Teachers' practical use of AI in science and green energy learning significantly predicts their AI integration ability (β = 0.391, p < 0.01, f² = 0.180)¶

Claim · All claims
Evidence · 1 study · associational r1 · q3 · i3 large
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q3 i3 Use of AI in science and green energy learning had a significant positive effect on AI Integration Ability (β = 0.391, p < 0.01), with a moderate effect size (f² = 0.180). → Riandi Riandi 2026

Evidence¶

Riandi Riandi 2026¶

Riandi Riandi, Ismail Ismail, Ida Kaniawati, Wahyu Sopandi, Diana Ayu Rostikawati, Defrizal Hamka & Suhendar Suhendar. (2026). Teacher involvement in developing sustainable education materials for AI integration in green energy education. Scientific Reports. https://doi.org/10.1038/s41598-025-34422-4

q3 · i3 · associational · r1

PLS-SEM analysis of survey data from 122 in-service teachers in a professional development program, using dichotomous questionnaire indicators. The structural path from Use of AI in Science and Green Energy to AI Integration Ability was significant, "with a moderate effect size (f 2 = 0.180)".

"Hypothesis testing revealed that the Use of AI in Science and Green Energy had a significant influence on AI Integration Ability (β = 0.391, t = 3.063, p < 0.01), with a moderate effect size (f 2 = 0.180)."

Discussion¶

Related Claims¶

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