&gt;
* Mertens R., Farzan R.,and Brusilovsky P. (2006) Social Navigation in Web Lectures. In proceedings of Seventeenth ACM Conference on Hypertext and Hypermedia(short paper).&lt;br /&gt;
* Farzan, R. &amp;amp; Brusilovsky P. (2005). Social Navigation Support through Annotation-Based Group Modeling.  In proceedings of 10th International Conference on User Modeling.&lt;br /&gt;
* Brusilovsky P., Farzan R. &amp;amp; Ahn J. (2005). Comprehensive Personalized Information Access in an Educational Digital Library. In proceedings of Joint Conference on Digital Libraries.&lt;br /&gt;
* Brusilovsky, P., Chavan, G., Farzan, R. (2004). Social Adaptive Navigation Support for Open Corpus Electronic Textbooks  - In: P.De Bra (ed.) Proceedings of the Third International Conference on Adaptive Hypermedia and Adaptive Web-based Systems (AH'2004), Eindhoven, the Netherlands&lt;br /&gt;
&lt;br /&gt;
===Mastery Grids===&lt;br /&gt;
* Loboda, T., Guerra, J., Hosseini, R., Brusilovsky, P. (2014). Mastery Grids: An Open Source Social Educational Progress Visualization. Paper accepted in ECTEL 2014&lt;br /&gt;
* Guerra, J., Hosseini, R.,  Somy{\&amp;quot;u}rek, S., Brusilovsky, P. (2016). An Intelligent Interface for Learning Content: Combining an Open Learner Model and Social Comparison to Support Self-Regulated Learning and Engagement. I press (available [here  http://columbus.exp.sis.pitt.edu/jguerra/files/intelligent-interface-learning.pdf]). IUI 2016.&lt;br /&gt;
&lt;br /&gt;
===[[NameSieve]]===&lt;br /&gt;
{{:NameSieve}}&lt;br /&gt;
&lt;br /&gt;
===[[NavEx]]===&lt;br /&gt;
{{:NavEx}}&lt;br /&gt;
&lt;br /&gt;
===[[PERSEUS]]===&lt;br /&gt;
{{:PERSEUS}}&lt;br /&gt;
&lt;br /&gt;
===[[Proactive]]===&lt;br /&gt;
* Lee, D. H. &amp;amp; Brusilovsky, P. (2007) Fighting Information Overflow with Personalized Comprehensive Information Access: A Proactive Job Recommender, Proceedings of the Third International Conference on Autonomic and Autonomous Systems (ICAS '07), Athens, Greece, June 19 ~ 25, 2007 &lt;br /&gt;
* Lee, D. and Brusilovsky, P. (2012) Proactive: Comprehensive Access to Job Information. Journal of Information Processing Systems  8 (4), 707-724.&lt;br /&gt;
&lt;br /&gt;
===[[Progressor]]===&lt;br /&gt;
{{:Progressor}}&lt;br /&gt;
===[[ProgressorPlus]]===&lt;br /&gt;
{{:ProgressorPlus}}&lt;br /&gt;
&lt;br /&gt;
===[[QuizJET]] and [[JavaGuide]]===&lt;br /&gt;
* Sahebi, S., Huang, Y., and Brusilovsky, P. (2014) '''Predicting Student Performance in Solving Parameterized Exercises''', ITS 2014.&lt;br /&gt;
* Sahebi, S., Huang, Y., and Brusilovsky, P. (2014) '''Parameterized Exercises in Java Programming: using Knowledge Structure for Performance Prediction''', The second Workshop on AI-supported Education for Computer Science (AIEDCS) 2014.&lt;br /&gt;
* Guerra, J., Sahebi, S., Lin, Y., Brusilovsky, P. The Problem Solving Genome: Analyzing Sequential Patterns of Student Work with Parameterized Exercises. Paper accepted in EDM 2014&lt;br /&gt;
{{:QuizJET}}&lt;br /&gt;
&lt;br /&gt;
===[[TaskSieve]]===&lt;br /&gt;
{{:TaskSieve}}&lt;br /&gt;
&lt;br /&gt;
===[[YourNews]]===&lt;br /&gt;
{{:YourNews}}&lt;br /&gt;
&lt;br /&gt;
===[[Others]]===&lt;br /&gt;
* Sahebi, S. and Brusilovsky, P. (2013) '''Cross-Domain Recommendation in a Cold-Start Context: The impact of User Profile Size on the Quality of Recommendation''', UMAP 2013, Springer Berlin Heidelberg, p. 289-295.&lt;br /&gt;
* Brusilovsky, P., Hsiao, I-H. and Folajimi, Y., (2011) '''QuizMap: Open Social Student Modeling and Adaptive Navigation Support with TreeMaps''', In: Proceedings of 6th European Conference on Technology Enhanced Education (ECTEL), ECTEL 2011, Palermo, Italy, September 20-23, 2011, Springer-Verlag, Volume 6964/2011, pp.71-82&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Publications&amp;diff=2981</id>
		<title>Publications</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Publications&amp;diff=2981"/>
		<updated>2016-01-14T15:31:42Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* Mastery Grids */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;===ADVISE===&lt;br /&gt;
{{:Adaptive_VIBE}}&lt;br /&gt;
&lt;br /&gt;
===[[AnnotEx]]===&lt;br /&gt;
* Hsiao, I. and Brusilvsky, P. (2011) '''The Role of Community Feedback in the Student Example Authoring Process: an Evaluation of AnnotEx''', British Journal of Educational Technology, Vol 42, Issue 3, Pages 482 - 499 [http://dx.doi.org/10.1111/j.1467-8535.2009.01030.x DOI]&lt;br /&gt;
* Hsiao, I. &amp;amp; Brusilovsky. P. (2008). '''Modeling Peer Review in Example Annotation'''. ICCE, The 16th International Conference on Computers in Education, Taipei, Taiwan, October 27- 31, 2008, ICCE [http://apsce.net/icce2008/contents/proceeding_0357.pdf URL] [http://www.sis.pitt.edu/~ihsiao/pub/5page_camera%20ready_ICCE_Modeling_Peer_Review_in_Example_Annotation.pdf PDF]&lt;br /&gt;
* Brusilovsky, P., Hsiao, I. &amp;amp; Yuldelson, M. (2008) '''Annotated Program Examples as First Class Objects in an Educational Digital Library''', JCDL 2008 [http://doi.acm.org/10.1145/1378889.1378946 DOI]&lt;br /&gt;
* Hsiao, I. &amp;amp; Brusilovsky, P. (2007) '''Collaborative Example Authoring System: The Value of Re-annotation based on Community Feedback''',In: J. Nall and R. Robson (eds.) Proceedings of World Conference on E-Learning, E-Learn 2007,Quebec City, Canada, October 15-19, 2007, AACE  [http://www.editlib.org/p/26914 URL] [http://www.sis.pitt.edu/~ihsiao/pub/2007ELearn_Collaborative_Example_Authoring_System_final.pdf PDF]&lt;br /&gt;
&lt;br /&gt;
===ASSIST===&lt;br /&gt;
* Freyne, J., Farzan, R., and Coyle, M. (2007). Toward the exploitation of social access patterns for recommendation. RecSys 2007.&lt;br /&gt;
* Farzan, R., Coyle, M., Freyne, J., Brusilovsky, P., and Smyth, P. (2007). ASSIST: Adaptive Social Support for Information Space Traversal. Hypertext 2007.&lt;br /&gt;
* Freyne J., Farzan R., Brusilovsky P., Smyth B., and Coyle M. (2007). Collecting Community Wisdom: Integrating Social Search &amp;amp; Social Navigation. In Proceedings of International Conference on Intelligent User Interfaces&lt;br /&gt;
&lt;br /&gt;
===Conference Navigator===&lt;br /&gt;
* [[User:Clau|López C.]], Farzan R., Sahebi S., and Brusilovsky P. (2013). What Influences the Decision to Participate in Audience-bounded Online Communities. iConference 2013.&lt;br /&gt;
* [[User:Clau|López C.]], Farzan R., and Brusilovsky P. (2012). Personalized Incremental Users' Engagement: Driving Contributions One Step Forward. ACM GROUP 2012.&lt;br /&gt;
* Farzan R., and Brusilovsky P. Where did the Researchers Go? Supporting Social Navigation at a Large Academic Conference. Hypertext 2008.&lt;br /&gt;
&lt;br /&gt;
===[[CourseAgent]]===&lt;br /&gt;
* Farzan, R. and Brusilovsky, P. (2011) Encouraging User Participation in a Course Recommender System: An Impact on User Behavior. Computers in Human Behavior  27 (1), 276-284.&lt;br /&gt;
&lt;br /&gt;
*Farzan R. &amp;amp; Brusilovsky P. (2006). Social Navigation Support in a Course Recommendation System. In proceedings of 4th International Conference on Adaptive Hypermedia and Adaptive Web-based Systems.&lt;br /&gt;
&lt;br /&gt;
===[[CUMULATE]]===&lt;br /&gt;
{{:CUMULATE}}&lt;br /&gt;
&lt;br /&gt;
===[[Eventur]]===&lt;br /&gt;
* Lee, D. H. (2008) PITTCULT: Trust-based Cultural Event Recommender, Proceedings of Doctoral Symposium on the 2nd ACM International Conference on Recommender Systems, Lausanne, Switzerland, October 23 ~ 25, 2008 &lt;br /&gt;
* Lee, D. H. (2008) PITTCULT: Recommender System using Trusted Human Network, Student Research Competition in Hypertext 2008, Pittsburgh PA., USA, June 19 ~ 21, 2008, Third Prize Winner of ACM Student Research Competition in Hypertext 2008 &amp;amp; Finalist for the Grand Prize of ACM SRC sponsored by Microsoft Research [http://pittcult.sis.pitt.edu/help.jsp Presentation], [http://www.sigweb.org/ht08/srcposters/lee.pdf pdf]&lt;br /&gt;
&lt;br /&gt;
===[[Knowledge Sea II]] and [[AnnotatEd]]===&lt;br /&gt;
* Lin, Y., Brusilovsky, P., and He, D. (2011) Improving Self-Organizing Information Maps as Navigational Tools: A Semantic Approach. Online Information Review  35 (3), 401-424.&lt;br /&gt;
* Farzan, R. and Brusilovsky P. (2008). AnnotatEd: A Social Navigation and Annotation Service for Web-based Educational Resources. Journal of the New Review of Hypermedia and Multimedia (NRHM)&lt;br /&gt;
* Ahn, J., Farzan, R., and Brusilovsky, P. (2006) Social Search in the Context of Social Navigation. Journal of the Korean Society for Information Management 23(2):147-165.&lt;br /&gt;
* Bateman S., Farzan R., Brusilovsky P., and McCalla G. (2006) OATS: The Open Annotation and Tagging System. In Proceedings 3rd annual e-learning conference on Intelligent Interactive Learning Object Repositories&lt;br /&gt;
* Farzan R. &amp;amp; Brusilovsky P. (2006). AnnotatEd: A Social Navigation and Annotation Service for Web-based Educational Resources. In Proceedings of E-Learn 2006--World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education.Winner of outstanding paper award.  &lt;br /&gt;
* Mertens R., Farzan R.,and Brusilovsky P. (2006) Social Navigation in Web Lectures. In proceedings of Seventeenth ACM Conference on Hypertext and Hypermedia(short paper).&lt;br /&gt;
* Farzan, R. &amp;amp; Brusilovsky P. (2005). Social Navigation Support through Annotation-Based Group Modeling.  In proceedings of 10th International Conference on User Modeling.&lt;br /&gt;
* Brusilovsky P., Farzan R. &amp;amp; Ahn J. (2005). Comprehensive Personalized Information Access in an Educational Digital Library. In proceedings of Joint Conference on Digital Libraries.&lt;br /&gt;
* Brusilovsky, P., Chavan, G., Farzan, R. (2004). Social Adaptive Navigation Support for Open Corpus Electronic Textbooks  - In: P.De Bra (ed.) Proceedings of the Third International Conference on Adaptive Hypermedia and Adaptive Web-based Systems (AH'2004), Eindhoven, the Netherlands&lt;br /&gt;
&lt;br /&gt;
===Mastery Grids===&lt;br /&gt;
* Loboda, T., Guerra, J., Hosseini, R., Brusilovsky, P. (2014). Mastery Grids: An Open Source Social Educational Progress Visualization. Paper accepted in ECTEL 2014&lt;br /&gt;
* Guerra, J., Hosseini, R.,  Somy{\&amp;quot;u}rek, S., Brusilovsky, P. (2016). An Intelligent Interface for Learning Content: Combining an Open Learner Model and Social Comparison to Support Self-Regulated Learning and Engagement. I press (available [here | http://columbus.exp.sis.pitt.edu/jguerra/files/intelligent-interface-learning.pdf]). IUI 2016.&lt;br /&gt;
&lt;br /&gt;
===[[NameSieve]]===&lt;br /&gt;
{{:NameSieve}}&lt;br /&gt;
&lt;br /&gt;
===[[NavEx]]===&lt;br /&gt;
{{:NavEx}}&lt;br /&gt;
&lt;br /&gt;
===[[PERSEUS]]===&lt;br /&gt;
{{:PERSEUS}}&lt;br /&gt;
&lt;br /&gt;
===[[Proactive]]===&lt;br /&gt;
* Lee, D. H. &amp;amp; Brusilovsky, P. (2007) Fighting Information Overflow with Personalized Comprehensive Information Access: A Proactive Job Recommender, Proceedings of the Third International Conference on Autonomic and Autonomous Systems (ICAS '07), Athens, Greece, June 19 ~ 25, 2007 &lt;br /&gt;
* Lee, D. and Brusilovsky, P. (2012) Proactive: Comprehensive Access to Job Information. Journal of Information Processing Systems  8 (4), 707-724.&lt;br /&gt;
&lt;br /&gt;
===[[Progressor]]===&lt;br /&gt;
{{:Progressor}}&lt;br /&gt;
===[[ProgressorPlus]]===&lt;br /&gt;
{{:ProgressorPlus}}&lt;br /&gt;
&lt;br /&gt;
===[[QuizJET]] and [[JavaGuide]]===&lt;br /&gt;
* Sahebi, S., Huang, Y., and Brusilovsky, P. (2014) '''Predicting Student Performance in Solving Parameterized Exercises''', ITS 2014.&lt;br /&gt;
* Sahebi, S., Huang, Y., and Brusilovsky, P. (2014) '''Parameterized Exercises in Java Programming: using Knowledge Structure for Performance Prediction''', The second Workshop on AI-supported Education for Computer Science (AIEDCS) 2014.&lt;br /&gt;
* Guerra, J., Sahebi, S., Lin, Y., Brusilovsky, P. The Problem Solving Genome: Analyzing Sequential Patterns of Student Work with Parameterized Exercises. Paper accepted in EDM 2014&lt;br /&gt;
{{:QuizJET}}&lt;br /&gt;
&lt;br /&gt;
===[[TaskSieve]]===&lt;br /&gt;
{{:TaskSieve}}&lt;br /&gt;
&lt;br /&gt;
===[[YourNews]]===&lt;br /&gt;
{{:YourNews}}&lt;br /&gt;
&lt;br /&gt;
===[[Others]]===&lt;br /&gt;
* Sahebi, S. and Brusilovsky, P. (2013) '''Cross-Domain Recommendation in a Cold-Start Context: The impact of User Profile Size on the Quality of Recommendation''', UMAP 2013, Springer Berlin Heidelberg, p. 289-295.&lt;br /&gt;
* Brusilovsky, P., Hsiao, I-H. and Folajimi, Y., (2011) '''QuizMap: Open Social Student Modeling and Adaptive Navigation Support with TreeMaps''', In: Proceedings of 6th European Conference on Technology Enhanced Education (ECTEL), ECTEL 2011, Palermo, Italy, September 20-23, 2011, Springer-Verlag, Volume 6964/2011, pp.71-82&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Adaptive_Navigation_Support_and_Open_Social_Learner_Modeling_for_PAL&amp;diff=2931</id>
		<title>Adaptive Navigation Support and Open Social Learner Modeling for PAL</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Adaptive_Navigation_Support_and_Open_Social_Learner_Modeling_for_PAL&amp;diff=2931"/>
		<updated>2015-10-26T18:56:52Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;== Description ==&lt;br /&gt;
&lt;br /&gt;
The goal of this project is to leverage the power of [[open social learner modeling]] and [[adaptive navigation support]] in the context of the envisioned Personalized Assistant for Learning (PAL). The project is supported by the [http://adlnet.gov|Advanced Distributed Learning Initiative] contract W911QY13C0032.&lt;br /&gt;
&lt;br /&gt;
== Directions of work ==&lt;br /&gt;
&lt;br /&gt;
The project focuses on both exploration and implementation of adaptive navigation support and open social learner modeling and pursues three directions of work&lt;br /&gt;
&lt;br /&gt;
* Exploring open social learner modeling interface for diverse learning content&lt;br /&gt;
* Enhancing algorithms for personalized guidance using knowledge-based and social approaches &lt;br /&gt;
* Developing architectural solutions and authoring tools to support open social learner modeling&lt;br /&gt;
&lt;br /&gt;
===Open Social Learner Modeling Interfaces===&lt;br /&gt;
&lt;br /&gt;
Our latest implementation of Open Social Learner Modeling (OSLM) interface is [[MasteryGrids]] system. Mastery Grids is both, a innovative OSML interface and an adaptive E-learning platform with integrated functionalities enabling multi-facet social comparison, open user modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
&lt;br /&gt;
=== The Architecture ===&lt;br /&gt;
The architecture supporting Mastery Grids fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the [[Mastery Grids Interface]],&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services,&lt;br /&gt;
&lt;br /&gt;
*backend user modeling services, and&lt;br /&gt;
&lt;br /&gt;
*backend content providing applications.&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the next figure. &lt;br /&gt;
&lt;br /&gt;
[[Image:architecture_v1.png]]&lt;br /&gt;
&lt;br /&gt;
=== Authoring Tools ===&lt;br /&gt;
&lt;br /&gt;
The set of authoring tools developed for the project include tools for creating several kinds of smart learning content as well as tools to create adaptive courses that use this content&lt;br /&gt;
&lt;br /&gt;
==== Content Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to create and index annotated examples. [[ContentAuthoring|more]]&lt;br /&gt;
&lt;br /&gt;
==== Course Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to create courses for Mastery Grids. [[CourseAuthoring|more]]&lt;br /&gt;
&lt;br /&gt;
==== Group Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to define groups of students who can access the course. [[GroupAuthoring|more]]&lt;br /&gt;
&lt;br /&gt;
==== Authoring Portal ====&lt;br /&gt;
This is the central portal for providing access to the course authoring and group authoring tools. [[AuthoringPortal|more]]&lt;br /&gt;
&lt;br /&gt;
== Systems ==&lt;br /&gt;
&lt;br /&gt;
=== Mastery Grids ===&lt;br /&gt;
Mastery Grids is a visual-rich, interactive, adaptive E-learning system and framework with integrated functionalities enabling multi-facet social comparison, open social student modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
&lt;br /&gt;
[[Mastery Grids Interface|==&amp;gt;More]]&lt;br /&gt;
&lt;br /&gt;
=== Aggregate ===&lt;br /&gt;
[[Aggregate|More]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Links == &lt;br /&gt;
Software sources and documentation is in GitHub. The Mastery Grids Interface, backend Aggregate and documentation can be found [https://github.com/PAWSLabUniversityOfPittsburgh/MasteryGrids here]. User model services can be found in [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices here].&lt;br /&gt;
&lt;br /&gt;
A demo view of MasteryGrids can be accessed [http://adapt2.sis.pitt.edu/um-vis-adl/index.html?usr=adl01&amp;amp;grp=ADL&amp;amp;sid=test&amp;amp;cid=13&amp;amp;data-top-n-grp=5&amp;amp;def-val-rep-lvl-id=p&amp;amp;def-val-res-id=AVG&amp;amp;ui-tbar-rep-lvl-vis=0&amp;amp;ui-tbar-topic-size-vis=0 here]&lt;br /&gt;
&lt;br /&gt;
== Publications ==&lt;br /&gt;
* Gonzalez-Brenes, J. P., Huang, Y., and Brusilovsky, P. (2013) FAST: Feature-Aware Student Knowledge Tracing. In:  Proceedings of NIPS 2013 Workshop on Data Driven Education, Lake Tahoe, NV, December 10, 2013, ([http://lytics.stanford.edu/datadriveneducation/papers/gonzalezetal.pdf paper])&lt;br /&gt;
* Hosseini, R. and Brusilovsky, P. (2013) JavaParser: A Fine-Grain Concept Indexing Tool for Java Problems. In:  Proceedings of The First Workshop on AI-supported Education for Computer Science (AIEDCS) at the 16th Annual Conference on Artificial Intelligence in Education, AIED 2013, Memphis, TN, USA, July 13, 2013, pp. 60-63. ([https://d-scholarship.pitt.edu/secure/26270/1/AIED2013-workshop-camera_ready_version.pdf paper]) ([http://www.slideshare.net/RoyaHosseini1/java-parser-a-fine-grained-indexing-tool-and-its-application presentation])&lt;br /&gt;
* Hosseini, R., Brusilovsky, P., and Guerra, J. (2013) Knowledge Maximizer: Concept-based Adaptive Problem Sequencing for Exam Preparation. In:  Proceedings of the 16th International Conference on Artificial Intelligence in Education (AIED 2013), Memphis, USA, pp. 848-851.  ([https://d-scholarship.pitt.edu/secure/26271/4/AIED2013-camera-ready-Knowledge_maximizer_.pdf paper]) ([http://www.slideshare.net/RoyaHosseini1/aied-2013 poster])&lt;br /&gt;
* Brusilovsky, P., Baishya, D., Hosseini, R., Guerra, J., and Liang, M. (2013) KnowledgeZoom for Java: A Concept-Based Exam Study Tool  with a Zoomable Open Student Model. In:  Proceedings of 2013 IEEE 13th International Conference on Advanced Learning Technologies, Beijing, China, July 15-18, 2013, pp. 275-279. ([http://dx.doi.org/10.1109/ICALT.2013.86 paper]) ([http://www.slideshare.net/RoyaHosseini1/kowledge-zoom-michelle-48735584 presentation])&lt;br /&gt;
* Brusilovsky, P. (2014) Addictive Links: Engaging Students through Adaptive Navigation Support and Open Social Student Modeling (Keynote talk). In:  Proceedings of WWW 2014 Workshop on Web-based Education Technologies, Seoul, Korea, April 8, 2014. ([http://www.slideshare.net/pbrusilovsky/addictive-links-keynote-talk-at-www-2014-workshop presentation])&lt;br /&gt;
* Huang, Y., Xu, Y., and Brusilovsky, P. (2014) Doing More with Less: Student Modeling and Performance Prediction with Reduced Content Models. In: V. Dimitrova, et al. (eds.) Proceedings of 22nd Conference on User Modeling, Adaptation and Personalization (UMAP 2014), Aalborg, Denmark, July 7-11, 2014, Springer Verlag, pp. 338-349. ([http://www.slideshare.net/pbrusilovsky/umap-v1 presentation][http://link.springer.com/chapter/10.1007%2F978-3-319-08786-3_30 paper])&lt;br /&gt;
* Hosseini, R. and Brusilovsky, P. (2014) Example-Based Problem Solving Support Using concept Analysis of Programming Content. In: S. Trausan-Matu, K. Boyer, M. Crosby and K. Panourgia (eds.) Proceedings of 12th International Conference on Intelligent Tutoring Systems (ITS 2014), Honolulu, HI, USA, June 5-9, 2014, Springer International Publishing, pp. 683-685. ([https://d-scholarship.pitt.edu/secure/26268/1/CameraReady_ITS2014_paper.pdf paper])  ([http://www.slideshare.net/RoyaHosseini1/presentation-48735557 presentation])&lt;br /&gt;
* Hosseini, R., Vihavainen, A., and Brusilovsky, P. (2014) Exploring Problem Solving Paths in a Java Programming Course. In:  Proceedings of Psychology of Programming Interest Group Annual Conference, PPIG 2014, Brighton, UK, June 25-27, 2014, pp. 65-76. ([https://d-scholarship.pitt.edu/secure/26272/1/PPIG_2014_camera_ready.pdf paper]) ([http://www.slideshare.net/RoyaHosseini1/ppig2014-problem-solvingpaths presentation])&lt;br /&gt;
* Huang, Y., González-Brenes, J. P., and Brusilovsky, P. (2014) General Features in Knowledge Tracing to Model Multiple Subskills, Temporal Item Response Theory, and Expert Knowledge. In: J. Stamper, Z. Pardos, M. Mavrikis and B. M. McLaren (eds.) Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014), London, UK, July 4-7,  2014, pp. 84-91. (First two authors contributed equally. Nominated for Best Paper Award) ([http://www.slideshare.net/huangyun/fast-presentation-48711687 presentation][http://educationaldatamining.org/EDM2014/uploads/procs2014/long%20papers/84_EDM-2014-Full.pdf paper][http://ml-smores.github.io/fast/ code])&lt;br /&gt;
* Khajah, M. M., Huang, Y., González-Brenes, J. P., Mozer, M. C., and Brusilovsky, P. (2014) Integrating Knowledge Tracing and Item Response Theory: A Tale of Two Frameworks. In: I. Cantador, M. Chi, R. Farzan and R. Jäschke (eds.) Proceedings of Workshop on Personalization Approaches in Learning Environments (PALE 2014) at the 22th International Conference on User Modeling, Adaptation, and Personalization, UMAP 2014, Aalborg, Denmark, July 11, 2014, CEUR, pp. 7-12. (First three authors contributed equally) ([http://www.slideshare.net/huangyun/pale-public-slideshare presentation][http://ceur-ws.org/Vol-1181/pale2014_paper_01.pdf paper]).&lt;br /&gt;
* Yudelson, M., Hosseini, R., Vihavainen, A., and Brusilovsky, P. (2014) Investigating Automated Student Modeling in a Java MOOC. In: J. Stamper, Z. Pardos, M. Mavrikis and B. M. McLaren (eds.) Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014), London, UK, July 4-7,  2014, pp. 261-264. ([https://d-scholarship.pitt.edu/secure/26273/1/EDM2014YudelsonHVB_camready.pdf paper]) ([http://www.slideshare.net/RoyaHosseini1/edm2014-investigating-automated-student-modeling-in-a-java-mooc presentation])&lt;br /&gt;
* Sahebi, S., Huang, Y., and Brusilovsky, P. (2014) Parameterized Exercises in Java Programming: Using Knowledge Structure for Performance Prediction. In:  Proceedings of The second Workshop on AI-supported Education for Computer Science (AIEDCS) at 12th International Conference on Intelligent Tutoring Systems ITS 2014, Honolulu, Hawaii, June 6 2014. ([http://d-scholarship.pitt.edu/21915/ paper])([http://www.slideshare.net/chagh/parameterized-exercises-in-java-programming-using-knowledge-structure-for-performance-prediction presentation])&lt;br /&gt;
* Sahebi, S., Huang, Y., and Brusilovsky, P. (2014) Predicting Student Performance in Solving Parameterized Exercises. In: S. Trausan-Matu, K. Boyer, M. Crosby and K. Panourgia (eds.) Proceedings of 12th International Conference on Intelligent Tutoring Systems (ITS 2014), Honolulu, HI, USA, June 5-9, 2014, Springer International Publishing, pp. 496-503, ([http://d-scholarship.pitt.edu/21916/ paper]) ([http://www.slideshare.net/chagh/its14-pitttemplate presentation])&lt;br /&gt;
* Guerra, J., Sahebi, S., Lin, Y.-R., and Brusilovsky, P. (2014) The Problem Solving Genome: Analyzing Sequential Patterns of Student Work with Parameterized Exercises. In: J. Stamper, Z. Pardos, M. Mavrikis and B. M. McLaren (eds.) Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014), London, UK, July 4-7,  2014, pp. 153-160 ([http://www.slideshare.net/huangyun/guerra-the-problemsolvinggenome presentation][http://educationaldatamining.org/EDM2014/uploads/procs2014/long%20papers/153_EDM-2014-Full.pdf paper]) &lt;br /&gt;
* Loboda, T., Guerra, J., Hosseini, R., and Brusilovsky, P. (2014) Mastery Grids: An Open Source Social Educational Progress Visualization. In: S. de Freitas, C. Rensing, P. J. Muñoz Merino and T. Ley (eds.) Proceedings of 9th European Conference on Technology Enhanced Learning (EC-TEL 2014), Graz, Austria, September 16-19, 2014 (Best paper award). ([http://link.springer.com/chapter/10.1007%2F978-3-319-11200-8_18#page-1 paper]) ([http://www.slideshare.net/pbrusilovsky/ectel2014-mg presentation])&lt;br /&gt;
* Brusilovsky, P., Edwards, S., Kumar, A., Malmi, L., Benotti, L., Buck, D., Ihantola, P., Prince, R., Sirkiä, T., Sosnovsky, S., Urquiza, J., Vihavainen, A., and Wollowski, M. (2014) Increasing Adoption of Smart Learning Content for Computer Science Education. In:  Proceedings of Proceedings of the Working Group Reports of the 2014 on Innovation &amp;amp;amp; Technology in Computer Science Education Conference, Uppsala, Sweden, ACM, pp. 31-57. ([http://dx.doi.org/10.1145/2713609.2713611 paper])&lt;br /&gt;
* Gonzalez-Brenes, J. P., Huang, Y. (2014) The White Method: Towards Automatic Evaluation Metrics for Adaptive Tutoring Systems. In:  Proceedings of NIPS 2014 Workshop on Human Propelled Machine Learning, Montreal, Canada, December 13, 2014&lt;br /&gt;
* Huang, Y., González-Brenes, J. P., and Brusilovsky, P. (2015) The FAST toolkit for Unsupervised Learning of HMMs with Features. In: The Machine Learning Open Source Software workshop at the 32nd International Conference on Machine Learning (ICML-MLOSS 2015), Lille, France July 10, 2015. ([http://mloss.org/software/view/609/ code])&lt;br /&gt;
* Huang, Y., González-Brenes, J. P., Kumar, R., Brusilovsky, P. (2015) A Framework for Multifaceted Evaluation of Student Models. In: Proceedings of the 8th International Conference on Educational Data Mining (EDM 2015), Madrid, Spain. (Full paper) ([http://www.educationaldatamining.org/EDM2015/uploads/papers/paper_164.pdf paper]) ([http://www.slideshare.net/huangyun/2015edm-a-framework-for-multifaceted-evaluation-of-student-models-polygon presentation])&lt;br /&gt;
* Huang, Y., González-Brenes, J. P., Brusilovsky, P. (2015) Challenges of Using Observational Data to Determine the Importance of Example Usage. In: Proceedings of the 17th International Conference on Artificial Intelligence in Education (AIED 2015), Madrid, Spain.&lt;br /&gt;
* Gonzalez-Brenes, J. P., Huang, Y. (2015) Your model is predictive— but is it useful? Theoretical and Empirical Considerations of a New Paradigm for Adaptive Tutoring Evaluation. In: Proceedings of the 8th International Conference on Educational Data Mining (EDM 2015), Madrid, Spain. (Full paper)&lt;br /&gt;
* Gonzalez-Brenes, J. P., Huang, Y. (2015) Using Data from Real and Simulated Learners to Evaluate Adaptive Tutoring Systems. In: 2nd AIED Workshop on Simulated Learners at the 17th International Conference on Artificial Intelligence in Education (AIED), Madrid, Spain.&lt;br /&gt;
* Gonzalez-Brenes, J. P., Huang, Y. (2015) The Leopard Framework: Towards understanding educational technology interventions with a Pareto Efficiency Perspective. In: The ICML 2015 Workshop on Machine Learning for Education, Friday, July 10, 2015, Lille, France.&lt;br /&gt;
* Guerra, J., Huang, Y., Hosseini, R., &amp;amp; Brusilovsky, P. (2015, June). Graph Analysis of Student Model Networks. In Proceedings of the Second International Workshop on Graph-Based Educational Data Mining (GEDM 2015). CEUR-WS. ([https://d-scholarship.pitt.edu/secure/25933/1/graph_analysis.pdf paper]) ([http://www.slideshare.net/mallium/graph-analysis-of-student-model-networks presentation])&lt;br /&gt;
* Guerra, J., Huang, Y., Hosseini, R., &amp;amp; Brusilovsky, P. Exploring the Effects of Open Social Student Model Beyond Social Comparison. In ISLG 2015 Fourth Workshop on Intelligent Support for Learning in Groups (p. 19). ([https://d-scholarship.pitt.edu/secure/25931/1/islg_pap4.pdf paper]) ([http://www.slideshare.net/mallium/exploring-the-effects-of-open-social-student-model-beyond-social-comparison poster])&lt;br /&gt;
* Hosseini, R., Hsiao, I.-H., Guerra, J., Brusilovsky, P. (2015) Off the Beaten Path: The Impact of Adaptive Content Sequencing on Student Navigation in an Open Social Student Modeling Interface. In: Proceedings of the 17th International Conference on Artificial Intelligence in Education (AIED 2015), Madrid, Spain, pp. 624-628. ([https://d-scholarship.pitt.edu/secure/25938/1/paper_183.pdf paper]) ([http://www.slideshare.net/RoyaHosseini1/aied-2015-poster-off-the-beaten-path-the-impact-of-adaptive-content-sequencing-on-student-navigation-in-an-open-social-student-modeling-interface poster])&lt;br /&gt;
* Hosseini, R., Hsiao, I.-H., Guerra, J., Brusilovsky, P. (2015) What Should I Do Next? Adaptive Sequencing in the Context of Open Social Student Modeling. Proceedings of 10th European Conference on Technology Enhanced Learning (EC-TEL 2015), Toledo, Spain, September 15-18, 2015, pp. 155-168. ([https://d-scholarship.pitt.edu/secure/26266/1/camera_ready.pdf paper])([http://www.slideshare.net/RoyaHosseini1/ectel-2015 presentation]).&lt;br /&gt;
* Hosseini, R., Sirkiä, T., Guerra, J., Brusilovsky, P., Malmi, L. (2016) Animated Examples as a Practice Content in Java Programming Course. Proceedings of the 47th ACM technical symposium on Computer Science Education (SIGCSE), Memphis, Tennessee, March 2-5, 2016. (Accepted)&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Adaptive_Navigation_Support_and_Open_Social_Learner_Modeling_for_PAL&amp;diff=2925</id>
		<title>Adaptive Navigation Support and Open Social Learner Modeling for PAL</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Adaptive_Navigation_Support_and_Open_Social_Learner_Modeling_for_PAL&amp;diff=2925"/>
		<updated>2015-10-26T18:26:47Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;== Description ==&lt;br /&gt;
&lt;br /&gt;
The goal of this project is to leverage the power of [[open social learner modeling]] and [[adaptive navigation support]] in the context of the envisioned Personalized Assistant for Learning (PAL). The project is supported by the [http://adlnet.gov|Advanced Distributed Learning Initiative] contract W911QY13C0032.&lt;br /&gt;
&lt;br /&gt;
== Directions of work ==&lt;br /&gt;
&lt;br /&gt;
The project focuses on both exploration and implementation of adaptive navigation support and open social learner modeling and pursues three directions of work&lt;br /&gt;
&lt;br /&gt;
* Exploring open social learner modeling interface for diverse learning content&lt;br /&gt;
* Enhancing algorithms for personalized guidance using knowledge-based and social approaches &lt;br /&gt;
* Developing architectural solutions and authoring tools to support open social learner modeling&lt;br /&gt;
&lt;br /&gt;
===Open Social Learner Modeling Interfaces===&lt;br /&gt;
&lt;br /&gt;
Our latest implementation of Open Social Learner Modeling (OSLM) interface is [[MasteryGrids]] system. Mastery Grids is both, a innovative OSML interface and an adaptive E-learning platform with integrated functionalities enabling multi-facet social comparison, open user modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
&lt;br /&gt;
=== The Architecture ===&lt;br /&gt;
The architecture supporting Mastery Grids fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the [[Mastery Grids Interface]],&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services,&lt;br /&gt;
&lt;br /&gt;
*backend user modeling services, and&lt;br /&gt;
&lt;br /&gt;
*backend content providing applications.&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the next figure. &lt;br /&gt;
&lt;br /&gt;
[[Image:architecture_v1.png]]&lt;br /&gt;
&lt;br /&gt;
=== Authoring Tools ===&lt;br /&gt;
&lt;br /&gt;
The set of authoring tools developed for the project include tools for creating several kinds of smart learning content as well as tools to create adaptive courses that use this content&lt;br /&gt;
&lt;br /&gt;
==== Content Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to create and index annotated examples. [[ContentAuthoring|more]]&lt;br /&gt;
&lt;br /&gt;
==== Course Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to create courses for Mastery Grids. [[CourseAuthoring|more]]&lt;br /&gt;
&lt;br /&gt;
==== Group Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to define groups of students who can access the course. [[GroupAuthoring|more]]&lt;br /&gt;
&lt;br /&gt;
==== Authoring Portal ====&lt;br /&gt;
This is the central portal for providing access to the course authoring and group authoring tools. [[AuthoringPortal|more]]&lt;br /&gt;
&lt;br /&gt;
== Systems ==&lt;br /&gt;
&lt;br /&gt;
=== Mastery Grids ===&lt;br /&gt;
Mastery Grids is a visual-rich, interactive, adaptive E-learning system and framework with integrated functionalities enabling multi-facet social comparison, open social student modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
&lt;br /&gt;
[[Mastery Grids Interface|==&amp;gt;More]]&lt;br /&gt;
&lt;br /&gt;
=== Aggregate ===&lt;br /&gt;
[[Aggregate|More]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Links == &lt;br /&gt;
Software sources and documentation is in GitHub. The Mastery Grids Interface, backend Aggregate and documentation can be found [https://github.com/PAWSLabUniversityOfPittsburgh/MasteryGrids here]. User model services can be found in [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices here].&lt;br /&gt;
&lt;br /&gt;
A demo view of MasteryGrids can be accessed [http://adapt2.sis.pitt.edu/um-vis-adl/index.html?usr=adl01&amp;amp;grp=ADL&amp;amp;sid=test&amp;amp;cid=13&amp;amp;data-top-n-grp=5&amp;amp;def-val-rep-lvl-id=p&amp;amp;def-val-res-id=AVG&amp;amp;ui-tbar-rep-lvl-vis=0&amp;amp;ui-tbar-topic-size-vis=0 here]&lt;br /&gt;
&lt;br /&gt;
== Publications ==&lt;br /&gt;
* Gonzalez-Brenes, J. P., Huang, Y., and Brusilovsky, P. (2013) FAST: Feature-Aware Student Knowledge Tracing. In:  Proceedings of NIPS 2013 Workshop on Data Driven Education, Lake Tahoe, NV, December 10, 2013, ([http://lytics.stanford.edu/datadriveneducation/papers/gonzalezetal.pdf paper])&lt;br /&gt;
* Hosseini, R. and Brusilovsky, P. (2013) JavaParser: A Fine-Grain Concept Indexing Tool for Java Problems. In:  Proceedings of The First Workshop on AI-supported Education for Computer Science (AIEDCS) at the 16th Annual Conference on Artificial Intelligence in Education, AIED 2013, Memphis, TN, USA, July 13, 2013, pp. 60-63. ([https://d-scholarship.pitt.edu/secure/26270/1/AIED2013-workshop-camera_ready_version.pdf paper]) ([http://www.slideshare.net/RoyaHosseini1/java-parser-a-fine-grained-indexing-tool-and-its-application presentation])&lt;br /&gt;
* Hosseini, R., Brusilovsky, P., and Guerra, J. (2013) Knowledge Maximizer: Concept-based Adaptive Problem Sequencing for Exam Preparation. In:  Proceedings of the 16th International Conference on Artificial Intelligence in Education (AIED 2013), Memphis, USA, pp. 848-851.  ([https://d-scholarship.pitt.edu/secure/26271/4/AIED2013-camera-ready-Knowledge_maximizer_.pdf paper]) ([http://www.slideshare.net/RoyaHosseini1/aied-2013 poster])&lt;br /&gt;
* Brusilovsky, P., Baishya, D., Hosseini, R., Guerra, J., and Liang, M. (2013) KnowledgeZoom for Java: A Concept-Based Exam Study Tool  with a Zoomable Open Student Model. In:  Proceedings of 2013 IEEE 13th International Conference on Advanced Learning Technologies, Beijing, China, July 15-18, 2013, pp. 275-279. ([http://dx.doi.org/10.1109/ICALT.2013.86 paper]) ([http://www.slideshare.net/RoyaHosseini1/kowledge-zoom-michelle-48735584 presentation])&lt;br /&gt;
* Brusilovsky, P. (2014) Addictive Links: Engaging Students through Adaptive Navigation Support and Open Social Student Modeling (Keynote talk). In:  Proceedings of WWW 2014 Workshop on Web-based Education Technologies, Seoul, Korea, April 8, 2014. ([http://www.slideshare.net/pbrusilovsky/addictive-links-keynote-talk-at-www-2014-workshop presentation])&lt;br /&gt;
* Huang, Y., Xu, Y., and Brusilovsky, P. (2014) Doing More with Less: Student Modeling and Performance Prediction with Reduced Content Models. In: V. Dimitrova, et al. (eds.) Proceedings of 22nd Conference on User Modeling, Adaptation and Personalization (UMAP 2014), Aalborg, Denmark, July 7-11, 2014, Springer Verlag, pp. 338-349. ([http://www.slideshare.net/pbrusilovsky/umap-v1 presentation][http://link.springer.com/chapter/10.1007%2F978-3-319-08786-3_30 paper])&lt;br /&gt;
* Hosseini, R. and Brusilovsky, P. (2014) Example-Based Problem Solving Support Using concept Analysis of Programming Content. In: S. Trausan-Matu, K. Boyer, M. Crosby and K. Panourgia (eds.) Proceedings of 12th International Conference on Intelligent Tutoring Systems (ITS 2014), Honolulu, HI, USA, June 5-9, 2014, Springer International Publishing, pp. 683-685. ([https://d-scholarship.pitt.edu/secure/26269/1/CameraReady_ITS2014_paper.pdf paper])  ([http://www.slideshare.net/RoyaHosseini1/presentation-48735557 presentation])&lt;br /&gt;
* Hosseini, R., Vihavainen, A., and Brusilovsky, P. (2014) Exploring Problem Solving Paths in a Java Programming Course. In:  Proceedings of Psychology of Programming Interest Group Annual Conference, PPIG 2014, Brighton, UK, June 25-27, 2014, pp. 65-76. ([https://d-scholarship.pitt.edu/secure/26272/1/PPIG_2014_camera_ready.pdf paper]) ([http://www.slideshare.net/RoyaHosseini1/ppig2014-problem-solvingpaths presentation])&lt;br /&gt;
* Huang, Y., González-Brenes, J. P., and Brusilovsky, P. (2014) General Features in Knowledge Tracing to Model Multiple Subskills, Temporal Item Response Theory, and Expert Knowledge. In: J. Stamper, Z. Pardos, M. Mavrikis and B. M. McLaren (eds.) Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014), London, UK, July 4-7,  2014, pp. 84-91. (First two authors contributed equally. Nominated for Best Paper Award) ([http://www.slideshare.net/huangyun/fast-presentation-48711687 presentation][http://educationaldatamining.org/EDM2014/uploads/procs2014/long%20papers/84_EDM-2014-Full.pdf paper][http://ml-smores.github.io/fast/ code])&lt;br /&gt;
* Khajah, M. M., Huang, Y., González-Brenes, J. P., Mozer, M. C., and Brusilovsky, P. (2014) Integrating Knowledge Tracing and Item Response Theory: A Tale of Two Frameworks. In: I. Cantador, M. Chi, R. Farzan and R. Jäschke (eds.) Proceedings of Workshop on Personalization Approaches in Learning Environments (PALE 2014) at the 22th International Conference on User Modeling, Adaptation, and Personalization, UMAP 2014, Aalborg, Denmark, July 11, 2014, CEUR, pp. 7-12. (First three authors contributed equally) ([http://www.slideshare.net/huangyun/pale-public-slideshare presentation][http://ceur-ws.org/Vol-1181/pale2014_paper_01.pdf paper]).&lt;br /&gt;
* Yudelson, M., Hosseini, R., Vihavainen, A., and Brusilovsky, P. (2014) Investigating Automated Student Modeling in a Java MOOC. In: J. Stamper, Z. Pardos, M. Mavrikis and B. M. McLaren (eds.) Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014), London, UK, July 4-7,  2014, pp. 261-264. ([https://d-scholarship.pitt.edu/secure/26273/1/EDM2014YudelsonHVB_camready.pdf paper]) ([http://www.slideshare.net/RoyaHosseini1/edm2014-investigating-automated-student-modeling-in-a-java-mooc presentation])&lt;br /&gt;
* Sahebi, S., Huang, Y., and Brusilovsky, P. (2014) Parameterized Exercises in Java Programming: Using Knowledge Structure for Performance Prediction. In:  Proceedings of The second Workshop on AI-supported Education for Computer Science (AIEDCS) at 12th International Conference on Intelligent Tutoring Systems ITS 2014, Honolulu, Hawaii, June 6 2014. ([http://d-scholarship.pitt.edu/21915/ paper])([http://www.slideshare.net/chagh/parameterized-exercises-in-java-programming-using-knowledge-structure-for-performance-prediction presentation])&lt;br /&gt;
* Sahebi, S., Huang, Y., and Brusilovsky, P. (2014) Predicting Student Performance in Solving Parameterized Exercises. In: S. Trausan-Matu, K. Boyer, M. Crosby and K. Panourgia (eds.) Proceedings of 12th International Conference on Intelligent Tutoring Systems (ITS 2014), Honolulu, HI, USA, June 5-9, 2014, Springer International Publishing, pp. 496-503, ([http://d-scholarship.pitt.edu/21916/ paper]) ([http://www.slideshare.net/chagh/its14-pitttemplate presentation])&lt;br /&gt;
* Guerra, J., Sahebi, S., Lin, Y.-R., and Brusilovsky, P. (2014) The Problem Solving Genome: Analyzing Sequential Patterns of Student Work with Parameterized Exercises. In: J. Stamper, Z. Pardos, M. Mavrikis and B. M. McLaren (eds.) Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014), London, UK, July 4-7,  2014, pp. 153-160 ([http://www.slideshare.net/huangyun/guerra-the-problemsolvinggenome presentation][http://educationaldatamining.org/EDM2014/uploads/procs2014/long%20papers/153_EDM-2014-Full.pdf paper]) &lt;br /&gt;
* Loboda, T., Guerra, J., Hosseini, R., and Brusilovsky, P. (2014) Mastery Grids: An Open Source Social Educational Progress Visualization. In: S. de Freitas, C. Rensing, P. J. Muñoz Merino and T. Ley (eds.) Proceedings of 9th European Conference on Technology Enhanced Learning (EC-TEL 2014), Graz, Austria, September 16-19, 2014 (Best paper award). ([http://link.springer.com/chapter/10.1007%2F978-3-319-11200-8_18#page-1 paper]) ([http://www.slideshare.net/pbrusilovsky/ectel2014-mg presentation])&lt;br /&gt;
* Brusilovsky, P., Edwards, S., Kumar, A., Malmi, L., Benotti, L., Buck, D., Ihantola, P., Prince, R., Sirkiä, T., Sosnovsky, S., Urquiza, J., Vihavainen, A., and Wollowski, M. (2014) Increasing Adoption of Smart Learning Content for Computer Science Education. In:  Proceedings of Proceedings of the Working Group Reports of the 2014 on Innovation &amp;amp;amp; Technology in Computer Science Education Conference, Uppsala, Sweden, ACM, pp. 31-57. ([http://dx.doi.org/10.1145/2713609.2713611 paper])&lt;br /&gt;
* Gonzalez-Brenes, J. P., Huang, Y. (2014) The White Method: Towards Automatic Evaluation Metrics for Adaptive Tutoring Systems. In:  Proceedings of NIPS 2014 Workshop on Human Propelled Machine Learning, Montreal, Canada, December 13, 2014&lt;br /&gt;
* Huang, Y., González-Brenes, J. P., and Brusilovsky, P. (2015) The FAST toolkit for Unsupervised Learning of HMMs with Features. In: The Machine Learning Open Source Software workshop at the 32nd International Conference on Machine Learning (ICML-MLOSS 2015), Lille, France July 10, 2015. ([http://mloss.org/software/view/609/ code])&lt;br /&gt;
* Huang, Y., González-Brenes, J. P., Kumar, R., Brusilovsky, P. (2015) A Framework for Multifaceted Evaluation of Student Models. In: Proceedings of the 8th International Conference on Educational Data Mining (EDM 2015), Madrid, Spain. (Full paper) ([http://www.educationaldatamining.org/EDM2015/uploads/papers/paper_164.pdf paper]) ([http://www.slideshare.net/huangyun/2015edm-a-framework-for-multifaceted-evaluation-of-student-models-polygon presentation])&lt;br /&gt;
* Huang, Y., González-Brenes, J. P., Brusilovsky, P. (2015) Challenges of Using Observational Data to Determine the Importance of Example Usage. In: Proceedings of the 17th International Conference on Artificial Intelligence in Education (AIED 2015), Madrid, Spain.&lt;br /&gt;
* Gonzalez-Brenes, J. P., Huang, Y. (2015) Your model is predictive— but is it useful? Theoretical and Empirical Considerations of a New Paradigm for Adaptive Tutoring Evaluation. In: Proceedings of the 8th International Conference on Educational Data Mining (EDM 2015), Madrid, Spain. (Full paper)&lt;br /&gt;
* Gonzalez-Brenes, J. P., Huang, Y. (2015) Using Data from Real and Simulated Learners to Evaluate Adaptive Tutoring Systems. In: 2nd AIED Workshop on Simulated Learners at the 17th International Conference on Artificial Intelligence in Education (AIED), Madrid, Spain.&lt;br /&gt;
* Gonzalez-Brenes, J. P., Huang, Y. (2015) The Leopard Framework: Towards understanding educational technology interventions with a Pareto Efficiency Perspective. In: The ICML 2015 Workshop on Machine Learning for Education, Friday, July 10, 2015, Lille, France.&lt;br /&gt;
* Guerra, J., Huang, Y., Hosseini, R., &amp;amp; Brusilovsky, P. (2015, June). Graph Analysis of Student Model Networks. In Proceedings of the Second International Workshop on Graph-Based Educational Data Mining (GEDM 2015). CEUR-WS. ([https://d-scholarship.pitt.edu/secure/25933/1/graph_analysis.pdf paper]) &lt;br /&gt;
* Guerra, J., Huang, Y., Hosseini, R., &amp;amp; Brusilovsky, P. Exploring the Effects of Open Social Student Model Beyond Social Comparison. In ISLG 2015 Fourth Workshop on Intelligent Support for Learning in Groups (p. 19). ([https://d-scholarship.pitt.edu/secure/25931/1/islg_pap4.pdf paper])&lt;br /&gt;
* Hosseini, R., Hsiao, I.-H., Guerra, J., Brusilovsky, P. (2015) Off the Beaten Path: The Impact of Adaptive Content Sequencing on Student Navigation in an Open Social Student Modeling Interface. In: Proceedings of the 17th International Conference on Artificial Intelligence in Education (AIED 2015), Madrid, Spain. ([https://d-scholarship.pitt.edu/secure/25938/1/paper_183.pdf paper]) ([http://www.slideshare.net/RoyaHosseini1/aied-2015-poster-off-the-beaten-path-the-impact-of-adaptive-content-sequencing-on-student-navigation-in-an-open-social-student-modeling-interface poster])&lt;br /&gt;
* Hosseini, R., Hsiao, I.-H., Guerra, J., Brusilovsky, P. (2015) What Should I Do Next? Adaptive Sequencing in the Context of Open Social Student Modeling. Proceedings of 10th European Conference on Technology Enhanced Learning (EC-TEL 2015), Toledo, Spain, September 15-18, 2015. ([https://d-scholarship.pitt.edu/secure/26266/1/camera_ready.pdf paper])([http://www.slideshare.net/RoyaHosseini1/ectel-2015 presentation]).&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Adaptive_Navigation_Support_and_Open_Social_Learner_Modeling_for_PAL&amp;diff=2924</id>
		<title>Adaptive Navigation Support and Open Social Learner Modeling for PAL</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Adaptive_Navigation_Support_and_Open_Social_Learner_Modeling_for_PAL&amp;diff=2924"/>
		<updated>2015-10-26T18:25:28Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;== Description ==&lt;br /&gt;
&lt;br /&gt;
The goal of this project is to leverage the power of [[open social learner modeling]] and [[adaptive navigation support]] in the context of the envisioned Personalized Assistant for Learning (PAL). The project is supported by the [http://adlnet.gov|Advanced Distributed Learning Initiative] contract W911QY13C0032.&lt;br /&gt;
&lt;br /&gt;
== Directions of work ==&lt;br /&gt;
&lt;br /&gt;
The project focuses on both exploration and implementation of adaptive navigation support and open social learner modeling and pursues three directions of work&lt;br /&gt;
&lt;br /&gt;
* Exploring open social learner modeling interface for diverse learning content&lt;br /&gt;
* Enhancing algorithms for personalized guidance using knowledge-based and social approaches &lt;br /&gt;
* Developing architectural solutions and authoring tools to support open social learner modeling&lt;br /&gt;
&lt;br /&gt;
===Open Social Learner Modeling Interfaces===&lt;br /&gt;
&lt;br /&gt;
Our latest implementation of Open Social Learner Modeling (OSLM) interface is [[MasteryGrids]] system. Mastery Grids is both, a innovative OSML interface and an adaptive E-learning platform with integrated functionalities enabling multi-facet social comparison, open user modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
&lt;br /&gt;
=== The Architecture ===&lt;br /&gt;
The architecture supporting Mastery Grids fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the [[Mastery Grids Interface]],&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services,&lt;br /&gt;
&lt;br /&gt;
*backend user modeling services, and&lt;br /&gt;
&lt;br /&gt;
*backend content providing applications.&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the next figure. &lt;br /&gt;
&lt;br /&gt;
[[Image:architecture_v1.png]]&lt;br /&gt;
&lt;br /&gt;
=== Authoring Tools ===&lt;br /&gt;
&lt;br /&gt;
The set of authoring tools developed for the project include tools for creating several kinds of smart learning content as well as tools to create adaptive courses that use this content&lt;br /&gt;
&lt;br /&gt;
==== Content Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to create and index annotated examples. [[ContentAuthoring|more]]&lt;br /&gt;
&lt;br /&gt;
==== Course Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to create courses for Mastery Grids. [[CourseAuthoring|more]]&lt;br /&gt;
&lt;br /&gt;
==== Group Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to define groups of students who can access the course. [[GroupAuthoring|more]]&lt;br /&gt;
&lt;br /&gt;
==== Authoring Portal ====&lt;br /&gt;
This is the central portal for providing access to the course authoring and group authoring tools. [[AuthoringPortal|more]]&lt;br /&gt;
&lt;br /&gt;
== Systems ==&lt;br /&gt;
&lt;br /&gt;
=== Mastery Grids ===&lt;br /&gt;
Mastery Grids is a visual-rich, interactive, adaptive E-learning system and framework with integrated functionalities enabling multi-facet social comparison, open social student modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
&lt;br /&gt;
[[Mastery Grids Interface|==&amp;gt;More]]&lt;br /&gt;
&lt;br /&gt;
=== Aggregate ===&lt;br /&gt;
[[Aggregate|More]]&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Links == &lt;br /&gt;
Software sources and documentation is in GitHub. The Mastery Grids Interface, backend Aggregate and documentation can be found [https://github.com/PAWSLabUniversityOfPittsburgh/MasteryGrids here]. User model services can be found in [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices here].&lt;br /&gt;
&lt;br /&gt;
A demo view of MasteryGrids can be accessed [http://adapt2.sis.pitt.edu/um-vis-adl/index.html?usr=adl01&amp;amp;grp=ADL&amp;amp;sid=test&amp;amp;cid=13&amp;amp;data-top-n-grp=5&amp;amp;def-val-rep-lvl-id=p&amp;amp;def-val-res-id=AVG&amp;amp;ui-tbar-rep-lvl-vis=0&amp;amp;ui-tbar-topic-size-vis=0 here]&lt;br /&gt;
&lt;br /&gt;
== Publications ==&lt;br /&gt;
* Gonzalez-Brenes, J. P., Huang, Y., and Brusilovsky, P. (2013) FAST: Feature-Aware Student Knowledge Tracing. In:  Proceedings of NIPS 2013 Workshop on Data Driven Education, Lake Tahoe, NV, December 10, 2013, ([http://lytics.stanford.edu/datadriveneducation/papers/gonzalezetal.pdf paper])&lt;br /&gt;
* Hosseini, R. and Brusilovsky, P. (2013) JavaParser: A Fine-Grain Concept Indexing Tool for Java Problems. In:  Proceedings of The First Workshop on AI-supported Education for Computer Science (AIEDCS) at the 16th Annual Conference on Artificial Intelligence in Education, AIED 2013, Memphis, TN, USA, July 13, 2013, pp. 60-63. ([https://d-scholarship.pitt.edu/secure/26270/1/AIED2013-workshop-camera_ready_version.pdf paper]) ([http://www.slideshare.net/RoyaHosseini1/java-parser-a-fine-grained-indexing-tool-and-its-application presentation])&lt;br /&gt;
* Hosseini, R., Brusilovsky, P., and Guerra, J. (2013) Knowledge Maximizer: Concept-based Adaptive Problem Sequencing for Exam Preparation. In:  Proceedings of the 16th International Conference on Artificial Intelligence in Education (AIED 2013), Memphis, USA, pp. 848-851.  ([https://d-scholarship.pitt.edu/secure/26271/4/AIED2013-camera-ready-Knowledge_maximizer_.pdf paper]) ([http://www.slideshare.net/RoyaHosseini1/aied-2013 poster])&lt;br /&gt;
* Brusilovsky, P., Baishya, D., Hosseini, R., Guerra, J., and Liang, M. (2013) KnowledgeZoom for Java: A Concept-Based Exam Study Tool  with a Zoomable Open Student Model. In:  Proceedings of 2013 IEEE 13th International Conference on Advanced Learning Technologies, Beijing, China, July 15-18, 2013, pp. 275-279. ([http://dx.doi.org/10.1109/ICALT.2013.86 paper]) ([http://www.slideshare.net/RoyaHosseini1/kowledge-zoom-michelle-48735584 presentation])&lt;br /&gt;
* Brusilovsky, P. (2014) Addictive Links: Engaging Students through Adaptive Navigation Support and Open Social Student Modeling (Keynote talk). In:  Proceedings of WWW 2014 Workshop on Web-based Education Technologies, Seoul, Korea, April 8, 2014. ([http://www.slideshare.net/pbrusilovsky/addictive-links-keynote-talk-at-www-2014-workshop presentation])&lt;br /&gt;
* Huang, Y., Xu, Y., and Brusilovsky, P. (2014) Doing More with Less: Student Modeling and Performance Prediction with Reduced Content Models. In: V. Dimitrova, et al. (eds.) Proceedings of 22nd Conference on User Modeling, Adaptation and Personalization (UMAP 2014), Aalborg, Denmark, July 7-11, 2014, Springer Verlag, pp. 338-349. ([http://www.slideshare.net/pbrusilovsky/umap-v1 presentation][http://link.springer.com/chapter/10.1007%2F978-3-319-08786-3_30 paper])&lt;br /&gt;
* Hosseini, R. and Brusilovsky, P. (2014) Example-Based Problem Solving Support Using concept Analysis of Programming Content. In: S. Trausan-Matu, K. Boyer, M. Crosby and K. Panourgia (eds.) Proceedings of 12th International Conference on Intelligent Tutoring Systems (ITS 2014), Honolulu, HI, USA, June 5-9, 2014, Springer International Publishing, pp. 683-685. ([https://d-scholarship.pitt.edu/secure/26269/1/CameraReady_ITS2014_paper.pdf paper])  ([http://www.slideshare.net/RoyaHosseini1/presentation-48735557 presentation])&lt;br /&gt;
* Hosseini, R., Vihavainen, A., and Brusilovsky, P. (2014) Exploring Problem Solving Paths in a Java Programming Course. In:  Proceedings of Psychology of Programming Interest Group Annual Conference, PPIG 2014, Brighton, UK, June 25-27, 2014, pp. 65-76. ([https://d-scholarship.pitt.edu/secure/26272/1/PPIG_2014_camera_ready.pdf paper]) ([http://www.slideshare.net/RoyaHosseini1/ppig2014-problem-solvingpaths presentation])&lt;br /&gt;
* Huang, Y., González-Brenes, J. P., and Brusilovsky, P. (2014) General Features in Knowledge Tracing to Model Multiple Subskills, Temporal Item Response Theory, and Expert Knowledge. In: J. Stamper, Z. Pardos, M. Mavrikis and B. M. McLaren (eds.) Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014), London, UK, July 4-7,  2014, pp. 84-91. (First two authors contributed equally. Nominated for Best Paper Award) ([http://www.slideshare.net/huangyun/fast-presentation-48711687 presentation][http://educationaldatamining.org/EDM2014/uploads/procs2014/long%20papers/84_EDM-2014-Full.pdf paper][http://ml-smores.github.io/fast/ code])&lt;br /&gt;
* Khajah, M. M., Huang, Y., González-Brenes, J. P., Mozer, M. C., and Brusilovsky, P. (2014) Integrating Knowledge Tracing and Item Response Theory: A Tale of Two Frameworks. In: I. Cantador, M. Chi, R. Farzan and R. Jäschke (eds.) Proceedings of Workshop on Personalization Approaches in Learning Environments (PALE 2014) at the 22th International Conference on User Modeling, Adaptation, and Personalization, UMAP 2014, Aalborg, Denmark, July 11, 2014, CEUR, pp. 7-12. (First three authors contributed equally) ([http://www.slideshare.net/huangyun/pale-public-slideshare presentation][http://ceur-ws.org/Vol-1181/pale2014_paper_01.pdf paper]).&lt;br /&gt;
* Yudelson, M., Hosseini, R., Vihavainen, A., and Brusilovsky, P. (2014) Investigating Automated Student Modeling in a Java MOOC. In: J. Stamper, Z. Pardos, M. Mavrikis and B. M. McLaren (eds.) Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014), London, UK, July 4-7,  2014, pp. 261-264. ([https://d-scholarship.pitt.edu/secure/26273/1/EDM2014YudelsonHVB_camready.pdf paper]) ([http://www.slideshare.net/RoyaHosseini1/edm2014-investigating-automated-student-modeling-in-a-java-mooc presentation])&lt;br /&gt;
* Sahebi, S., Huang, Y., and Brusilovsky, P. (2014) Parameterized Exercises in Java Programming: Using Knowledge Structure for Performance Prediction. In:  Proceedings of The second Workshop on AI-supported Education for Computer Science (AIEDCS) at 12th International Conference on Intelligent Tutoring Systems ITS 2014, Honolulu, Hawaii, June 6 2014. ([http://d-scholarship.pitt.edu/21915/ paper])([http://www.slideshare.net/chagh/parameterized-exercises-in-java-programming-using-knowledge-structure-for-performance-prediction presentation])&lt;br /&gt;
* Sahebi, S., Huang, Y., and Brusilovsky, P. (2014) Predicting Student Performance in Solving Parameterized Exercises. In: S. Trausan-Matu, K. Boyer, M. Crosby and K. Panourgia (eds.) Proceedings of 12th International Conference on Intelligent Tutoring Systems (ITS 2014), Honolulu, HI, USA, June 5-9, 2014, Springer International Publishing, pp. 496-503, ([http://d-scholarship.pitt.edu/21916/ paper]) ([http://www.slideshare.net/chagh/its14-pitttemplate presentation])&lt;br /&gt;
* Guerra, J., Sahebi, S., Lin, Y.-R., and Brusilovsky, P. (2014) The Problem Solving Genome: Analyzing Sequential Patterns of Student Work with Parameterized Exercises. In: J. Stamper, Z. Pardos, M. Mavrikis and B. M. McLaren (eds.) Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014), London, UK, July 4-7,  2014, pp. 153-160 ([http://www.slideshare.net/huangyun/guerra-the-problemsolvinggenome presentation][http://educationaldatamining.org/EDM2014/uploads/procs2014/long%20papers/153_EDM-2014-Full.pdf paper]) &lt;br /&gt;
* Loboda, T., Guerra, J., Hosseini, R., and Brusilovsky, P. (2014) Mastery Grids: An Open Source Social Educational Progress Visualization. In: S. de Freitas, C. Rensing, P. J. Muñoz Merino and T. Ley (eds.) Proceedings of 9th European Conference on Technology Enhanced Learning (EC-TEL 2014), Graz, Austria, September 16-19, 2014 (Best paper award). ([http://link.springer.com/chapter/10.1007%2F978-3-319-11200-8_18#page-1 paper]) ([http://www.slideshare.net/pbrusilovsky/ectel2014-mg presentation])&lt;br /&gt;
* Brusilovsky, P., Edwards, S., Kumar, A., Malmi, L., Benotti, L., Buck, D., Ihantola, P., Prince, R., Sirkiä, T., Sosnovsky, S., Urquiza, J., Vihavainen, A., and Wollowski, M. (2014) Increasing Adoption of Smart Learning Content for Computer Science Education. In:  Proceedings of Proceedings of the Working Group Reports of the 2014 on Innovation &amp;amp;amp; Technology in Computer Science Education Conference, Uppsala, Sweden, ACM, pp. 31-57. ([http://dx.doi.org/10.1145/2713609.2713611 paper])&lt;br /&gt;
* Gonzalez-Brenes, J. P., Huang, Y. (2014) The White Method: Towards Automatic Evaluation Metrics for Adaptive Tutoring Systems. In:  Proceedings of NIPS 2014 Workshop on Human Propelled Machine Learning, Montreal, Canada, December 13, 2014&lt;br /&gt;
* Huang, Y., González-Brenes, J. P., and Brusilovsky, P. (2015) The FAST toolkit for Unsupervised Learning of HMMs with Features. In: The Machine Learning Open Source Software workshop at the 32nd International Conference on Machine Learning (ICML-MLOSS 2015), Lille, France July 10, 2015. ([http://mloss.org/software/view/609/ code])&lt;br /&gt;
* Huang, Y., González-Brenes, J. P., Kumar, R., Brusilovsky, P. (2015) A Framework for Multifaceted Evaluation of Student Models. In: Proceedings of the 8th International Conference on Educational Data Mining (EDM 2015), Madrid, Spain. (Full paper) ([http://www.educationaldatamining.org/EDM2015/uploads/papers/paper_164.pdf paper]) ([http://www.slideshare.net/huangyun/2015edm-a-framework-for-multifaceted-evaluation-of-student-models-polygon presentation])&lt;br /&gt;
* Huang, Y., González-Brenes, J. P., Brusilovsky, P. (2015) Challenges of Using Observational Data to Determine the Importance of Example Usage. In: Proceedings of the 17th International Conference on Artificial Intelligence in Education (AIED 2015), Madrid, Spain.&lt;br /&gt;
* Gonzalez-Brenes, J. P., Huang, Y. (2015) Your model is predictive— but is it useful? Theoretical and Empirical Considerations of a New Paradigm for Adaptive Tutoring Evaluation. In: Proceedings of the 8th International Conference on Educational Data Mining (EDM 2015), Madrid, Spain. (Full paper)&lt;br /&gt;
* Gonzalez-Brenes, J. P., Huang, Y. (2015) Using Data from Real and Simulated Learners to Evaluate Adaptive Tutoring Systems. In: 2nd AIED Workshop on Simulated Learners at the 17th International Conference on Artificial Intelligence in Education (AIED), Madrid, Spain.&lt;br /&gt;
* Gonzalez-Brenes, J. P., Huang, Y. (2015) The Leopard Framework: Towards understanding educational technology interventions with a Pareto Efficiency Perspective. In: The ICML 2015 Workshop on Machine Learning for Education, Friday, July 10, 2015, Lille, France.&lt;br /&gt;
* Guerra, J., Huang, Y., Hosseini, R., &amp;amp; Brusilovsky, P. (2015, June). Graph Analysis of Student Model Networks. In Proceedings of the Second International Workshop on Graph-Based Educational Data Mining (GEDM 2015). CEUR-WS. (https://d-scholarship.pitt.edu/secure/25933/1/graph_analysis.pdf) &lt;br /&gt;
* Guerra, J., Huang, Y., Hosseini, R., &amp;amp; Brusilovsky, P. Exploring the Effects of Open Social Student Model Beyond Social Comparison. In ISLG 2015 Fourth Workshop on Intelligent Support for Learning in Groups (p. 19). ([https://d-scholarship.pitt.edu/secure/25931/1/islg_pap4.pdf])&lt;br /&gt;
* Hosseini, R., Hsiao, I.-H., Guerra, J., Brusilovsky, P. (2015) Off the Beaten Path: The Impact of Adaptive Content Sequencing on Student Navigation in an Open Social Student Modeling Interface. In: Proceedings of the 17th International Conference on Artificial Intelligence in Education (AIED 2015), Madrid, Spain. ([https://d-scholarship.pitt.edu/secure/25938/1/paper_183.pdf paper]) ([http://www.slideshare.net/RoyaHosseini1/aied-2015-poster-off-the-beaten-path-the-impact-of-adaptive-content-sequencing-on-student-navigation-in-an-open-social-student-modeling-interface poster])&lt;br /&gt;
* Hosseini, R., Hsiao, I.-H., Guerra, J., Brusilovsky, P. (2015) What Should I Do Next? Adaptive Sequencing in the Context of Open Social Student Modeling. Proceedings of 10th European Conference on Technology Enhanced Learning (EC-TEL 2015), Toledo, Spain, September 15-18, 2015. ([https://d-scholarship.pitt.edu/secure/26266/1/camera_ready.pdf paper])([http://www.slideshare.net/RoyaHosseini1/ectel-2015 presentation]).&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Adaptive_Navigation_Support_and_Open_Social_Learner_Modeling_for_PAL&amp;diff=2551</id>
		<title>Adaptive Navigation Support and Open Social Learner Modeling for PAL</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Adaptive_Navigation_Support_and_Open_Social_Learner_Modeling_for_PAL&amp;diff=2551"/>
		<updated>2015-03-12T03:28:08Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* Resources */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;== Description ==&lt;br /&gt;
PAWS participation in ADL is focused in the development of MasteryGrids system. Mastery Grids is a visual-rich, interactive, adaptive E-learning platform with integrated functionalities enabling multi-facet social comparison, open user modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
The architecture supporting Mastery Grids fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the [[Mastery Grids Interface]],&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services,&lt;br /&gt;
&lt;br /&gt;
*backend user modeling services, and&lt;br /&gt;
&lt;br /&gt;
*backend content providing applications.&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the next figure. &lt;br /&gt;
&lt;br /&gt;
[[Image:architecture_v1.png]]&lt;br /&gt;
&lt;br /&gt;
== Systems ==&lt;br /&gt;
&lt;br /&gt;
=== Mastery Grids ===&lt;br /&gt;
MasteryGrids is an open social student modeling interface written in Javascript. The interface shows the student's progress levels in a series of topics and content items as long as provides navigation support and access to educational content.&lt;br /&gt;
&lt;br /&gt;
[[Mastery Grids Interface|More]]&lt;br /&gt;
&lt;br /&gt;
=== Aggregate ===&lt;br /&gt;
[[Aggregate|More]]&lt;br /&gt;
&lt;br /&gt;
== Learning Content ==&lt;br /&gt;
&lt;br /&gt;
== Authoring Tools == &lt;br /&gt;
==== Content Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to create and index annotated examples. [[ContentAuthoring|more]]&lt;br /&gt;
&lt;br /&gt;
==== Course Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to create courses for Mastery Grids. [[CourseAuthoring|more]]&lt;br /&gt;
&lt;br /&gt;
==== Group Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to define groups of students who can access the course. [[GroupAuthoring|more]]&lt;br /&gt;
== Resources == &lt;br /&gt;
Software sources and documentation is in GitHub. The Mastery Grids Interface, backend Aggregate and documentation can be found [https://github.com/PAWSLabUniversityOfPittsburgh/MasteryGrids here]. User model services can be found in [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices here].&lt;br /&gt;
&lt;br /&gt;
A demo view of MasteryGrids can be accessed [http://adapt2.sis.pitt.edu/um-vis-adl/index.html?usr=adl01&amp;amp;grp=ADL&amp;amp;sid=test&amp;amp;cid=13&amp;amp;data-top-n-grp=5&amp;amp;def-val-rep-lvl-id=p&amp;amp;def-val-res-id=AVG&amp;amp;ui-tbar-rep-lvl-vis=0&amp;amp;ui-tbar-topic-size-vis=0 here]&lt;br /&gt;
&lt;br /&gt;
== Publications ==&lt;br /&gt;
*Loboda, T., Guerra, J., Hosseini, R., and Brusilovsky, P. (2014) Mastery Grids: An Open Source Social Educational Progress Visualization. In: S. de Freitas, C. Rensing, P. J. Muñoz Merino and T. Ley (eds.) Proceedings of 9th European Conference on Technology Enhanced Learning (EC-TEL 2014), Graz, Austria, September 16-19, 2014 (Best paper award).&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Adaptive_Navigation_Support_and_Open_Social_Learner_Modeling_for_PAL&amp;diff=2550</id>
		<title>Adaptive Navigation Support and Open Social Learner Modeling for PAL</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Adaptive_Navigation_Support_and_Open_Social_Learner_Modeling_for_PAL&amp;diff=2550"/>
		<updated>2015-03-12T03:27:46Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* Mastery Grids */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;== Description ==&lt;br /&gt;
PAWS participation in ADL is focused in the development of MasteryGrids system. Mastery Grids is a visual-rich, interactive, adaptive E-learning platform with integrated functionalities enabling multi-facet social comparison, open user modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
The architecture supporting Mastery Grids fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the [[Mastery Grids Interface]],&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services,&lt;br /&gt;
&lt;br /&gt;
*backend user modeling services, and&lt;br /&gt;
&lt;br /&gt;
*backend content providing applications.&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the next figure. &lt;br /&gt;
&lt;br /&gt;
[[Image:architecture_v1.png]]&lt;br /&gt;
&lt;br /&gt;
== Systems ==&lt;br /&gt;
&lt;br /&gt;
=== Mastery Grids ===&lt;br /&gt;
MasteryGrids is an open social student modeling interface written in Javascript. The interface shows the student's progress levels in a series of topics and content items as long as provides navigation support and access to educational content.&lt;br /&gt;
&lt;br /&gt;
[[Mastery Grids Interface|More]]&lt;br /&gt;
&lt;br /&gt;
=== Aggregate ===&lt;br /&gt;
[[Aggregate|More]]&lt;br /&gt;
&lt;br /&gt;
== Learning Content ==&lt;br /&gt;
&lt;br /&gt;
== Authoring Tools == &lt;br /&gt;
==== Content Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to create and index annotated examples. [[ContentAuthoring|more]]&lt;br /&gt;
&lt;br /&gt;
==== Course Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to create courses for Mastery Grids. [[CourseAuthoring|more]]&lt;br /&gt;
&lt;br /&gt;
==== Group Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to define groups of students who can access the course. [[GroupAuthoring|more]]&lt;br /&gt;
== Resources == &lt;br /&gt;
Software sources and documentation is in GitHub. The Mastery Grids Interface, backend Aggregate and documentation can be found [https://github.com/PAWSLabUniversityOfPittsburgh/MasteryGrids here]. User model services can be found in [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices here].&lt;br /&gt;
&lt;br /&gt;
== Publications ==&lt;br /&gt;
*Loboda, T., Guerra, J., Hosseini, R., and Brusilovsky, P. (2014) Mastery Grids: An Open Source Social Educational Progress Visualization. In: S. de Freitas, C. Rensing, P. J. Muñoz Merino and T. Ley (eds.) Proceedings of 9th European Conference on Technology Enhanced Learning (EC-TEL 2014), Graz, Austria, September 16-19, 2014 (Best paper award).&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Adaptive_Navigation_Support_and_Open_Social_Learner_Modeling_for_PAL&amp;diff=2549</id>
		<title>Adaptive Navigation Support and Open Social Learner Modeling for PAL</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Adaptive_Navigation_Support_and_Open_Social_Learner_Modeling_for_PAL&amp;diff=2549"/>
		<updated>2015-03-12T03:27:05Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* Mastery Grids */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;== Description ==&lt;br /&gt;
PAWS participation in ADL is focused in the development of MasteryGrids system. Mastery Grids is a visual-rich, interactive, adaptive E-learning platform with integrated functionalities enabling multi-facet social comparison, open user modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
The architecture supporting Mastery Grids fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the [[Mastery Grids Interface]],&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services,&lt;br /&gt;
&lt;br /&gt;
*backend user modeling services, and&lt;br /&gt;
&lt;br /&gt;
*backend content providing applications.&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the next figure. &lt;br /&gt;
&lt;br /&gt;
[[Image:architecture_v1.png]]&lt;br /&gt;
&lt;br /&gt;
== Systems ==&lt;br /&gt;
&lt;br /&gt;
=== Mastery Grids ===&lt;br /&gt;
MasteryGrids is an open social student modeling interface written in Javascript. The interface shows the student's progress levels in a series of topics and content items as long as provides navigation support and access to educational content.&lt;br /&gt;
[[Mastery Grids Interface|More]]&lt;br /&gt;
&lt;br /&gt;
=== Aggregate ===&lt;br /&gt;
[[Aggregate|More]]&lt;br /&gt;
&lt;br /&gt;
== Learning Content ==&lt;br /&gt;
&lt;br /&gt;
== Authoring Tools == &lt;br /&gt;
==== Content Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to create and index annotated examples. [[ContentAuthoring|more]]&lt;br /&gt;
&lt;br /&gt;
==== Course Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to create courses for Mastery Grids. [[CourseAuthoring|more]]&lt;br /&gt;
&lt;br /&gt;
==== Group Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to define groups of students who can access the course. [[GroupAuthoring|more]]&lt;br /&gt;
== Resources == &lt;br /&gt;
Software sources and documentation is in GitHub. The Mastery Grids Interface, backend Aggregate and documentation can be found [https://github.com/PAWSLabUniversityOfPittsburgh/MasteryGrids here]. User model services can be found in [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices here].&lt;br /&gt;
&lt;br /&gt;
== Publications ==&lt;br /&gt;
*Loboda, T., Guerra, J., Hosseini, R., and Brusilovsky, P. (2014) Mastery Grids: An Open Source Social Educational Progress Visualization. In: S. de Freitas, C. Rensing, P. J. Muñoz Merino and T. Ley (eds.) Proceedings of 9th European Conference on Technology Enhanced Learning (EC-TEL 2014), Graz, Austria, September 16-19, 2014 (Best paper award).&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Adaptive_Navigation_Support_and_Open_Social_Learner_Modeling_for_PAL&amp;diff=2548</id>
		<title>Adaptive Navigation Support and Open Social Learner Modeling for PAL</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Adaptive_Navigation_Support_and_Open_Social_Learner_Modeling_for_PAL&amp;diff=2548"/>
		<updated>2015-03-12T03:26:17Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* Mastery Grids */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;== Description ==&lt;br /&gt;
PAWS participation in ADL is focused in the development of MasteryGrids system. Mastery Grids is a visual-rich, interactive, adaptive E-learning platform with integrated functionalities enabling multi-facet social comparison, open user modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
The architecture supporting Mastery Grids fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the [[Mastery Grids Interface]],&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services,&lt;br /&gt;
&lt;br /&gt;
*backend user modeling services, and&lt;br /&gt;
&lt;br /&gt;
*backend content providing applications.&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the next figure. &lt;br /&gt;
&lt;br /&gt;
[[Image:architecture_v1.png]]&lt;br /&gt;
&lt;br /&gt;
== Systems ==&lt;br /&gt;
&lt;br /&gt;
=== Mastery Grids ===&lt;br /&gt;
[[Mastery Grids Interface|More]]&lt;br /&gt;
&lt;br /&gt;
=== Aggregate ===&lt;br /&gt;
[[Aggregate|More]]&lt;br /&gt;
&lt;br /&gt;
== Learning Content ==&lt;br /&gt;
&lt;br /&gt;
== Authoring Tools == &lt;br /&gt;
==== Content Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to create and index annotated examples. [[ContentAuthoring|more]]&lt;br /&gt;
&lt;br /&gt;
==== Course Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to create courses for Mastery Grids. [[CourseAuthoring|more]]&lt;br /&gt;
&lt;br /&gt;
==== Group Authoring ====&lt;br /&gt;
This tool provides the interface for teachers to define groups of students who can access the course. [[GroupAuthoring|more]]&lt;br /&gt;
== Resources == &lt;br /&gt;
Software sources and documentation is in GitHub. The Mastery Grids Interface, backend Aggregate and documentation can be found [https://github.com/PAWSLabUniversityOfPittsburgh/MasteryGrids here]. User model services can be found in [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices here].&lt;br /&gt;
&lt;br /&gt;
== Publications ==&lt;br /&gt;
*Loboda, T., Guerra, J., Hosseini, R., and Brusilovsky, P. (2014) Mastery Grids: An Open Source Social Educational Progress Visualization. In: S. de Freitas, C. Rensing, P. J. Muñoz Merino and T. Ley (eds.) Proceedings of 9th European Conference on Technology Enhanced Learning (EC-TEL 2014), Graz, Austria, September 16-19, 2014 (Best paper award).&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Projects&amp;diff=2539</id>
		<title>Projects</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Projects&amp;diff=2539"/>
		<updated>2015-03-12T01:34:07Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* ADL Project */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;== ADL Project==&lt;br /&gt;
PAWS participation in ADL is focused in the development of MasteryGrids system. Mastery Grids is a visual-rich, interactive, adaptive E-learning platform with integrated functionalities enabling multi-facet social comparison, open user modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
&lt;br /&gt;
[[ADL|more]]&lt;br /&gt;
&lt;br /&gt;
== Conference Navigator ==&lt;br /&gt;
It offers an enhanced version of a conference schedule. It combines social tagging and social navigation features, but also use accumulated data from existing long-term communities (e.g. Facebook, CiteULike) to help users to find the relevant sessions to attend and to determine the appropriate people to make contact with during the conference. [[CN3|more]]&lt;br /&gt;
&lt;br /&gt;
== PACER ==&lt;br /&gt;
Personalized Access to Open Corpus Educational Resources through Adaptive Navigation Support and Adaptive Visualization. [[PACER|more]]&lt;br /&gt;
&lt;br /&gt;
== IMPROVE ==&lt;br /&gt;
IMproved PROgram Visualization for Education. [[IMPROVE|more]]&lt;br /&gt;
&lt;br /&gt;
== ADAPT&amp;lt;sup&amp;gt;2&amp;lt;/sup&amp;gt; ==&lt;br /&gt;
ADAPT&amp;lt;sup&amp;gt;2&amp;lt;/sup&amp;gt; (read adapt-square) - Advanced Distributed Architecture for Personalized Teaching and Training - is a framework targeted at providing personalization and adaptation services for developers of content that lacks personalization.&lt;br /&gt;
[[ADAPT2|more]]&lt;br /&gt;
&lt;br /&gt;
== Ensemble ==&lt;br /&gt;
[[Ensemble]] is a cross-university collaborative effort that aims to bring together the global community of computing educators around a growing set of content collections with high-quality educational resources.&lt;br /&gt;
[[Ensemble|more]]&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Mastery_Grids_Interface&amp;diff=2506</id>
		<title>Mastery Grids Interface</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Mastery_Grids_Interface&amp;diff=2506"/>
		<updated>2015-03-11T15:40:01Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* MasteryGrids Interface */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;MasteryGrids is an open social student modeling interface written in Javascript. The interface shows the student's progress levels in a series of topics and content items as long as provides navigation support and access to educational content (see figure).&lt;br /&gt;
&lt;br /&gt;
[[Image:mg_1.png]]&lt;br /&gt;
&lt;br /&gt;
A demo view of MasteryGrids can be found [http://adapt2.sis.pitt.edu/um-vis-adl/index.html?usr=adl01&amp;amp;grp=ADL&amp;amp;sid=test&amp;amp;cid=13&amp;amp;data-top-n-grp=5&amp;amp;def-val-rep-lvl-id=p&amp;amp;def-val-res-id=AVG&amp;amp;ui-tbar-rep-lvl-vis=0&amp;amp;ui-tbar-topic-size-vis=0 here]&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Mastery_Grids_Interface&amp;diff=2505</id>
		<title>Mastery Grids Interface</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Mastery_Grids_Interface&amp;diff=2505"/>
		<updated>2015-03-11T15:39:30Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* MasteryGrids Interface */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;== MasteryGrids Interface ==&lt;br /&gt;
MasteryGrids is an open social student modeling interface written in Javascript. The interface shows the student's progress levels in a series of topics and content items as long as provides navigation support and access to educational content (see figure).&lt;br /&gt;
&lt;br /&gt;
[[Image:mg_1.png]]&lt;br /&gt;
&lt;br /&gt;
A demo view of MasteryGrids can be found [http://adapt2.sis.pitt.edu/um-vis-adl/index.html?usr=adl01&amp;amp;grp=ADL&amp;amp;sid=test&amp;amp;cid=13&amp;amp;data-top-n-grp=5&amp;amp;def-val-rep-lvl-id=p&amp;amp;def-val-res-id=AVG&amp;amp;ui-tbar-rep-lvl-vis=0&amp;amp;ui-tbar-topic-size-vis=0 here]&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=File:Mg_1.png&amp;diff=2504</id>
		<title>File:Mg 1.png</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=File:Mg_1.png&amp;diff=2504"/>
		<updated>2015-03-11T15:38:39Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Mastery_Grids_Interface&amp;diff=2503</id>
		<title>Mastery Grids Interface</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Mastery_Grids_Interface&amp;diff=2503"/>
		<updated>2015-03-11T15:37:32Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: New page: == MasteryGrids Interface == MasteryGrids is an open social student modeling interface written in Javascript. The interface shows the student's progress levels in a series of topics and co...&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;== MasteryGrids Interface ==&lt;br /&gt;
MasteryGrids is an open social student modeling interface written in Javascript. The interface shows the student's progress levels in a series of topics and content items as long as provides navigation support and access to educational content (see figure).&lt;br /&gt;
&lt;br /&gt;
[[Image:masterygrids_1.png]]&lt;br /&gt;
&lt;br /&gt;
A demo view of MasteryGrids can be found [here http://adapt2.sis.pitt.edu/um-vis-adl/index.html?usr=adl01&amp;amp;grp=ADL&amp;amp;sid=test&amp;amp;cid=13&amp;amp;data-top-n-grp=5&amp;amp;def-val-rep-lvl-id=p&amp;amp;def-val-res-id=AVG&amp;amp;ui-tbar-rep-lvl-vis=0&amp;amp;ui-tbar-topic-size-vis=0]&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2502</id>
		<title>ADL</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2502"/>
		<updated>2015-03-11T15:24:41Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* Description */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;This page is for the ADL project.&lt;br /&gt;
&lt;br /&gt;
== Description ==&lt;br /&gt;
&lt;br /&gt;
PAWS participation in ADL is focused in the development of MasteryGrids system. Mastery Grids is a visual-rich, interactive, adaptive E-learning platform with integrated functionalities enabling multi-facet social comparison, open user modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
The architecture supporting Mastery Grids fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the [[Mastery Grids Interface]],&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services,&lt;br /&gt;
&lt;br /&gt;
*backend user modeling services, and&lt;br /&gt;
&lt;br /&gt;
*backend content providing applications.&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the next figure. &lt;br /&gt;
&lt;br /&gt;
[[Image:architecture_v1.png]]&lt;br /&gt;
&lt;br /&gt;
== Resources == &lt;br /&gt;
Software sources and documentation is in GitHub. The Mastery Grids Interface, backend Aggregate and documentation can be found [https://github.com/PAWSLabUniversityOfPittsburgh/MasteryGrids here]. User model services can be found in [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices here].&lt;br /&gt;
&lt;br /&gt;
== Publications ==&lt;br /&gt;
*Loboda, T., Guerra, J., Hosseini, R., and Brusilovsky, P. (2014) Mastery Grids: An Open Source Social Educational Progress Visualization. In: S. de Freitas, C. Rensing, P. J. Muñoz Merino and T. Ley (eds.) Proceedings of 9th European Conference on Technology Enhanced Learning (EC-TEL 2014), Graz, Austria, September 16-19, 2014 (Best paper award).&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2501</id>
		<title>ADL</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2501"/>
		<updated>2015-03-11T15:24:16Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* Description */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;This page is for the ADL project.&lt;br /&gt;
&lt;br /&gt;
== Description ==&lt;br /&gt;
&lt;br /&gt;
PAWS participation in ADL is focused in the development of MasteryGrids system. Mastery Grids is a visual-rich, interactive, adaptive E-learning platform with integrated functionalities enabling multi-facet social comparison, open user modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
The architecture supporting Mastery Grids fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the [Mastery Grids Interface],&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services,&lt;br /&gt;
&lt;br /&gt;
*backend user modeling services, and&lt;br /&gt;
&lt;br /&gt;
*backend content providing applications.&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the next figure. &lt;br /&gt;
&lt;br /&gt;
[[Image:architecture_v1.png]]&lt;br /&gt;
&lt;br /&gt;
== Resources == &lt;br /&gt;
Software sources and documentation is in GitHub. The Mastery Grids Interface, backend Aggregate and documentation can be found [https://github.com/PAWSLabUniversityOfPittsburgh/MasteryGrids here]. User model services can be found in [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices here].&lt;br /&gt;
&lt;br /&gt;
== Publications ==&lt;br /&gt;
*Loboda, T., Guerra, J., Hosseini, R., and Brusilovsky, P. (2014) Mastery Grids: An Open Source Social Educational Progress Visualization. In: S. de Freitas, C. Rensing, P. J. Muñoz Merino and T. Ley (eds.) Proceedings of 9th European Conference on Technology Enhanced Learning (EC-TEL 2014), Graz, Austria, September 16-19, 2014 (Best paper award).&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2500</id>
		<title>ADL</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2500"/>
		<updated>2015-03-11T15:23:40Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* Resource */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;This page is for the ADL project.&lt;br /&gt;
&lt;br /&gt;
== Description ==&lt;br /&gt;
&lt;br /&gt;
PAWS participation in ADL is focused in the development of MasteryGrids system. Mastery Grids is a visual-rich, interactive, adaptive E-learning platform with integrated functionalities enabling multi-facet social comparison, open user modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
The architecture supporting Mastery Grids fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the '''''Mastery Grids Interface''''',&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services,&lt;br /&gt;
&lt;br /&gt;
*backend user modeling services, and&lt;br /&gt;
&lt;br /&gt;
*backend content providing applications.&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the next figure. &lt;br /&gt;
&lt;br /&gt;
[[Image:architecture_v1.png]]&lt;br /&gt;
&lt;br /&gt;
== Resources == &lt;br /&gt;
Software sources and documentation is in GitHub. The Mastery Grids Interface, backend Aggregate and documentation can be found [https://github.com/PAWSLabUniversityOfPittsburgh/MasteryGrids here]. User model services can be found in [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices here].&lt;br /&gt;
&lt;br /&gt;
== Publications ==&lt;br /&gt;
*Loboda, T., Guerra, J., Hosseini, R., and Brusilovsky, P. (2014) Mastery Grids: An Open Source Social Educational Progress Visualization. In: S. de Freitas, C. Rensing, P. J. Muñoz Merino and T. Ley (eds.) Proceedings of 9th European Conference on Technology Enhanced Learning (EC-TEL 2014), Graz, Austria, September 16-19, 2014 (Best paper award).&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2499</id>
		<title>ADL</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2499"/>
		<updated>2015-03-11T15:23:27Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* Publications */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;This page is for the ADL project.&lt;br /&gt;
&lt;br /&gt;
== Description ==&lt;br /&gt;
&lt;br /&gt;
PAWS participation in ADL is focused in the development of MasteryGrids system. Mastery Grids is a visual-rich, interactive, adaptive E-learning platform with integrated functionalities enabling multi-facet social comparison, open user modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
The architecture supporting Mastery Grids fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the '''''Mastery Grids Interface''''',&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services,&lt;br /&gt;
&lt;br /&gt;
*backend user modeling services, and&lt;br /&gt;
&lt;br /&gt;
*backend content providing applications.&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the next figure. &lt;br /&gt;
&lt;br /&gt;
[[Image:architecture_v1.png]]&lt;br /&gt;
&lt;br /&gt;
== Resource == &lt;br /&gt;
Software sources and documentation is in GitHub. The Mastery Grids Interface, backend Aggregate and documentation can be found [https://github.com/PAWSLabUniversityOfPittsburgh/MasteryGrids here]. User model services can be found in [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices here].&lt;br /&gt;
&lt;br /&gt;
== Publications ==&lt;br /&gt;
*Loboda, T., Guerra, J., Hosseini, R., and Brusilovsky, P. (2014) Mastery Grids: An Open Source Social Educational Progress Visualization. In: S. de Freitas, C. Rensing, P. J. Muñoz Merino and T. Ley (eds.) Proceedings of 9th European Conference on Technology Enhanced Learning (EC-TEL 2014), Graz, Austria, September 16-19, 2014 (Best paper award).&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2498</id>
		<title>ADL</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2498"/>
		<updated>2015-03-11T15:23:17Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* Publications */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;This page is for the ADL project.&lt;br /&gt;
&lt;br /&gt;
== Description ==&lt;br /&gt;
&lt;br /&gt;
PAWS participation in ADL is focused in the development of MasteryGrids system. Mastery Grids is a visual-rich, interactive, adaptive E-learning platform with integrated functionalities enabling multi-facet social comparison, open user modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
The architecture supporting Mastery Grids fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the '''''Mastery Grids Interface''''',&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services,&lt;br /&gt;
&lt;br /&gt;
*backend user modeling services, and&lt;br /&gt;
&lt;br /&gt;
*backend content providing applications.&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the next figure. &lt;br /&gt;
&lt;br /&gt;
[[Image:architecture_v1.png]]&lt;br /&gt;
&lt;br /&gt;
== Resource == &lt;br /&gt;
Software sources and documentation is in GitHub. The Mastery Grids Interface, backend Aggregate and documentation can be found [https://github.com/PAWSLabUniversityOfPittsburgh/MasteryGrids here]. User model services can be found in [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices here].&lt;br /&gt;
&lt;br /&gt;
== Publications ==&lt;br /&gt;
Loboda, T., Guerra, J., Hosseini, R., and Brusilovsky, P. (2014) Mastery Grids: An Open Source Social Educational Progress Visualization. In: S. de Freitas, C. Rensing, P. J. Muñoz Merino and T. Ley (eds.) Proceedings of 9th European Conference on Technology Enhanced Learning (EC-TEL 2014), Graz, Austria, September 16-19, 2014 (Best paper award).&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2497</id>
		<title>ADL</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2497"/>
		<updated>2015-03-11T15:21:27Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* Resource */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;This page is for the ADL project.&lt;br /&gt;
&lt;br /&gt;
== Description ==&lt;br /&gt;
&lt;br /&gt;
PAWS participation in ADL is focused in the development of MasteryGrids system. Mastery Grids is a visual-rich, interactive, adaptive E-learning platform with integrated functionalities enabling multi-facet social comparison, open user modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
The architecture supporting Mastery Grids fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the '''''Mastery Grids Interface''''',&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services,&lt;br /&gt;
&lt;br /&gt;
*backend user modeling services, and&lt;br /&gt;
&lt;br /&gt;
*backend content providing applications.&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the next figure. &lt;br /&gt;
&lt;br /&gt;
[[Image:architecture_v1.png]]&lt;br /&gt;
&lt;br /&gt;
== Resource == &lt;br /&gt;
Software sources and documentation is in GitHub. The Mastery Grids Interface, backend Aggregate and documentation can be found [https://github.com/PAWSLabUniversityOfPittsburgh/MasteryGrids here]. User model services can be found in [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices here].&lt;br /&gt;
&lt;br /&gt;
== Publications ==&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2496</id>
		<title>ADL</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2496"/>
		<updated>2015-03-11T15:20:34Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* Resource */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;This page is for the ADL project.&lt;br /&gt;
&lt;br /&gt;
== Description ==&lt;br /&gt;
&lt;br /&gt;
PAWS participation in ADL is focused in the development of MasteryGrids system. Mastery Grids is a visual-rich, interactive, adaptive E-learning platform with integrated functionalities enabling multi-facet social comparison, open user modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
The architecture supporting Mastery Grids fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the '''''Mastery Grids Interface''''',&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services,&lt;br /&gt;
&lt;br /&gt;
*backend user modeling services, and&lt;br /&gt;
&lt;br /&gt;
*backend content providing applications.&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the next figure. &lt;br /&gt;
&lt;br /&gt;
[[Image:architecture_v1.png]]&lt;br /&gt;
&lt;br /&gt;
== Resource == &lt;br /&gt;
The Mastery Grids Interface, backend Aggregate and documentation can be found [https://github.com/PAWSLabUniversityOfPittsburgh/MasteryGrids here]. User model services can be found in [https://github.com/PAWSLabUniversityOfPittsburgh/AggregateUMServices here].&lt;br /&gt;
&lt;br /&gt;
== Publications ==&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2495</id>
		<title>ADL</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2495"/>
		<updated>2015-03-11T15:16:15Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;This page is for the ADL project.&lt;br /&gt;
&lt;br /&gt;
== Description ==&lt;br /&gt;
&lt;br /&gt;
PAWS participation in ADL is focused in the development of MasteryGrids system. Mastery Grids is a visual-rich, interactive, adaptive E-learning platform with integrated functionalities enabling multi-facet social comparison, open user modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
The architecture supporting Mastery Grids fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the '''''Mastery Grids Interface''''',&lt;br /&gt;
&lt;br /&gt;
*backend '''''Aggregate''''' services communicating between the main interface and user modeling services,&lt;br /&gt;
&lt;br /&gt;
*backend user modeling services, and&lt;br /&gt;
&lt;br /&gt;
*backend content providing applications.&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the next figure. &lt;br /&gt;
&lt;br /&gt;
[[Image:architecture_v1.png]]&lt;br /&gt;
&lt;br /&gt;
== Resource == &lt;br /&gt;
tutorials/slide/github&lt;br /&gt;
&lt;br /&gt;
== Publications ==&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2494</id>
		<title>ADL</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2494"/>
		<updated>2015-03-11T15:14:43Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;This page is for the ADL project.&lt;br /&gt;
&lt;br /&gt;
== Description ==&lt;br /&gt;
&lt;br /&gt;
PAWS participation in ADL is focused in the development of MasteryGrids system. Mastery Grids is a visual-rich, interactive, adaptive E-learning platform with integrated functionalities enabling multi-facet social comparison, open user modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
The architecture supporting Mastery Grids fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the Mastery Grids interface,&lt;br /&gt;
&lt;br /&gt;
*backend Aggregate services communicating between the main interface and user modeling services,&lt;br /&gt;
&lt;br /&gt;
*backend user modeling services, and&lt;br /&gt;
&lt;br /&gt;
*backend content providing applications.&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the next figure. &lt;br /&gt;
&lt;br /&gt;
[[Image:architecture_v1.png]]&lt;br /&gt;
&lt;br /&gt;
== Resource == &lt;br /&gt;
tutorials/slide/github&lt;br /&gt;
&lt;br /&gt;
== Publications ==&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=File:Architecture_v1.png&amp;diff=2493</id>
		<title>File:Architecture v1.png</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=File:Architecture_v1.png&amp;diff=2493"/>
		<updated>2015-03-11T15:14:16Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2492</id>
		<title>ADL</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2492"/>
		<updated>2015-03-11T15:13:59Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* Description */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;This page is for the ADL project.&lt;br /&gt;
&lt;br /&gt;
== Description ==&lt;br /&gt;
&lt;br /&gt;
PAWS participation in ADL is focused in the development of MasteryGrids system. Mastery Grids is a visual-rich, interactive, adaptive E-learning platform with integrated functionalities enabling multi-facet social comparison, open user modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
The architecture supporting Mastery Grids fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components:&lt;br /&gt;
&lt;br /&gt;
*frontend user-system interaction interface, the Mastery Grids interface,&lt;br /&gt;
&lt;br /&gt;
*backend Aggregate services communicating between the main interface and user modeling services,&lt;br /&gt;
&lt;br /&gt;
*backend user modeling services, and&lt;br /&gt;
&lt;br /&gt;
*backend content providing applications.&lt;br /&gt;
&lt;br /&gt;
An overall architecture of the system can be sen in the next figure. &lt;br /&gt;
[[Image:architecture_v1.png]]&lt;br /&gt;
&lt;br /&gt;
== Resource == &lt;br /&gt;
tutorials/slide/github&lt;br /&gt;
&lt;br /&gt;
== Publications ==&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2491</id>
		<title>ADL</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=ADL&amp;diff=2491"/>
		<updated>2015-03-11T15:10:41Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: /* Description */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;This page is for the ADL project.&lt;br /&gt;
&lt;br /&gt;
== Description ==&lt;br /&gt;
&lt;br /&gt;
PAWS participation in ADL is focused in the development of MasteryGrids system. Mastery Grids is a visual-rich, interactive, adaptive E-learning platform with integrated functionalities enabling multi-facet social comparison, open user modeling, and multi-type learning materials support. It presents and compares user learning progress and knowledge level (mastery) by colored grids, tracks user activities and feedbacks dynamically and provides flexible user-centered navigation across different content levels (e.g. topic, question) and different content types (e.g. question, example) of learning materials.&lt;br /&gt;
The architecture supporting Mastery Grids fulfills a major objective, portability, which is the ability to be integrated to other systems with little set up and modification. The architecture is modular and includes different software components:&lt;br /&gt;
&lt;br /&gt;
frontend user-system interaction interface, the Mastery Grids interafce,&lt;br /&gt;
&lt;br /&gt;
backend Aggregate services communicating between the main interface and user modeling services,&lt;br /&gt;
&lt;br /&gt;
backend user modeling services, and&lt;br /&gt;
&lt;br /&gt;
backend content providing applications.&lt;br /&gt;
&lt;br /&gt;
== Resource == &lt;br /&gt;
tutorials/slide/github&lt;br /&gt;
&lt;br /&gt;
== Publications ==&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
	<entry>
		<id>https://adapt2.sis.pitt.edu/w/index.php?title=Publications&amp;diff=2143</id>
		<title>Publications</title>
		<link rel="alternate" type="text/html" href="https://adapt2.sis.pitt.edu/w/index.php?title=Publications&amp;diff=2143"/>
		<updated>2014-06-10T15:01:20Z</updated>

		<summary type="html">&lt;p&gt;Jguerra: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;===ADVISE===&lt;br /&gt;
{{:Adaptive_VIBE}}&lt;br /&gt;
&lt;br /&gt;
===[[AnnotEx]]===&lt;br /&gt;
* Hsiao, I. and Brusilvsky, P. (2011) '''The Role of Community Feedback in the Student Example Authoring Process: an Evaluation of AnnotEx''', British Journal of Educational Technology, Vol 42, Issue 3, Pages 482 - 499 [http://dx.doi.org/10.1111/j.1467-8535.2009.01030.x DOI]&lt;br /&gt;
* Hsiao, I. &amp;amp; Brusilovsky. P. (2008). '''Modeling Peer Review in Example Annotation'''. ICCE, The 16th International Conference on Computers in Education, Taipei, Taiwan, October 27- 31, 2008, ICCE [http://apsce.net/icce2008/contents/proceeding_0357.pdf URL] [http://www.sis.pitt.edu/~ihsiao/pub/5page_camera%20ready_ICCE_Modeling_Peer_Review_in_Example_Annotation.pdf PDF]&lt;br /&gt;
* Brusilovsky, P., Hsiao, I. &amp;amp; Yuldelson, M. (2008) '''Annotated Program Examples as First Class Objects in an Educational Digital Library''', JCDL 2008 [http://doi.acm.org/10.1145/1378889.1378946 DOI]&lt;br /&gt;
* Hsiao, I. &amp;amp; Brusilovsky, P. (2007) '''Collaborative Example Authoring System: The Value of Re-annotation based on Community Feedback''',In: J. Nall and R. Robson (eds.) Proceedings of World Conference on E-Learning, E-Learn 2007,Quebec City, Canada, October 15-19, 2007, AACE  [http://www.editlib.org/p/26914 URL] [http://www.sis.pitt.edu/~ihsiao/pub/2007ELearn_Collaborative_Example_Authoring_System_final.pdf PDF]&lt;br /&gt;
&lt;br /&gt;
===ASSIST===&lt;br /&gt;
* Freyne, J., Farzan, R., and Coyle, M. (2007). Toward the exploitation of social access patterns for recommendation. RecSys 2007.&lt;br /&gt;
* Farzan, R., Coyle, M., Freyne, J., Brusilovsky, P., and Smyth, P. (2007). ASSIST: Adaptive Social Support for Information Space Traversal. Hypertext 2007.&lt;br /&gt;
* Freyne J., Farzan R., Brusilovsky P., Smyth B., and Coyle M. (2007). Collecting Community Wisdom: Integrating Social Search &amp;amp; Social Navigation. In Proceedings of International Conference on Intelligent User Interfaces&lt;br /&gt;
&lt;br /&gt;
===Conference Navigator===&lt;br /&gt;
* [[User:Clau|López C.]], Farzan R., Sahebi S., and Brusilovsky P. (2013). What Influences the Decision to Participate in Audience-bounded Online Communities. iConference 2013.&lt;br /&gt;
* [[User:Clau|López C.]], Farzan R., and Brusilovsky P. (2012). Personalized Incremental Users' Engagement: Driving Contributions One Step Forward. ACM GROUP 2012.&lt;br /&gt;
* Farzan R., and Brusilovsky P. Where did the Researchers Go? Supporting Social Navigation at a Large Academic Conference. Hypertext 2008.&lt;br /&gt;
&lt;br /&gt;
===[[CourseAgent]]===&lt;br /&gt;
* Farzan, R. and Brusilovsky, P. (2011) Encouraging User Participation in a Course Recommender System: An Impact on User Behavior. Computers in Human Behavior  27 (1), 276-284.&lt;br /&gt;
&lt;br /&gt;
*Farzan R. &amp;amp; Brusilovsky P. (2006). Social Navigation Support in a Course Recommendation System. In proceedings of 4th International Conference on Adaptive Hypermedia and Adaptive Web-based Systems.&lt;br /&gt;
&lt;br /&gt;
===[[CUMULATE]]===&lt;br /&gt;
{{:CUMULATE}}&lt;br /&gt;
&lt;br /&gt;
===[[Knowledge Sea II]] and [[AnnotatEd]]===&lt;br /&gt;
* Lin, Y., Brusilovsky, P., and He, D. (2011) Improving Self-Organizing Information Maps as Navigational Tools: A Semantic Approach. Online Information Review  35 (3), 401-424.&lt;br /&gt;
* Farzan, R. and Brusilovsky P. (2008). AnnotatEd: A Social Navigation and Annotation Service for Web-based Educational Resources. Journal of the New Review of Hypermedia and Multimedia (NRHM)&lt;br /&gt;
* Ahn, J., Farzan, R., and Brusilovsky, P. (2006) Social Search in the Context of Social Navigation. Journal of the Korean Society for Information Management 23(2):147-165.&lt;br /&gt;
* Bateman S., Farzan R., Brusilovsky P., and McCalla G. (2006) OATS: The Open Annotation and Tagging System. In Proceedings 3rd annual e-learning conference on Intelligent Interactive Learning Object Repositories&lt;br /&gt;
* Farzan R. &amp;amp; Brusilovsky P. (2006). AnnotatEd: A Social Navigation and Annotation Service for Web-based Educational Resources. In Proceedings of E-Learn 2006--World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education.Winner of outstanding paper award.  &lt;br /&gt;
* Mertens R., Farzan R.,and Brusilovsky P. (2006) Social Navigation in Web Lectures. In proceedings of Seventeenth ACM Conference on Hypertext and Hypermedia(short paper).&lt;br /&gt;
* Farzan, R. &amp;amp; Brusilovsky P. (2005). Social Navigation Support through Annotation-Based Group Modeling.  In proceedings of 10th International Conference on User Modeling.&lt;br /&gt;
* Brusilovsky P., Farzan R. &amp;amp; Ahn J. (2005). Comprehensive Personalized Information Access in an Educational Digital Library. In proceedings of Joint Conference on Digital Libraries.&lt;br /&gt;
* Brusilovsky, P., Chavan, G., Farzan, R. (2004). Social Adaptive Navigation Support for Open Corpus Electronic Textbooks  - In: P.De Bra (ed.) Proceedings of the Third International Conference on Adaptive Hypermedia and Adaptive Web-based Systems (AH'2004), Eindhoven, the Netherlands&lt;br /&gt;
&lt;br /&gt;
===Mastery Grids===&lt;br /&gt;
* Loboda, T., Guerra, J., Hosseini, R., Brusilovsky, P. (2014). Mastery Grids: An Open Source Social Educational Progress Visualization. Paper accepted in ECTEL 2014&lt;br /&gt;
&lt;br /&gt;
===[[AnnotEx]]===&lt;br /&gt;
* Hsiao, I. and Brusilvsky, P. (2011) '''The Role of Community Feedback in the Student Example Authoring Process: an Evaluation of AnnotEx''', British Journal of Educational Technology, Vol 42, Issue 3, Pages 482 - 499 [http://dx.doi.org/10.1111/j.1467-8535.2009.01030.x DOI]&lt;br /&gt;
&lt;br /&gt;
===[[NameSieve]]===&lt;br /&gt;
{{:NameSieve}}&lt;br /&gt;
&lt;br /&gt;
===[[NavEx]]===&lt;br /&gt;
{{:NavEx}}&lt;br /&gt;
&lt;br /&gt;
===[[PERSEUS]]===&lt;br /&gt;
{{:PERSEUS}}&lt;br /&gt;
&lt;br /&gt;
===[[PittCult]]===&lt;br /&gt;
* Lee, D. H. (2008) PITTCULT: Trust-based Cultural Event Recommender, Proceedings of Doctoral Symposium on the 2nd ACM International Conference on Recommender Systems, Lausanne, Switzerland, October 23 ~ 25, 2008 &lt;br /&gt;
* Lee, D. H. (2008) PITTCULT: Recommender System using Trusted Human Network, Student Research Competition in Hypertext 2008, Pittsburgh PA., USA, June 19 ~ 21, 2008, Third Prize Winner of ACM Student Research Competition in Hypertext 2008 &amp;amp; Finalist for the Grand Prize of ACM SRC sponsored by Microsoft Research [http://pittcult.sis.pitt.edu/help.jsp Presentation], [http://www.sigweb.org/ht08/srcposters/lee.pdf pdf]&lt;br /&gt;
&lt;br /&gt;
===[[Proactive]]===&lt;br /&gt;
* Lee, D. H. &amp;amp; Brusilovsky, P. (2007) Fighting Information Overflow with Personalized Comprehensive Information Access: A Proactive Job Recommender, Proceedings of the Third International Conference on Autonomic and Autonomous Systems (ICAS '07), Athens, Greece, June 19 ~ 25, 2007 &lt;br /&gt;
* Lee, D. and Brusilovsky, P. (2012) Proactive: Comprehensive Access to Job Information. Journal of Information Processing Systems  8 (4), 707-724.&lt;br /&gt;
&lt;br /&gt;
===[[Progressor]]===&lt;br /&gt;
{{:Progressor}}&lt;br /&gt;
===[[ProgressorPlus]]===&lt;br /&gt;
{{:ProgressorPlus}}&lt;br /&gt;
&lt;br /&gt;
===[[QuizJET]] and [[JavaGuide]]===&lt;br /&gt;
* Guerra, J., Sahebi, S., Lin, Y., Brusilovsky, P. The Problem Solving Genome: Analyzing Sequential Patterns of Student Work with Parameterized Exercises. Paper accepted in EDM 2014&lt;br /&gt;
{{:QuizJET}}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
===[[TaskSieve]]===&lt;br /&gt;
{{:TaskSieve}}&lt;br /&gt;
&lt;br /&gt;
===[[YourNews]]===&lt;br /&gt;
{{:YourNews}}&lt;br /&gt;
&lt;br /&gt;
===[[Others]]===&lt;br /&gt;
* Brusilovsky, P., Hsiao, I-H. and Folajimi, Y., (2011) '''QuizMap: Open Social Student Modeling and Adaptive Navigation Support with TreeMaps''', In: Proceedings of 6th European Conference on Technology Enhanced Education (ECTEL), ECTEL 2011, Palermo, Italy, September 20-23, 2011, Springer-Verlag, Volume 6964/2011, pp.71-82&lt;/div&gt;</summary>
		<author><name>Jguerra</name></author>
		
	</entry>
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