The CS Instructional Area is one of the largest computer science instructional areas in the United States. This area is comprised of award-winning, creative, world-class faculty who are leading a diverse set of high-impact education- and computer science-based initiatives. By creating and sharing innovative and inclusive educational practices, visualizations, technologies, and transformative learning experiences, the instructional area is helping to redefine education at Illinois and beyond.
Strengths and Impact
Illinois Computer Science Summer Teaching Workshop
The Instructional Area hosts an annual Summer Teaching Workshop. The goal is to bring together college instructors who are engaged with teaching computer science to discuss best practices, present new ideas, challenge the status quo, propose new directions, debunk existing assumptions, advocate for new approaches, and present surprising or preliminary results. Learn more at the Summer Teaching Workshop website.
Innovative Teaching Technologies
- Interactive Visualization Systems Laboratory - Enabling exploratory deep dives into high quality and impactful data.
- PrairieLearn - An online problem-driven learning system to promote mastery in solving STEM problems.
- Computer Based Testing Facility (CBTF) - A secure proctored computer based testing environment.
- ClassTranscribe - Fully accessible video content and I•Note text, epub, pdf and latex document generation.
- Queue - Efficient and effective office hours and group formation in both in-person and online settings.
- ScribeAR - Augmented reality live captions, visualization, and speaker identification for Deaf and hard of hearing students.
Educational Data Mining, Teaching at Scale, Online Assessments, Collaborative Learning, Data-Driven Teaching
Blended Degree Programs, Pathways for Computing Education, Undergraduate Research, Professional Development and Training
Fully-Accessible Video-Based Learning; Video-to-Book Generation; ASL Glossary; Generating Accurate Captions and Content Description; Applied Machine Learning for Accessibility and Transformative Media Applications
Mastery Grading; Science and Technology Studies
CS1, Online Instruction, Frequent Small Assessment, Teaching at Scale, Effective Autograding
Teaching at Scale, Discrete Mathematics, Formal Models of Computation
Ethics and Professional Issues in Computing; Legal and Policy Issues in Computing; Digital Forensics; Computer Security; Applied Machine Learning
Incentivizing Productive Student Behaviors, Open Source Curricula, Assessment, Learning Analytics
Data Discovery, Social Media, Open-Ended Creative Assessments
Discrete Mathematics, Frequent Assessment, AI Autograding
Broadening Participation in Computing, Discrete Mathematics and Algorithms, K-12 CS Education
Autograding Math Computations and Proofs; Applying Formal Methods and Program Analysis to Computer Education
Computer Architecture, Study Skills/Habits, Students' Sense of Belonging, Frequent Low-Stakes Assessments
Application of Universal Design for Learning for Inclusive Large Classroom Teaching; Real-World-Data-Based Assignments for Experiential Learning; Active Learning Practices in STEM Courses; Affective Learning Practices; Understanding of Learning Pathways
Motion Planning and Control, Autonomous Robots, Machine Learning
Assessment, Broadening Participation in Computing, Learning Analytics, Online Learning Platforms, Teaching at Scale
Teaching at Scale, Problem-Based Learning, Immersive Learning, Assessment, Learning Analytics
Teaching at Scale, Assessment, Collaborative Learning, Online Learning Platforms
Computer Science Education
Teaching at Scale, Assessment, Introductory Programming Education, Non-Majors
Broadening Participation in Computing; K-12 CS Education; Teaching Assistant Preparation; K-12 Teacher Preparation
Pedagogy, Inclusive Classrooms, Adult and Multiple Pathways Computing Education
Experience-Based Learning, Team Projects, Peer Evaluations, Static Code Analysis