Gender does not significantly moderate the effect of AI-supported PBL on computational thinking or academic achievement¶

Claim · All claims
Evidence · 1 study (2 entries) · causal r2 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? The Group × Gender interaction on Post_CT_Total was not statistically significant, F(1, 70) = 0.41, p = .527, partial η2 = .006, so Hypothesis 3 was not supported. → Ayanwale 2026 q2 i? The Group × Gender interaction on Post_Academic_Achievement was also not statistically significant, F(1, 70) = 0.584, p = .447, partial η2 = .008. → Ayanwale 2026 (2)

Evidence¶

Ayanwale 2026¶

Ayanwale, M. A., & Omeh, C. B. (2026). AI-supported problem-based learning for enhancing computational thinking skills in STEM education. Computers in Human Behavior: Artificial Humans 7 (2026) 100263. https://doi.org/10.1016/j.chbah.2026.100263

q2 · i? · causal · r2

Two-way ANCOVA interaction term (Group × Gender) predicting Post_CT_Total in the 103-student quasi-experiment, reported in the Results section; the article states Hypothesis 3 is not supported.

"The interaction effect was not statistically significant, F (1, 70) = 0.41, p = .527, partial η2 = .006 (see Table 2a), suggesting that the influence of instructional group on computational thinking outcomes did not differ by gender"

Ayanwale 2026 (2)¶

Ayanwale, M. A., & Omeh, C. B. (2026). AI-supported problem-based learning for enhancing computational thinking skills in STEM education. Computers in Human Behavior: Artificial Humans 7 (2026) 100263. https://doi.org/10.1016/j.chbah.2026.100263

q2 · i? · causal · r2

The Group × Gender row for Post_Academic_Achievement in the ANCOVA summary table (Table 2a) of the same study, printed as "0.584 .447 .008" for F, p, and η2.

"​ Group × Gender 0.584 .447 .008"

Discussion¶

Learner Variables¶

• Gender — moderator: an instructional effect differs by group

Related Claims¶

• GenAI function, intervention duration, publication year, and gender were not significant moderators of GenAI's motivational effect — the general claim this finding bears on, with the studies behind it
• AI-PBL students achieve high normalized learning gains (g = 0.73) in computational thinking and academic achievement while control students record low gains (g ≤ 0.20) — related
• AI-supported PBL students obtain significantly higher posttest computational thinking scores than traditional-lecture students when controlling pretest scores — related
• AI-supported PBL students obtain significantly higher posttest academic achievement scores in robotics programming than traditional-lecture students when controlling pretest scores — related
• Pedagogical tool significantly moderates the CT gender gap, with programming and robots associated with male-favoring gaps and other tools (e.g., web-based) showing a negative significant effect — related