Teacher involvement in developing ESD-based teaching materials significantly predicts AI integration ability (β = 0.236, p < 0.05, f² = 0.127)¶

Claim · All claims
Evidence · 1 study · associational r1 · q3 · i2 medium
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q3 i2 Involvement in developing ESD-aligned teaching materials had a significant positive effect on AI Integration Ability (β = 0.236, p < 0.05; f² = 0.127, moderate). → 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 · i2 · associational · r1

Same PLS-SEM survey of 122 in-service teachers; the structural path from ESD Teaching Material development to AI Integration Ability was significant at p < 0.05 with a moderate f² = 0.127, per the hypothesis test and effect-size tables.

"The ESD Teaching Material construct also had a significant effect (β = 0.236, t = 1.936, p < 0.05), indicating that teachers who are actively involved in developing ESD-aligned teaching materials are more prepared to integrate AI in their classrooms."

Discussion¶

Related Claims¶

• AI knowledge and attitudes toward AI did not significantly predict teachers' AI integration ability — related
• 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) — related
• The four-predictor model explains approximately 55.4% of variance in teachers' AI integration ability — related