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Computers and Education

Computing has a large and growing impact on education. It is improving classroom interactivity, increasing accessibility, facilitating personalized learning inside and outside the classroom, and providing a platform for exploring fundamental questions about how people learn.

At the same time, demand for computer science education is skyrocketing world-wide. Reaching larger and more diverse audiences requires both understanding how people learn computer science and creating best practices for teaching specific computing topics.

Our faculty study broadly in both of these facets of computers and education. We build new systems, run them at scale, and design interfaces and study the human impacts of technology in the classroom. We gather and analyze data about student behavior to better understand the learning process using both data science techniques and qualitative research.

Faculty & Affiliate Faculty

Active Learning in Large Classrooms, Teamwork and Collaboration, Computer-Based Assessment, Instructional Technologies

Success Factors of Underrepresented Students in Online Courses, Universal Access, Crowd-Based Course Curation

Process Oriented / Guided Inquiry Learning, Training Graduate Teaching Assistants, Scalable Education, Semantics Based Autograders

Online Learning Platforms, Outcomes Assessment, Prison Education, Pedagogy

Technology to Improve Classroom Interactivity and Outcomes, Data-Driven Approaches to Teaching and Learning

Incentivizing Productive Student Behaviors, Open Source Curricula, Assessment, Learning Analytics

Outcomes Assessment

Data Discovery, Social Media, Open-Ended Creative Assessments

Scalable Education, Automated Interactive Assessment, Blended Learning

Learning at Scale

How Students Learn Computing, Studying How to Design Effective Instructional Visualization, Teaching at Scale, Assessing Student Learning

Broadening Participation in Computing, K-12 CS Education, Conceptual Change in CS, Cultural and Structural Barriers in CS, Anti-Racist CS Education

Automated Interactive Assessment, Learning Analytics, Scalable Education, Pedagogy

Teaching at Scale, Outcomes Assessment, Learning Analytics

Teaching at Scale, Assessment, Collaborative Learning, Online Learning Platforms

Pedagogy, Inclusive Classrooms, Adult and Multiple Pathways Computing Education

Intelligent Education Systems, Scalable Education, Applications of Data Science in Education

Learning Analytics, Pedagogy, Computer-Based Testing, Assessment, Asynchronous Exams, Item Generation, Concept Inventories, Plagiarism Detection

Adjunct Faculty

Collaborators

Name Research Interests
Gabrielle Allen, Astronomy/College of Education STEM Education
Carolyn Anderson, Educational Psychology, Psychology, and Statistics Underrepresented STEM Students, Multi-level Statistics
Suma Bhat, Electrical and Computer Engineering Online Spaces to Support Underrepresented STEM Students
Bill Cope, Education Policy, Organization and Leadership e-Learning Platforms
Jennifer Cromley, Educational Psychology STEM Students' Achievement and Retention
Sebastian Kelle, Computer Science Instructional Development Team Serious Games, Virtual Reality Learning, Interactive Storytelling, Instructional Design
H. Chad Lane, Educational Psychology AI in Education, Educational Games, Informal CS Education
Robb Lindgren, Curriculum & Instruction Learning in Emerging Platforms (e.g., Simulations, Virtual Environments)
Michael Loui, Electrical and Computer Engineering Motivation and Persistence of Engineering Students; Identity Development and Affective Outcomes;  Ethics in Engineering and Computing 
Luc Paquette, Curriculum & Instruction Modeling Student Behavior, Educational Data Mining, Learning Analytics
Michelle Perry, Educational Psychology Online Spaces to Support Underrepresented STEM Students
Matthew West, Mechanical Science and Engineering Online Learning Platforms, Learning Analytics, Computer-Based Testing

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