Greater prior AI learning experience and female gender predicted upward motivational profile transitions¶

Claim · All claims
Evidence · 1 study (2 entries) · associational r3 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Among initially Disengaged students, those with greater prior AI learning experience were more likely to transition to higher motivational profiles. → Liang 2026 q2 i? Female students in the Developing profile were more likely than male students to transition to the Self-Determined profile. → Liang 2026 (2)

Evidence¶

Liang 2026¶

Liang, S., Yau, K. W., Meng, H., Chiu, T. K. F., King, I., Yam, Y., & Chai, C. S. (2026). From disengaged to self-determined: A latent transition analysis of students' AI learning motivation. Education and Information Technologies. https://doi.org/10.1007/s10639-026-13998-y

q2 · i? · associational · r3

Conditional LTA models regressed transition paths on gender, grade level, and prior AI learning experience (Table 8). The quote reports the prior-experience effect; Table 8 shows a coefficient of −0.50* (p <.05) for the Disengaged no-transition path, with gender dummy coded Male = 0, Female = 1.

"Among students initially classified as Disengaged, those with greater prior AI learning experience were more likely to transition to the Developing and Self-Determined profiles."

Liang 2026 (2)¶

Liang, S., Yau, K. W., Meng, H., Chiu, T. K. F., King, I., Yam, Y., & Chai, C. S. (2026). From disengaged to self-determined: A latent transition analysis of students' AI learning motivation. Education and Information Technologies. https://doi.org/10.1007/s10639-026-13998-y

q2 · i? · associational · r3

Conditional LTA with demographic predictors of transition paths (Table 8). The quote reports the gender contrast between female and male students in the Developing profile; the article reports a coefficient of 0.39 for the Developing-to-Self-Determined path in Table 8 (p <.05 threshold indicated).

"In addition, female students in the Developing profile were more likely than male students to transition to the Self-Determined profile."

Discussion¶

Learner Variables¶

• Gender — predictor: outcomes differ by group: a gap reflecting circumstances and treatment, not a cause

Related Claims¶

• Students who transitioned into or remained in the Self-Determined profile showed the greatest improvements in AI literacy — related
• Secondary students in AI learning fall into three distinct SDT-based motivational profiles — Disengaged, Developing, and Self-Determined — at both pre- and post-test — related
• During a year-long AI curriculum, most students maintained or moved upward in motivational profile, with substantial upward transitions out of the Disengaged profile — related
• Female gender, higher autonomous motivation, lower prior knowledge, and higher final course grades each predict more frequent voluntary StatBot use among graduate statistics students — related
• Higher self-rated Japanese proficiency, more frequent AI use, and prior AI-related training predicted membership in the positive versus maladaptive adaptation profile at Time 1 — related