Stanford Seminar - Cognitively Appropriate Computing Education for Young Learners, Griffin Dietz скачать в хорошем качестве

Stanford Seminar - Cognitively Appropriate Computing Education for Young Learners, Griffin Dietz

Griffin Dietz of Stanford University May 13, 2022 In recent years, we have seen a growing push for computing education for all children, yet computational thinking, programming, and AI education reaches only a fraction of young learners, in part because relevant educational tools often require expensive hardware or do not align with the cognitive skills and abilities (e.g., literacy) of young users. To fill these gaps we must both understand the developmental capacities of children to reason about and engage with computing concepts and design educational platforms that support age-appropriate learning. In this talk, I describe my research that 1) studies the ways that children intuitively think about everyday technology and their abilities to reason in a computational way, 2) understands the non-pedagogical needs of learners aiming to engage with this material, and 3) applies this knowledge to the design and development of accessible, approachable, and engaging systems for computing education. I will describe three projects. The first is a voice-driven application to introduce key computing concepts to children, and a multimodal extension to that system that scaffolds computational practices as well. Collectively, these systems demonstrate the capacity for voice-based interfaces to deliver just-in-time pedagogy to independent at-home learners, leading to greater system understanding and higher quality code. This project, however, opens questions about how children conceive of the voice-driven interfaces they increasingly interact with. In the second project, I describe an experimental behavioral study that demonstrates how children age 3-8 might extend their cognitive capacities to reason about humans in order to reason about virtual assistants. This research demonstrates a need for education around AI and machine learning in K-12 education, so in the third project, I describe a system for middle school reinforcement learning education in a virtual robotics context. This system develops student understanding of reinforcement learning, shows high levels of engagement, and inspires young users to want to learn more about machine learning. Learn more about Stanford's Human-Computer Interaction Graduate Program: https://online.stanford.edu/programs/... 0:00 Introduction 1:10 Learners Still Lack Access to Computing Education 1:38 Interdisciplinary Approach Designing and Developing Computing Education Tools 2:04 Thesis Statement 3:04 Roadmap 4:03 Existing Solutions Bypass Literacy 4:26 Early Tools Support Concepts without Practices 5:37 Computing and Storytelling By Voice 6:12 Computational Learning Goals For the K-2 Grade Band 6:43 Storytelling Learning Goals For K-2 Language Comprehension 7:07 Needfinding with Educators and Students 7:27 Three Key Design Goals 8:40 Six Voice-based User Flows Storytelling 8:57 Create a Story Scaffolded Decomposition, Abstraction, and Planning 11:57 Each Child Told Three Stories 13:34 Computing Recognition Task Scratch Animation Context 15:35 Voice Interfaces Present Memory Challenges 23:22 Instruction More Impactful in Scratch Jr 24:43 Visual StoryCoder Yields Higher-Quality Stories 27:56 Humans Can Robustly Reason About Agents 29:18 Drawings Contain Human Features Before Age 6 31:47 Typical Trajectory of False Belief Understanding Where will Rachel look for her raisins? 34:56 Responses Follow False Belief Trajectory 40:17 ARtonomous Training Autonomous Navigation Models To Integrate with Code