Date
Publisher
British Journal of Educational Technology
While generative AI (GenAI) tools are emerging as educational resources, general-purpose applications like ChatGPT are not explicitly designed to support the metacognitive and socio-emotional dimensions of learning, often failing to address students' emotional states or promote independent thinking. In response, this study introduces a CVT-SRL GenAI Support Framework integrating control-value theory (CVT) and self-regulated learning (SRL) and tests a learner-centred GenAI chatbot design employing prompt-based SRL scaffolding and emotional support. In a preregistered experiment in an authentic educational setting, 144 high school students were randomly assigned to one of three conditions: (1) ChatGPT, (2) SRLbot (GenAI with SRL scaffolding), (3) emotional SRLbot (GenAI with SRL and emotional support). Outcomes included conceptual knowledge and transfer, trace-based and self-reported engagement in SRL phases (forethought, performance, self-reflection), enjoyment, boredom, hopelessness, self-efficacy and trust. Data were collected at pretest, posttest and 4-week follow-up. Across conditions, students showed improvements in conceptual knowledge and transfer from pretest to posttest, with no significant condition differences in post-to-follow-up change. Both SRLbot and Emotional SRLbot were associated with higher self-reported enjoyment and lower boredom than ChatGPT and elicited trace-based SRL behaviours. Moreover, Emotional SRLbot prompted greater engagement in performance-phase and self-reflection processes than the other conditions. These findings provide preliminary evidence that GenAI agents integrating SRL and emotional scaffolding can support more positive emotional states and task-level SRL behaviours than general-purpose GenAI, highlighting control-value appraisals as a promising target for emotionally supportive SRL design. Future research should explore longitudinal effects on SRL skill development and independent regulation.
Study at a glance
- Question: How does adding self-regulated learning and emotional scaffolding to generative AI chatbots affect high school students' learning and emotions?
- Setting and data: Authentic educational setting, 144 high school students, with data gathered at pretest, posttest, and a 4-week follow-up.
- Method: Preregistered randomized controlled trial comparing three chatbot conditions.
Why it matters
General-purpose generative AI tools are not designed to support metacognitive or socio-emotional learning, often failing to address students' emotions or encourage independent thinking.
Key findings
- Students across all conditions improved in conceptual knowledge and transfer from pretest to posttest, with no significant differences between conditions in post-to-follow-up changes.
- Both SRLbot and Emotional SRLbot were associated with higher reported enjoyment, lower boredom, and more self-regulated learning behaviors than ChatGPT.
- Emotional SRLbot prompted higher student engagement in performance-phase and self-reflection processes than the other two conditions.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
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