ARCS motivation showed the strongest correlations in the matrix with both behavioral intention and use behavior¶

Claim · All claims
Evidence · 1 study · associational r2 · q2 · i3 large
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i3 ARCS motivation correlated more strongly with intention and use (r ≈ 0.61–0.68) than UTAUT3 predictors did (r ≈ 0.49–0.63). → Xin Tian 2026

Evidence¶

Xin Tian 2026¶

Xin Tian, Musa Adekunle Ayanwale, Rethabile Rosemary Molefi, Preeti Manchanda, Nurgün Gençel and Barakat Olabisi Ogunjoun. (2026). Decoding symmetric and asymmetric pathways in generative AI learning adoption: a multi-method study. International Journal of Educational Technology in Higher Education. https://doi.org/10.1186/s41239-026-00613-w

q2 · i3 · associational · r2

Preliminary correlational analysis (Table 2) of the 842-respondent Lesotho survey; all correlations were positive and significant (p < 0.01), with UTAUT3 predictors correlating at r ≈ 0.49–0.59 with intention and r ≈ 0.52–0.63 with use behavior.

"ARCS motivation displayed the strongest correlations in the matrix (r ≈ 0.61–0.68), indicating a particularly close association between motivational experience and both intention and enacted use"

Discussion¶

Related Claims¶

• Instruction should present the learning task as engaging and meaningful and promote positive expectations of success, because effort requires that learners value the task and believe they can succeed — the general claim this finding bears on, with the studies behind it
• ARCS motivation did not significantly moderate any of the tested UTAUT3 acceptance pathways — related
• ARCS motivation did not significantly predict behavioral intention but exerted a strong direct effect on use behavior, dominating its explanation — related
• Attitude, facilitating conditions, and social influence correlate most strongly with behavioral intention, while perceived ease of use correlates weakest — related
• Effort expectancy and facilitating conditions negatively predict behavioral intention, contradicting conventional UTAUT assumptions in studio-based creative education — related
• Performance expectancy, effort expectancy, social influence and facilitating conditions predict vocational students' LMS acceptance, with performance expectancy the most influential — related
• Hedonic motivation and habit were the strongest predictors of behavioral intention, and habit also substantially predicted use behavior — reports the opposite