Design and Effects of a Chemistry Data Training Program using the No-Code Orange3 Tool: Enhancing In-Service Chemistry Teachers’ AI Teaching Efficacy and Data Literacy 


Vol. 69,  No. 6, pp. 345-355, Dec.  2025
10.5012/jkcs.2025.69.6.345


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  Abstract

This study developed an educational program that integrates AI and data science into chemistry teaching using the no-code machine learning platform Orange3 and examined its effects with 20 in-service chemistry teachers. The program was designed to provide hands-on experience across the entire process of data collection, preprocessing, visualization, and modeling. Quantitative analysis revealed significant improvements in all subdomains of data literacy and in teachers’ individual AI teaching efficacy. Qualitative analysis identified three key themes: (1) a shift in perception of AI from an expert-exclusive domain to a universally accessible tool, (2) the enhancement of chemistry concept understanding through Orange3’s visualization features, and (3) the strengthening of teachers’ practical willingness to apply data-driven lessons to students. These findings suggest that no-code AI tools can expand teachers’ instructional competencies and contribute to innovation in data-driven science education.

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  Cite this article

[IEEE Style]

H. Yang, S. Kim, S. Kang, "Design and Effects of a Chemistry Data Training Program using the No-Code Orange3 Tool: Enhancing In-Service Chemistry Teachers’ AI Teaching Efficacy and Data Literacy," Journal of the Korean Chemical Society, vol. 69, no. 6, pp. 345-355, 2025. DOI: 10.5012/jkcs.2025.69.6.345.

[ACM Style]

Heesun Yang, Shin-Yu Kim, and Seong-Joo Kang. 2025. Design and Effects of a Chemistry Data Training Program using the No-Code Orange3 Tool: Enhancing In-Service Chemistry Teachers’ AI Teaching Efficacy and Data Literacy. Journal of the Korean Chemical Society, 69, 6, (2025), 345-355. DOI: 10.5012/jkcs.2025.69.6.345.

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