Exploratory stage-of-study analyses: undergraduate year level is positively associated with AI-related disengagement, and the GPA-band pattern is stronger in postgraduate/research students for active engagement and perceived learning impact¶

Claim · All claims
Evidence · 1 study (2 entries) · associational r1 · q2 · i1 small
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i1 Within undergraduates, year level correlated positively with AI-related disengagement (ρ = 0.170, p = 0.007), with no comparable associations for the other indices. → Jason Zagami 2026 q2 i? Exploratory interaction models showed the GPA slope was significantly stronger in postgraduate/research students for active AI engagement (p = .001) and perceived positive learning impact (p = .002); no significant interaction for positive affect. → Jason Zagami 2026 (2)

Evidence¶

Jason Zagami 2026¶

Jason Zagami. (2026). Guarded adoption of generative AI in higher education: high-achieving students, successful-student identity, and epistemic agency in a single-university mixed-methods survey. International Journal of Educational Technology in Higher Education 23:47. https://doi.org/10.1186/s41239-026-00625-6

q2 · i1 · associational · r1

Exploratory undergraduate year-level analysis (Table 4, ρ = 0.170, p = 0.007). The article presents this as modest, suggesting later-year undergraduates may become somewhat more likely to report dependency-prone AI use.

"Within the undergraduate cohort, year level showed a positive association with AI-related disengagement, as shown in Table 4. No comparable year-level associations were observed for active engagement, positive affect, negative affect, or perceived positive learning impact."

Jason Zagami 2026 (2)¶

Jason Zagami. (2026). Guarded adoption of generative AI in higher education: high-achieving students, successful-student identity, and epistemic agency in a single-university mixed-methods survey. International Journal of Educational Technology in Higher Education 23:47. https://doi.org/10.1186/s41239-026-00625-6

q2 · i? · associational · r1

Exploratory GPA-by-cohort interaction models comparing undergraduate and postgraduate/research cohorts (Table 5 shows cohort-specific correlations, e.g. perceived learning impact ρ = −0.515 postgraduate vs −0.318 undergraduate). Only p values are printed for the interactions.

"Exploratory interaction models suggested that the GPA slope was significantly stronger in postgraduate or research students for active AI engagement ( p = .001) and perceived positive learning impact ( p = .002). No significant interaction was observed for positive affect."

Discussion¶

Related Claims¶

• GPA band remains a significant negative predictor of active AI engagement, positive affect, perceived learning impact, and AI-related disengagement when controlling for age, gender, and year category — related
• High-achieving students less often endorse AI-supported autonomy, effective learning, and active engagement, and more often agree that reliance on AI hinders critical thinking and independent problem solving — related
• Exploratory multi-group analyses suggest competence-related paths differ by educational level and gender, with heterogeneity concentrated downstream of intention — related