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Effect of an Analogy-Based Approach of Artificial Intelligence Pedagogy in Upper Primary Schools

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Title: Effect of an Analogy-Based Approach of Artificial Intelligence Pedagogy in Upper Primary Schools
Language: English
Authors: Dai, Yun (ORCID 0000-0002-1199-9855), Lin, Ziyan, Liu, Ang, Dai, Dan, Wang, Wenlan
Source: Journal of Educational Computing Research. 2024 61(8):159-186.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 28
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Education Level: Elementary Education
Grade 6
Intermediate Grades
Descriptors: Foreign Countries, Grade 6, Artificial Intelligence, Logical Thinking, Elementary School Students, Instructional Effectiveness, Computer Science Education, Scaffolding (Teaching Technique), Instructional Design
Geographic Terms: China
DOI: 10.1177/07356331231201342
ISSN: 0735-6331
1541-4140
Abstract: Artificial intelligence (AI) has emerged as a prominent topic in K-12 education recently. However, pedagogical design has remained a major challenge, especially among young learners. Guided by the Zone of Proximal Development theory and AI education research literature, this design-based study proposes an analogy-based pedagogical approach to support AI teaching and learning in upper primary education. This pedagogical approach is centered on human-AI comparison, where humans are gradually shifted from an analogue to a contrast to make visible the attributes, mechanisms, and processes of AI. To evaluate its effectiveness, a quasi-experimental study with mixed methods was conducted. The quantitative comparison shows that the participants in the experimental group learning with the analogy-based pedagogical approach significantly outperformed their peers with the conventional direct instructional approach in all three dimensions of AI knowledge, skills, and ethical awareness. Qualitative analyses further reveal its pedagogical benefits, including demystifying AI through relatable and engaging learning, supporting student comprehension and skill mastery, and nurturing critical thinking and attitudes. The analogy-based approach contributes to the field of K-12 AI education with an age-appropriate, child-friendly pedagogical approach. Notably, AI education should prioritize teaching for student understanding, and AI should be recognized as an independent subject with interdisciplinary applications.
Abstractor: As Provided
Entry Date: 2023
Accession Number: EJ1402101
Database: ERIC
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  Data: Effect of an Analogy-Based Approach of Artificial Intelligence Pedagogy in Upper Primary Schools
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  Data: <searchLink fieldCode="AR" term="%22Dai%2C+Yun%22">Dai, Yun</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-1199-9855">0000-0002-1199-9855</externalLink>)<br /><searchLink fieldCode="AR" term="%22Lin%2C+Ziyan%22">Lin, Ziyan</searchLink><br /><searchLink fieldCode="AR" term="%22Liu%2C+Ang%22">Liu, Ang</searchLink><br /><searchLink fieldCode="AR" term="%22Dai%2C+Dan%22">Dai, Dan</searchLink><br /><searchLink fieldCode="AR" term="%22Wang%2C+Wenlan%22">Wang, Wenlan</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Educational+Computing+Research%22"><i>Journal of Educational Computing Research</i></searchLink>. 2024 61(8):159-186.
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  Data: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
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  Data: 28
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  Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink>
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  Data: 10.1177/07356331231201342
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  Data: 0735-6331<br />1541-4140
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  Data: Artificial intelligence (AI) has emerged as a prominent topic in K-12 education recently. However, pedagogical design has remained a major challenge, especially among young learners. Guided by the Zone of Proximal Development theory and AI education research literature, this design-based study proposes an analogy-based pedagogical approach to support AI teaching and learning in upper primary education. This pedagogical approach is centered on human-AI comparison, where humans are gradually shifted from an analogue to a contrast to make visible the attributes, mechanisms, and processes of AI. To evaluate its effectiveness, a quasi-experimental study with mixed methods was conducted. The quantitative comparison shows that the participants in the experimental group learning with the analogy-based pedagogical approach significantly outperformed their peers with the conventional direct instructional approach in all three dimensions of AI knowledge, skills, and ethical awareness. Qualitative analyses further reveal its pedagogical benefits, including demystifying AI through relatable and engaging learning, supporting student comprehension and skill mastery, and nurturing critical thinking and attitudes. The analogy-based approach contributes to the field of K-12 AI education with an age-appropriate, child-friendly pedagogical approach. Notably, AI education should prioritize teaching for student understanding, and AI should be recognized as an independent subject with interdisciplinary applications.
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