Claims

Course major moderates the predictive effects on Gen Z students' AI adoption

Claim · All claims
Evidence · 1 study · associational r? · q3
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.

q3 i? Course major influences the predictive effect on AI adoption among Gen Z university students. → Mohd Shafie Rosli 2026

Evidence

Mohd Shafie Rosli 2026

Mohd Shafie Rosli, Nor Shela Saleh, Azlah Md. Ali, Suaibah Abu Bakar. (2026). Exploring the Factors Influencing Artificial Intelligence Adoption among Gen Z University Students: the Role of Self-Efficacy and Perceived Trust. Journal for STEM Education Research. https://doi.org/10.1007/s41979-025-00171-2

q3 · i? · associational · r?

Multigroup analysis across course major clusters (162 non-engineering, 187 engineering students) found that course major "influences the predictive effect" in the extended UTAUT model. No specific path differences or statistics for the major comparison are printed in the provided text.

"Additionally, the course major also influences the predictive effect."

Discussion

Page metadata
Field Value
type claim
id course-major-moderates-gen-z-ai-adoption
title Course major moderates the predictive effects on Gen Z students' AI adoption
description Course major moderates the predictive effects on Gen Z students' AI adoption
status review
evidence_strength moderate
newest_evidence 2026
generated by process:wiki-ingest on 2026-10-15
trust unverified — no one has confirmed this page's content
sources 1 — mohd-shafie-rosli-2026

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