Effort expectancy is associated with AI use only indirectly through competence, whereas hedonic motivation shows a direct positive association¶
Claim · All claims
Evidence · 1 study (2 entries) · associationalr2·q2
Currency · newest study 2026 · not yet checked against its sources · 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.
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q2 i? Effort expectancy was associated with pedagogical AI competence (β = 0.28, p = .006) and indirectly with AI use (β = 0.12, p = .021), with a non-significant direct path. → Feng 2026
q2 i? Hedonic motivation showed a significant direct positive association with AI use (β = 0.19, p = .029), independent of competence. → Feng 2026 (2)
Evidence¶
Feng 2026¶
Feng, S., Koch, M. J., & Carolus, A. (2026). AI Mindset – An empirically tested theoretical framework on the psychological factors shaping AI competence and AI use. Computers in Human Behavior: Artificial Humans. https://doi.org/10.1016/j.chbah.2026.100402
q2 · i? · associational · r2
Discussion of the SEM results for the teacher sample. The discussion states effort-related appraisals showed an indirect association with AI use through competence; the results section prints the competence path (β = 0.28, p = .006), the indirect effect (β = 0.12, p = .021), and a non-significant direct path (β = -0.08, p = .319).
"Effort-related appraisals showed an indirect association with AI use through competence, indicating that perceptions of the ease, usability, and effort required to use AI tools may be related to AI use primarily by supporting the competence required to implement AI in educational practice."
Feng 2026 (2)¶
Feng, S., Koch, M. J., & Carolus, A. (2026). AI Mindset – An empirically tested theoretical framework on the psychological factors shaping AI competence and AI use. Computers in Human Behavior: Artificial Humans. https://doi.org/10.1016/j.chbah.2026.100402
q2 · i? · associational · r?
Discussion of the SEM results for the same sample. The discussion reports hedonic motivation showed a direct positive association with AI use; the results section prints the direct path as β = 0.19, p = .029, with a non-significant indirect effect via competence.
"In contrast, affective reward appraisals, reflected by hedonic motivation, showed a direct positive association with AI use, suggesting that experiential enjoyment may be related to AI engagement indepen - dent of perceived competence."
Discussion¶
Related Claims¶
- Habit shows the strongest direct and competence-mediated associations with teachers' AI use — related
- AI-related fear shows a differentiated pattern: positive direct association with AI use but negative association with pedagogical AI competence and negative indirect effect — related
- Openness and need for relatedness are associated with teachers' AI use indirectly through pedagogical AI competence, with relatedness negatively associated with competence — related
- Pedagogical AI competence is positively associated with teachers' AI use — related
- Personal innovativeness did not significantly influence behavioral intention to use ChatGPT — related
- Hedonic motivation and habit were the strongest predictors of behavioral intention, and habit also substantially predicted use behavior — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
effort-expectancy-mediated-hedonic-motivation-direct |
title |
Effort expectancy is associated with AI use only indirectly through competence, whereas hedonic motivation shows a direct positive association |
description |
Effort expectancy is associated with AI use only indirectly through competence, whereas hedonic motivation shows a direct positive association |
status |
review |
evidence_strength |
weak |
newest_evidence |
2026 |
generated |
by process:wiki-ingest on 2026-10-12 |
trust |
unverified — no one has confirmed this page's content |
sources |
2 — feng-2026, feng-2026-2 |
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