Research Projects
Filtered by: Youth Experience, Learning, and Digital Practices
An AI-Enhanced Colleague for Teachers: Developing and Studying an Innovative Platform for Efficient, Inclusive Middle-Grade Mathematics Lesson Planning
Funders: National Science Foundation
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval Youth Experience, Learning, and Digital Practices
This project supports middle school math teachers by developing an AI-powered lesson planning tool that enhances efficiency, quality, and inclusivity. Integrating generative AI with research-based practices, it offers personalized guidance for creating effective lessons. The project also examines impacts on teacher stress, instructional effectiveness, and student learning outcomes.
Funders: National Science Foundation
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval Youth Experience, Learning, and Digital Practices
This project supports middle school math teachers by developing an AI-powered lesson planning tool that enhances efficiency, quality, and inclusivity. Integrating generative AI with research-based practices, it offers personalized guidance for creating effective lessons. The project also examines impacts on teacher stress, instructional effectiveness, and student learning outcomes.
Campus Computation Center: Support, Enrichment & Computing Identity Development to Boost STEM Success
Principal Investigator(s): Katherine Izsak Ron Padrón Vedat G. Diker Bill Kules beth bonsignore
Funders: DoD-Navy
Research Areas: Accessibility and Inclusive Design Human-Computer Interaction Youth Experience, Learning, and Digital Practices
The project focuses on several research areas, including Accessibility and Inclusive Design, Human-Computer Interaction, and Youth Experience, Learning, and Digital Practices.
Principal Investigator(s): Katherine Izsak Ron Padrón Vedat G. Diker Bill Kules beth bonsignore
Funders: DoD-Navy
Research Areas: Accessibility and Inclusive Design Human-Computer Interaction Youth Experience, Learning, and Digital Practices
The project focuses on several research areas, including Accessibility and Inclusive Design, Human-Computer Interaction, and Youth Experience, Learning, and Digital Practices.
CAREER: API Can Code: Situating Computational Learning Opportunities in the Digital Lives of Students
Principal Investigator(s): David Weintrop
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Human-Computer Interaction Youth Experience, Learning, and Digital Practices
Principal Investigator(s): David Weintrop
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Human-Computer Interaction Youth Experience, Learning, and Digital Practices
Collaborative Research: Harmonizing Scratch Encore: Empowering Educators to Create Customized Culturally-Responsive Computing Materials
Principal Investigator(s): David Weintrop
Funders: National Science Foundation
Research Areas: Youth Experience, Learning, and Digital Practices
This project explores ways to support middle school computer science teachers in drawing on their students' cultural resources and prior knowledge to situate introductory computer science learning experiences.
Principal Investigator(s): David Weintrop
Funders: National Science Foundation
Research Areas: Youth Experience, Learning, and Digital Practices
This project explores ways to support middle school computer science teachers in drawing on their students' cultural resources and prior knowledge to situate introductory computer science learning experiences.
Computer and Information Science and Engineering Graduate Fellowships (CSGrad4US) – Micah Morgan
Principal Investigator(s): Sheena Erete
Funders: Computing Research Association Other Non-Federal
Research Areas: Information Justice, Human Rights, and Technology Ethics Library and Information Science Youth Experience, Learning, and Digital Practices
The CSGrad4US Fellowship Program supports domestic bachelor’s degree holders returning to academia by providing mentoring and funding to pursue PhDs in computing. Through this cooperative agreement, the Computing Research Association will manage recruitment, applications, mentoring, and program evaluation to expand diversity in CISE fields.
Principal Investigator(s): Sheena Erete
Funders: Computing Research Association Other Non-Federal
Research Areas: Information Justice, Human Rights, and Technology Ethics Library and Information Science Youth Experience, Learning, and Digital Practices
The CSGrad4US Fellowship Program supports domestic bachelor’s degree holders returning to academia by providing mentoring and funding to pursue PhDs in computing. Through this cooperative agreement, the Computing Research Association will manage recruitment, applications, mentoring, and program evaluation to expand diversity in CISE fields.
Designing a Computer Science Pre-service Teacher Methods Course for Maryland
Principal Investigator(s): David Weintrop
Funders: Maryland Center for Computing Education (MCCE) State of MD UMD Funded
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval Youth Experience, Learning, and Digital Practices
Principal Investigator(s): David Weintrop
Funders: Maryland Center for Computing Education (MCCE) State of MD UMD Funded
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval Youth Experience, Learning, and Digital Practices
Developing and Investigating Data Science Interventions Connected to University Athletics to Address Systemic Racism in Undergraduate STEM Education (better known as DataGOAT)
Principal Investigator(s): Tamara Clegg
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Future of Work Health Informatics Human-Computer Interaction Information Justice, Human Rights, and Technology Ethics Social Networks, Online Communities, and Social Media Youth Experience, Learning, and Digital Practices
This project, DataGOAT, engages Black male collegiate athletes in data science by connecting their sports performance and health data to STEM learning. It aims to overcome racialized stereotypes, foster STEM identities, and create educational pathways through courses, internships, and data analysis tools, benefiting both participants and the broader educational community.
Principal Investigator(s): Tamara Clegg
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Future of Work Health Informatics Human-Computer Interaction Information Justice, Human Rights, and Technology Ethics Social Networks, Online Communities, and Social Media Youth Experience, Learning, and Digital Practices
This project, DataGOAT, engages Black male collegiate athletes in data science by connecting their sports performance and health data to STEM learning. It aims to overcome racialized stereotypes, foster STEM identities, and create educational pathways through courses, internships, and data analysis tools, benefiting both participants and the broader educational community.
HCC: Small: The Incel Phenomenon: Assessing Radicalization and Deradicalization Online
Principal Investigator(s): Jennifer Golbeck
Funders: National Science Foundation
Research Areas: Human-Computer Interaction Information Justice, Human Rights, and Technology Ethics Social Networks, Online Communities, and Social Media Youth Experience, Learning, and Digital Practices
This project, led by Jennifer Golbeck at UMD’s College of Information, studies how radicalization and deradicalization occur within online incel communities.
Principal Investigator(s): Jennifer Golbeck
Funders: National Science Foundation
Research Areas: Human-Computer Interaction Information Justice, Human Rights, and Technology Ethics Social Networks, Online Communities, and Social Media Youth Experience, Learning, and Digital Practices
This project, led by Jennifer Golbeck at UMD’s College of Information, studies how radicalization and deradicalization occur within online incel communities.
Information Technology Access RERC
Principal Investigator(s): J. Bern Jordan Amanda Lazar Hernisa Kacorri
Funders: DHHS-Administration for Community Living Other Federal
Research Areas: Accessibility and Inclusive Design Human-Computer Interaction Information Justice, Human Rights, and Technology Ethics Machine Learning, AI, Computational Linguistics, and Information Retrieval Youth Experience, Learning, and Digital Practices
The University of Maryland Information Technology RERC aims to improve accessibility for people with disabilities through research, technology development, and standards creation. Key initiatives include individualizing generative AI, enhancing usability for older adults, developing cross-disability solutions, and creating open-source tools and guidelines to ensure broad, equitable access to information and communication technologies.
Principal Investigator(s): J. Bern Jordan Amanda Lazar Hernisa Kacorri
Funders: DHHS-Administration for Community Living Other Federal
Research Areas: Accessibility and Inclusive Design Human-Computer Interaction Information Justice, Human Rights, and Technology Ethics Machine Learning, AI, Computational Linguistics, and Information Retrieval Youth Experience, Learning, and Digital Practices
The University of Maryland Information Technology RERC aims to improve accessibility for people with disabilities through research, technology development, and standards creation. Key initiatives include individualizing generative AI, enhancing usability for older adults, developing cross-disability solutions, and creating open-source tools and guidelines to ensure broad, equitable access to information and communication technologies.
Integration of Computer-Assisted Methods and Human Interactions to Understand Lesson Plan Quality and Teaching to Advance Middle-Grade Mathematics Instruction
Principal Investigator(s): Wei Ai
Funders: University of Washington Other Non-Federal
Research Areas: Data Science, Analytics, and Visualization Future of Work Human-Computer Interaction Machine Learning, AI, Computational Linguistics, and Information Retrieval Youth Experience, Learning, and Digital Practices
This NSF-funded project uses machine learning, human coding, and teacher input to evaluate the quality of middle-grades mathematics lesson plans. By combining computational analysis with educator perspectives, it aims to improve how instructional materials are assessed and used in classrooms.
Principal Investigator(s): Wei Ai
Funders: University of Washington Other Non-Federal
Research Areas: Data Science, Analytics, and Visualization Future of Work Human-Computer Interaction Machine Learning, AI, Computational Linguistics, and Information Retrieval Youth Experience, Learning, and Digital Practices
This NSF-funded project uses machine learning, human coding, and teacher input to evaluate the quality of middle-grades mathematics lesson plans. By combining computational analysis with educator perspectives, it aims to improve how instructional materials are assessed and used in classrooms.
Read, Watch, Play: Development of a Pedagogical Approach and Technical Infrastructure to Build Gamification, Game-Based Learning, and Other Hands-On Projects into Courses across Campus
Principal Investigator(s): Caro Williams-Pierce Andrew Fellows Katherine Izsak Pamela Duffy
Funders: State of MD
Research Areas: Youth Experience, Learning, and Digital Practices
Principal Investigator(s): Caro Williams-Pierce Andrew Fellows Katherine Izsak Pamela Duffy
Funders: State of MD
Research Areas: Youth Experience, Learning, and Digital Practices