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Title: Designing a Visual Interface for Elementary Students to Formulate AI Planning Tasks
Recent years have seen the rapid adoption of artificial intelligence (AI) in every facet of society. The ubiquity of AI has led to an increasing demand to integrate AI learning experiences into K-12 education. Early learning experiences incorporating AI concepts and practices are critical for students to better understand, evaluate, and utilize AI technologies. AI planning is an important class of AI technologies in which an AI-driven agent utilizes the structure of a problem to construct plans of actions to perform a task. Although a growing number of efforts have explored promoting AI education for K-12 learners, limited work has investigated effective and engaging approaches for delivering AI learning experiences to elementary students. In this paper, we propose a visual interface to enable upper elementary students (grades 3-5, ages 8-11) to formulate AI planning tasks within a game-based learning environment. We present our approach to designing the visual interface as well as how the AI planning tasks are embedded within narrative-centered gameplay structured around a Use-Modify-Create scaffolding progression. Further, we present results from a qualitative study of upper elementary students using the visual interface. We discuss how the Use-Modify-Create approach supported student learning as well as discuss the misconceptions and more » usability issues students encountered while using the visual interface to formulate AI planning tasks. « less
Authors:
; ; ; ; ; ; ;
Award ID(s):
1934153 1934128
Publication Date:
NSF-PAR ID:
10352381
Journal Name:
2021 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)
Page Range or eLocation-ID:
1 to 9
Sponsoring Org:
National Science Foundation
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