The Social Cognitive Model of Technology Integration explains 55% of variation in preservice teachers' technology integration intentions¶

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

Subclaims¶

q2 i? Variables in the Social Cognitive Model of Technology Integration accounted for 55% of variation in preservice teachers' intentions, over twice the variation reported for some other models. → Serkan Perkmen 2026

Evidence¶

Serkan Perkmen 2026¶

Serkan Perkmen, Sara Dexter. (2026). From sources of self-efficacy to technology integration intentions: a new social cognitive model. Educational technology research and development. https://doi.org/10.1007/s11423-026-10623-0

q2 · i? · associational · r2

Path analysis and hierarchical regression with 144 Turkish preservice teachers; hierarchical regression showed self-efficacy and outcome expectations accounted for 50% of intention variance, sources of self-efficacy added 3%, and interests added 2% (R² = 0.55 in the final step).

"Variables in the Social Cognitive Model of Technology Integration accounted for 55% of variation in preservice teachers' intentions to use educational technology in their future classrooms. This is over twice the amount of variation Buabeng-Andoh et al. ( 2019) found could be explained by some other models"

Discussion¶

Related Claims¶

• Outcome expectations have a stronger direct influence on technology integration intentions than self-efficacy, and interests contribute directly — related
• The serial mediation model explains 32.5–37.0% of variance in AI-TPACK, self-efficacy, and AI integration intention — related
• Mastery experiences are the central source of self-efficacy: they strongly predict self-efficacy and uniquely predict intentions when other variables are controlled — related