Breakout Workshops
Concurrent Session I (60 minutes): 8:40 AM–9:40 AM, ET:
Concurrent Session IV (60 minutes): 2:00 PM – 3:00 PM, ET:
Concurrent Session I (60 minutes): 8:40 AM–9:40 AM, ET:
- Workshop 1: Bridging Math and Code: Teaching Algebra with Scratch Programming (By Heejung An, William Paterson University of New Jersey)
- Workshop 2: Deploying Design Justice to Code Solutions for Communities in Need (By Antonio Byrd, University of Missouri-Kansas City)
- Workshop 3: Teach About Artificial Intelligence Starting in Kindergarten? ABSOLUTELY (By Vicky Sedgwick, Computer Science Teachers Association (CSTA) Greater Los Angeles Chapter)
- Workshop 4: Teaching Introductory Programming with Generative Artificial Intelligence (AI): Strategies for CS and Engineering Educators (By Olgun Sadik, Indiana University)
- Workshop 5: Advancing Computer Science (Python Programming) Instruction through Process-Based Analytics (By Donggil Song, Texas A&M University)
- Workshop 6: Pathways to CS: Scaffolding Learning Across K-6 Grades with Free Online Resources (By Denise Post and Melissa VanWingerden, New Providence Public Schools, NJ)
- Workshop 7: Cybersecurity in the Classroom: Attacks, Tools, and Defenses (By Kiho Lim, William Paterson University of New Jersey)
- Workshop 8: The Synergy Between Literacy and Computer Science in Elementary Grades (By Vicky Sedgwick, Computer Science Teachers Association (CSTA) Greater Los Angeles Chapter)
- Workshop 9: Develop a Foundational Understanding of Coding Through Geometric Patterns Using Hopscotch (By Woonhee Sung, The University of Texas at Tyler)
Concurrent Session IV (60 minutes): 2:00 PM – 3:00 PM, ET:
- Workshop 10: Unplugged-to-Plugged: A Blended Approach to Coding Instruction (By Jessica Kerr, Barnett Shoals Elementary in Athens, GA; University of Georgia)
- Workshop 11: Introducing Machine Learning to Young Learners: Practical Approaches (By Gihan Mohamad, William Paterson University of New Jersey)
- Workshop 12: Empowering Computer Science (CS) Teaching with Artificial Intelligence (AI): Practical Uses of Large Language Models in Programming Education (By Meina Zhu, Wayne State University)
