LMS quality did not significantly influence academic performance and did not independently mediate the AI literacy–performance relationship¶

Claim · All claims
Evidence · 1 study · associational r? · q2 · i0 negligible
Currency · newest study 2025 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i0 LMS quality did not significantly influence academic performance (β = .074, p = .233) and did not independently mediate the correlation between AI literacy and academic performance (β = .061, p = .236). → Charles Atta Koduah 2025

Evidence¶

Charles Atta Koduah 2025¶

Charles Atta Koduah, Harry Barton Essel, Prosper Setsoafia, Edmund Boamah Acheampong, and 5 more. (2025). AI Literacy and Academic Performance among Non-STEM Students in KNUST: The Roles of LMS Quality and Blended-Learning Satisfaction. Research Square preprint. https://doi.org/10.21203/rs.3.rs-11239563/v1

q2 · i0 · associational · r?

Null paths in the same PLS-SEM model: the direct LMS-quality-to-performance path (β = .074, p = .233) and its independent mediation (β = .061, p = .236) were not significant.

"LMS quality did not significantly influence academic performance (β = .074, p = .233). It did not independently mediate the correlation between AI literacy and academic performance (β = .061, p = .236)."

Discussion¶

Related Claims¶

• AI literacy has a significant direct effect on academic performance among non-STEM students (β = .222, p = .001) — related
• AI literacy strongly predicts LMS quality among non-STEM students (β = .814, p < .001) — related
• The sequential pathway from AI literacy through LMS quality and blended-learning satisfaction to academic performance is significant (β = .263, p < .001) — reports the opposite
• LMS quality predicts blended-learning satisfaction, which predicts academic performance (β = .604 and β = .535) — reports the opposite