Stanford Seminar - Cognitively Appropriate Computing Education for Young Learners

Explore a Stanford seminar on developing cognitively appropriate computing education for young learners. Delve into the challenges of providing access to computing education and the interdisciplinary approach to designing educational tools. Examine existing solutions that bypass literacy and early tools supporting concepts without practices. Discover the integration of computing and storytelling through voice interfaces, focusing on computational and storytelling learning goals for K-2 grade students. Learn about needfinding with educators and students, key design goals, and voice-based user flows for storytelling. Analyze the results of children creating stories and completing computing recognition tasks. Investigate the challenges of voice interfaces and the impact of visual aids on story quality. Explore the development of false belief understanding in children and its implications for educational design. Finally, examine the ARtonomous project for training autonomous navigation models integrated with code.

Introduction.
Learners Still Lack Access to Computing Education.
Interdisciplinary Approach Designing and Developing Computing Education Tools.
Thesis Statement.
Roadmap.
Existing Solutions Bypass Literacy.
Early Tools Support Concepts without Practices.
Computing and Storytelling By Voice.
Computational Learning Goals For the K-2 Grade Band.
Storytelling Learning Goals For K-2 Language Comprehension.
Needfinding with Educators and Students.
Three Key Design Goals.
Six Voice-based User Flows Storytelling.
Create a Story Scaffolded Decomposition, Abstraction, and Planning.
Each Child Told Three Stories.
Computing Recognition Task Scratch Animation Context.
Voice Interfaces Present Memory Challenges.
Instruction More Impactful in Scratch Jr.
Visual StoryCoder Yields Higher-Quality Stories.
Humans Can Robustly Reason About Agents.
Drawings Contain Human Features Before Age 6.
Typical Trajectory of False Belief Understanding Where will Rachel look for her raisins?.
Responses Follow False Belief Trajectory.
ARtonomous Training Autonomous Navigation Models To Integrate with Code.