Difference between revisions of "Projects"

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===[[CSEdPad|CSEdPad: Investigating and Scaffolding Students' Mental Models during Computer Programming Tasks to Improve Learning, Engagement, and Retention]]===
 
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Supported by NSF grant IIS 1822752 (2018-2023). [[CSEdPad|==> more]]
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This project is a joint effort of research teams at the University of Memphis and the University of Pittsburgh to explore the process of code comprehension by students and build AI-based tools to support the practice and assessment of code comprehension. In the course of the project, we developed and evaluated open-learned modeling approaches, code-tracing tools to practice code comprehension, and an intelligent tutor for assessing code comprehension through explanations.
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Supported by the National Science Foundation grant IIS [https://www.nsf.gov/awardsearch/showAward?AWD_ID=1822752&HistoricalAwards=false Award 1822752] (2018-2023). [[CSEdPad|==> more]]
  
 
===[[Open Corpus Personalized Learning]]===
 
===[[Open Corpus Personalized Learning]]===

Revision as of 21:25, 31 March 2024

This page presents a list of funded projects performed by PAWS Lab. The most recent projects are shown at the top of the list.

Contents

Current Projects

An Interactive Electronic Textbook for Python Programming and Data Science Courses

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). ==> more

Investigating and Evaluating Exploratory Recommender Systems

An Infrastructure for Sustainable Innovation and Research in Computer Science Education

Integrating Complementary Learning Principles in Aphasia Rehabilitation via Adaptive Modeling

Aphasia, commonly caused by stroke or other acquired brain injuries, can have a negative effect on an individual’s quality of life, often leading to depression and feelings of isolation. A primary frustration for people with aphasia is anomia, or word-finding difficulty. In this NIH-funded project, an interdisciplinary team of researchers will work on developing and evaluating novel adaptive computer-based aphasia treatments to help improve the efficiency and long-term impact of language treatment.

Supported by NIH grant 1R01DC019325-01A1 (2021 - 2026).

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.

For a detailed description of our vision and goals, see the [home page of the project http://www.pitt.edu/~dah44/helper/]

Supported by NIH grant R01-LM013038-02 (2019 - 2023).

The Pitt Grapevine: An Academic Recommender System

The goal of the project is to connect students with research advisors at the University of Pittsburgh through an interactive recommender system.

Supported by the University of Pittsburgh through the Personalized Education program (2018-2020). ==> more

Past Projects

Community-Building and Infrastructure Design for Data-Intensive Research in Computer Science Education

The mission of this collaborative project is to support the CS Education community by supplying documentation and infrastructure to help with adopting shared standards, protocols, and tools. In this way we hope to promote

  • development and broader re-use of innovative learning content that is instrumented for rich data collection;
  • formats and tools for analysis of learner data; and
  • best practices to make large collections of learner data and associated analytics available to researchers in the CSE, data science, and learner science communities.

For a more complete description of our vision and goals, see the [home page of the project https://cssplice.github.io/]

Supported by NSF grant EHR 1740775 (2017-2021). ==> more

CSEdPad: Investigating and Scaffolding Students' Mental Models during Computer Programming Tasks to Improve Learning, Engagement, and Retention

This project is a joint effort of research teams at the University of Memphis and the University of Pittsburgh to explore the process of code comprehension by students and build AI-based tools to support the practice and assessment of code comprehension. In the course of the project, we developed and evaluated open-learned modeling approaches, code-tracing tools to practice code comprehension, and an intelligent tutor for assessing code comprehension through explanations.

Supported by the National Science Foundation grant IIS Award 1822752 (2018-2023). ==> more

Open Corpus Personalized Learning

This project challenges the assumption that adaptive hypermedia systems require expensive knowledge engineering for domain and content modeling. It replaces the carefully-crafted domain model with automatically-created domain models, lowering the cost of developing such systems while also providing a wider range of instructional paths through the content.

Supported by NSF grant IIS 1525186 (2015-2018). ==> more

Adaptive Navigation Support and Open Social Learner Modeling for PAL

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).

Supported by the Distributed Learning Initiative contract W911QY13C0032 (2013-2016). ==> more

Ensemble: Enriching Communities and Collections to Support Education in Computing

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.

Supported by NSF (2008-2014). ==> more

Engaging Students in Online Reading Through Social Progress Visualization

This project explores an alternative approach to encourage student online textbook reading using a social progress visualization interface.

Supported by Innovation in Education Award, University of Pittsburgh (2012-2013). ==> more

Personalized Social Systems for Local Communities

The project explored the use of personalization and mobile computing to increase user engagement in location-bound social systems.

Supported by Google (2010-2012). ==> more

Personalization and Social Networking for Short-Term Communities

The project explored a range of approaches, which can enable reliable social networking and personalization in communities, which exist for short period of time, like researchers attending a specific conference.

Supported by NSF (2010-2011). In collaboration with Jung Sun Oh. ==> more

Modeling and Visualization of Latent Communities

The project focused on the problem of discovering latent communities from Social Web data and presenting this data in visual form.

Supported by the Institute for Defense Analysis and NSF (2010-2012). ==> more

Personalized Exploratorium for Database Courses

The project focused on developing and evaluating of a personalized educational environment for teaching Database courses.

Supported by NSF (2007-2008). In collaboration with Vladimir Zadorozhny. ==> more

GALE: Distillation with Utility-Optimized Transcription and Translation

Supported by DARPA (2005-2007) In collaboration with Carnegie Mellon University and IBM ==> more

Personalized Access to Open Corpus Educational Resources through Adaptive Navigation Support and Adaptive Visualization

The project focused on developing technologies for personalized access to information based on adaptive navigation support, collaborative filtering, and information visualization.

Supported by NSF (2005-2010). ==> more

Adaptive Explanatory Visualization for Learning Programming Concepts

The project focused on developing and studying adaptive explanatory visualization technologies for C and Java programming languages.

Supported by NSF (2004-2007). In collaboration with Michael Spring. ==> more

Individualized Exercises for Assessment and Self-Assessment of Programming Knowledge

The project focused on developing and evaluating a personalized assessment technology for programming courses.

Supported by NSF (2003-2005). ==> more

Educational Software for Teaching and Learning Information Retrieval

Supported by Innovation in Education Award, University of Pittsburgh (2003-2004). ==> more

Supporting Learning from Examples in a Programming Course

Supported by Innovation in Education Award, University of Pittsburgh (2001-2002). ==> more

Adaptive Electronic Textbooks for World Wide Web

Supported by Alexander von Humboldt Foundation (1995-1996) and NSF (1997-1998). In collaboration with Gerhard Weber and John Anderson ==> more