A three-round Delphi process with 36 Hong Kong school teachers reached consensus on 20 ChatGPT-based learning activities that satisfy SDT needs and foster SRL phases.¶

Claim · All claims
Evidence · 1 study · design r3 · q2
Currency · newest study 2024 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? After three Delphi rounds, teacher consensus yielded a classification list of 20 learning activities using ChatGPT linked to SDT needs and SRL phases. → Chiu 2024

Evidence¶

Chiu 2024¶

Chiu, T. K. F. (2024). A classification tool to foster self-regulated learning with generative artificial intelligence by applying self-determination theory: a case of ChatGPT. Education Tech Research Dev, 72, 2401–2416. https://doi.org/10.1007/s11423-024-10366-w

q2 · i? · design · r3

Three-round Delphi survey of Hong Kong school teachers, who refined an initial activity list through qualitative comments and consensus ratings. The results section reports that "the teachers in Hong Kong suggested 20 learning activities using ChatGPT that could satisfy SDT needs to foster SRL in schools."

"The analyses after the three rounds revealed that the teachers in Hong Kong suggested 20 learning activities using ChatGPT that could satisfy SDT needs to foster SRL in schools."

Discussion¶

Related Claims¶

• Most of the 20 ChatGPT learning activities (11 of 20) better satisfy competence, fewer satisfy autonomy, and the fewest satisfy relatedness. — related
• Among the 20 ChatGPT learning activities, performance and self-reflection are each better supported by eight activities, and forethought by four. — related
• Competence is the only SDT need that ChatGPT learning activities satisfy across all three SRL phases; relatedness and autonomy are not adequately satisfied at every phase. — related
• Competence is the strongest independent psychological predictor of AI literacy performance, followed by autonomy; relatedness has no significant independent effect — related