Openness and need for relatedness are associated with teachers' AI use indirectly through pedagogical AI competence, with relatedness negatively associated with competence¶
Claim · All claims
Evidence · 1 study (2 entries) · associationalr1–r2·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.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? Openness (β = 0.07, p = .036) and need for relatedness (β = -0.07, p = .026) showed significant indirect associations with AI use via pedagogical AI competence. → Feng 2026
q2 i? Need for relatedness was negatively associated with pedagogical AI competence (β = -0.16, p = .012), an unexpected finding. → 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
SEM indirect-effect results for the teacher sample. The results sentence reports significant indirect effects via pedagogical AI competence for openness and need for relatedness; the table prints the relatedness indirect effect with a negative sign (β = -0.07, p = .026).
"Significant indirect effects via pedagogical AI competence were observed for selected dispositional, contextual and social, as well as technology-related factors, including openness (β = 0.07, p = .036), need for relatedness (β = 0.07, p = .026), habit (β = 0.14, p = .011), AI-related fear (β = 0.07, p = .044), and effort expectancy (β = 0.12, p = .021)."
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 · r1
Discussion of the SEM results. The authors report the negative relatedness-to-competence association (table: β = -0.16, p = .012) was unexpected and offer explanations: the single-item operationalisation captures general interpersonal connectedness, and reliance on interpersonal support within teaching contexts may reduce perceived need to develop AI competence.
"The negative association between need for relatedness and peda - gogical AI competence was unexpected. Relatedness was operational - ised using a single item (“I feel close and connected with other people who are important to me”) which captures general interpersonal connected - ness."
Discussion¶
Related Claims¶
- 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
- Effort expectancy is associated with AI use only indirectly through competence, whereas hedonic motivation shows a direct positive association — related
- Habit shows the strongest direct and competence-mediated associations with teachers' AI use — related
- Social and organizational support relate to AI well-being indirectly through AI literacy and technological self-efficacy — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
openness-relatedness-indirect-via-competence |
title |
Openness and need for relatedness are associated with teachers' AI use indirectly through pedagogical AI competence, with relatedness negatively associated with competence |
description |
Openness and need for relatedness are associated with teachers' AI use indirectly through pedagogical AI competence, with relatedness negatively associated with competence |
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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