Claims

Student self-efficacy moderates the relationship between lecturer technology use and behavioral engagement, with stronger effects for lower self-efficacy students

Claim · All claims
Evidence · 1 study · associational r2 · q3
Currency · newest study 2023 · checked against its sources 2026-10-30 (automated, 1 of 1 entry) · not reviewed by a person

Subclaims

Reading the evidence codes

q is the design tier, i the impact, n the sample, and the kind with its r the rigour judged within that kind: what each code means.

This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.

q3 i? The interaction is significant (β = -0.09, p < .001); the technology use effect on behavioral engagement is strongest at -1 SD self-efficacy (β = 0.33) and weakest at +1 SD (β = 0.16). → Hazzam 2023

Evidence

Hazzam 2023

Hazzam, J., & Wilkins, S. (2023). The influences of lecturer charismatic leadership and technology use on student online engagement, learning performance, and satisfaction. Computers & Education. https://doi.org/10.1016/j.compedu.2023.104809

q3 · i? · associational · r2

Moderation analysis (Process model 1, 5000 bootstrap samples); interaction significant (β = -0.09, t = -3.89, p < .001, ΔR² = 0.014). Unlike charismatic leadership, the technology effect remains significant at +1 SD.

"The results suggest that for -1 standard deviation from the mean on self-efficacy the effect (β = 0.33, t = 8.48, p < .001) is higher than the effect on the mean level of self-efficacy (β = 0.24, t = 7.26, p < .001) and the effect of +1 standard deviation (β = 0.16, t = 3.84, p < .001) from the mean on student self-efficacy."

Discussion

Learner Variables

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