Perceived usefulness, attitude, and behavioral intention form a significant TAM pathway predicting GenAI adoption among law students¶

Claim · All claims
Evidence · 1 study (2 entries) · causal r2 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person
Design limits · Haifang Liu 2026: no comparison group · Haifang Liu 2026 (2): no comparison group (read from the study by two models, 2026-10-29)

Subclaims¶

q2 i? Perceived usefulness strongly predicted attitude toward use (β = .52, t = 7.84, p < .001), attitude predicted behavioral intention (β = .61, t = 9.15, p < .001), and behavioral intention predicted actual use (β = .58, t = 8.32, p < .001). → Haifang Liu 2026 q2 i? The model explained 59% of variance in behavioral intention and 68% in legal reasoning ability. → Haifang Liu 2026 (2)

Evidence¶

Haifang Liu 2026¶

Haifang Liu. (2026). AI-enhanced legal pedagogy: a case study of generative AI integration in property law courses. Education Tech Research Dev. https://doi.org/10.1007/s11423-026-10698-9

q2 · i? · causal · r2

PLS-SEM on the full sample of 180 participants using SmartPLS 4.0 with 5000 bootstrap resamples; the article prints path coefficients and t-values but no standardized effect sizes for individual paths, so impact is null.

"perceived usefulness strongly predicted attitude toward use (H2: β = .52, t = 7.84, p < .001), while attitude significantly influenced behavioral intention (H4: β = .61, t = 9.15, p < .001). Behavioral intention strongly predicted actual usage (H8: β = .58, t = 8.32, p < .001)"

Haifang Liu 2026 (2)¶

Haifang Liu. (2026). AI-enhanced legal pedagogy: a case study of generative AI integration in property law courses. Education Tech Research Dev. https://doi.org/10.1007/s11423-026-10698-9

q2 · i? · causal · r2

Variance-explained and fit indices from the same SEM; R2 values are variance explained from a path model, which the coding rules treat as not a standardized effect size, so impact is null.

"The model explained substantial variance in endogenous constructs: 52% in attitude toward use, 59% in behavioral intention, and 68% in legal reasoning ability. Model fit indices demonstrated excellent alignment with observed data (SRMR = .062, NFI = .91, CFI = .94)"

Discussion¶

Related Claims¶

• GenAI-enhanced instruction is associated with substantially greater legal reasoning gains than traditional instruction in property law, though the effect size warrants cautious interpretation — related
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