Date
Publisher
arXiv
Effective study strategies fail when preparatory tasks consume learning time. While AI educational tools demonstrate efficacy, understanding how they align with self-regulation needs in authentic study contexts remains limited. We conducted formative design research using an AI flashcard prototype, employing large language models to generate design hypotheses, which were validated through researcher walkthroughs and student sessions. Six students across disciplines completed sessions combining interviews and think-aloud tasks with their materials. Analysis revealed that students value automation for addressing the overwhelming preparation burden, yet require transparent, editable AI outputs to maintain cognitive ownership, which is essential for self-regulation. They conceptualized AI as a collaborative partner demanding verifiable reasoning rather than an autonomous agent. Metacognitive scaffolding was endorsed when clarifying study direction without constraining choice. Motivational features produced divergent responses. We derive design principles prioritizing editability and transparency, scaffolding metacognition without prescription, and accommodating motivational diversity. Findings identify conditions under which automation supports versus undermines metacognitive development in self-regulated learning.
Study at a glance
- Question: How do higher education students experience and balance AI automation and agency when using an AI flashcard tool?
- Setting and data: Six undergraduate and graduate students aged 22-31 across multiple disciplines at a southeastern US public university.
- Method: Formative design research with think-aloud tasks, semi-structured interviews, researcher cognitive walkthroughs, and reflexive thematic analysis.
Why it matters
When preparatory study tasks impose high extraneous cognitive load, they prevent deep learning. However, automated AI tools risk reducing learner agency and the active metacognitive engagement needed for self-regulated learning.
Key findings
- Students valued AI automation for lifting the heavy burden of material preparation, which previously led some learners to abandon review entirely.
- Learners required transparent and editable AI-generated content to maintain cognitive ownership, viewing the inability to modify flashcards as a major source of anxiety.
- Students welcomed metacognitive scaffolding that guided study planning without restricting choice, while gamified motivational features produced sharply conflicting reactions.
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