Projects - Revision history

Peterb: /* Past Projects */

2024-04-21T19:09:30Z

‎Past Projects

Peterb: /* Current Projects */

2024-04-21T19:09:18Z

‎Current Projects

Peterb: /* An Infrastructure for Sustainable Innovation and Research in Computer Science Education */

2024-04-04T01:38:50Z

‎An Infrastructure for Sustainable Innovation and Research in Computer Science Education

Peterb: /* An Infrastructure for Sustainable Innovation and Research in Computer Science Education */

2024-04-04T01:37:08Z

‎An Infrastructure for Sustainable Innovation and Research in Computer Science Education

Peterb: /* An Interactive Electronic Textbook for Python Programming and Data Science Courses */

2024-04-04T01:35:05Z

‎An Interactive Electronic Textbook for Python Programming and Data Science Courses

Peterb: /* Investigating and Evaluating Exploratory Recommender Systems */

2024-04-04T00:08:20Z

‎Investigating and Evaluating Exploratory Recommender Systems

Peterb: /* Investigating and Evaluating Exploratory Recommender Systems */

2024-04-04T00:07:11Z

‎Investigating and Evaluating Exploratory Recommender Systems

Peterb: /* Investigating and Evaluating Exploratory Recommender Systems */

2024-04-04T00:05:39Z

‎Investigating and Evaluating Exploratory Recommender Systems

Peterb: /* HELPeR - Health e-Librarian with Personalized Recommender */

2024-04-03T02:48:16Z

‎HELPeR - Health e-Librarian with Personalized Recommender

Peterb: /* HELPeR - Health e-Librarian with Personalized Recommender */

2024-04-03T02:47:42Z

‎HELPeR - Health e-Librarian with Personalized Recommender

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 Supported by the University of Pittsburgh through the Personalized Education program (2018-2020). [[The Pitt Grapevine|==> more]]
-== Past Projects ==
+== Past Funded Projects ==
 ===[[Community-Building and Infrastructure Design for Data-Intensive Research in Computer Science Education]]===

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 Mohammad https://arxiv.org/abs/2312.02105
 Rully Hendrawan [LLM for domain modeling](https://docs.google.com/presentation/d/1EjlC0MUKzbWKfOMHJffrVXJ31cbjJFcxIv5F9HBjULU/edit?usp=sharing) -->
-== Current Projects ==
+== Current Funded Projects ==
 ===[[An Interactive Electronic Textbook for Python Programming and Data Science Courses]] ===

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 ===[[An Infrastructure for Sustainable Innovation and Research in Computer Science Education]]===
 Researchers from the University of Pittsburgh, Carnegie Mellon University, North Carolina State University, and Virginia Tech collaborate to support the Computer Science Education Hub, social and technical infrastructure to accelerate research on teaching and learning of computing disciplines. The Hub will host community events and provide a web repository for computing education datasets, tools, and common analysis methods. The Hub facilitates creation and adoption of new tools to support computing educators and students, and new standards to support data collection and data-enabled research. Hub community events help researchers and educators from many learning contexts to develop and improve computing education resources.
 ===[[Integrating Complementary Learning Principles in Aphasia Rehabilitation via Adaptive Modeling]]===

← Older revision		Revision as of 01:37, 4 April 2024
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	===[[An Infrastructure for Sustainable Innovation and Research in Computer Science Education]]===		===[[An Infrastructure for Sustainable Innovation and Research in Computer Science Education]]===
		+	Researchers from the University of Pittsburgh, Carnegie Mellon University, North Carolina State University, and Virginia Tech collaborate to support the Computer Science Education Hub, social and technical infrastructure to accelerate research on teaching and learning of computing disciplines. The Hub will host community events and provide a web repository for computing education datasets, tools, and common analysis methods. The Hub facilitates creation and adoption of new tools to support computing educators and students, and new standards to support data collection and data-enabled research. Hub community events help researchers and educators from many learning contexts to develop and improve computing education resources.

	===[[Integrating Complementary Learning Principles in Aphasia Rehabilitation via Adaptive Modeling]]===		===[[Integrating Complementary Learning Principles in Aphasia Rehabilitation via Adaptive Modeling]]===

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 Peter Brusilovsky proposes to develop AdaPT, an interactive and adaptive system for learning and practicing Python programming and Data Science skills, which fuses a well-tested electronic textbook with a large volume of “smart” interactive learning content: worked code examples, code animations, and several types of automatically assessed practice problems. The system uses advanced learner modeling to trace the growth of learner’s knowledge and skills and to identify misunderstood concepts. Adapting dynamically to the current state of knowledge, it suggests most appropriate interactive content to practice at every step of learning.
-Supported by Innovation in Education Award, University of Pittsburgh (2023-2024). [[An Interactive Electronic Textbook for Python Programming and Data Science Courses|==> more]]
+Supported by [https://www.provost.pitt.edu/acie/awards/funded-projects Innovation in Education Award], University of Pittsburgh (2023-2024). [[An Interactive Electronic Textbook for Python Programming and Data Science Courses|==> more]]
 ===[[Investigating and Evaluating Exploratory Recommender Systems]]===

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 Exploratory recommender systems bring together the power of Human and Artificial Intelligence through human-AI collaboration and user-controlled recommendation. In this project, we develop and evaluate exploratory recommender systems in several domains. The focus of the project are carousel-based interfaces and novel recommender algorithms that can better adapt to user actions in the human-AI collaboration process.
-The project is supported by Amazon Research Award to Peter Brusilovsky (2022-2024) ==> [[Investigating and Evaluating Exploratory Recommender Systems|more]]
+Supported by Amazon Research Award to Peter Brusilovsky (2022-2024) [[Investigating and Evaluating Exploratory Recommender Systems|==> more]]
 ===[[An Infrastructure for Sustainable Innovation and Research in Computer Science Education]]===

← Older revision		Revision as of 00:05, 4 April 2024
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	===[[Investigating and Evaluating Exploratory Recommender Systems]]===		===[[Investigating and Evaluating Exploratory Recommender Systems]]===
		+	Exploratory recommender systems bring together the power of Human and Artificial Intelligence through human-AI collaboration and user-controlled recommendation. In this project, we develop and evaluate exploratory recommender systems in several domains. The focus of the project are carousel-based interfaces and novel recommender algorithms that can better adapt to user actions in the human-AI collaboration process.
		+
		+	The project is supported by Amazon Research Award to Peter Brusilovsky

	===[[An Infrastructure for Sustainable Innovation and Research in Computer Science Education]]===		===[[An Infrastructure for Sustainable Innovation and Research in Computer Science Education]]===

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 ===[[HELPeR - Health e-Librarian with Personalized Recommender]]===
-As the Internet has become a prominent source of health information to guide patients’ decision-making and self-management activities, patients strongly indicate they need navigational support to locate appropriate information on the Internet. The overall goal of this project is to build and implement a “Health E-Librarian with Personalized Recommendations (HELPeR)” - a personalized information access system with a hybrid recommender engine that adapts to different aspects of the patient: information needs based on the user’s profile, the user’s uniquely expressed information interests, and the level of user’s disease-related knowledge. The overall goal of our project is to build and implement a “Health E-Librarian with Personalized Recommendations (HELPeR)”, a personalized digital librarian that provides individualized, reliable online information relevant to the patient’s needs, interests, and knowledge across the disease trajectory.
+As the Internet has become a prominent source of health information to guide patients’ decision-making and self-management activities, patients strongly indicate they need navigational support to locate appropriate information on the Internet. The overall goal of this project is to build and implement a “Health E-Librarian with Personalized Recommendations (HELPeR)” - a personalized information access system with a hybrid recommender engine that adapts to different aspects of the patient: information needs based on the user’s profile, the user’s uniquely expressed information interests, and the level of user’s disease-related knowledge.
 Supported by NIH grant [https://www.grantome.com/grant/NIH/R01-LM013038-02 R01-LM013038-02] (2019 - 2023).