Dialogic competence is a prerequisite for meaningful engagement with LLM-based chatbots¶

Claim · All claims
Evidence · 1 study · design r3 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Across the cycles, students struggled to initiate and sustain purposeful interactions with the chatbot, revealing a gap in AI literacy beyond technical familiarity that the authors call dialogic competence. → Hilliger 2026

Evidence¶

Hilliger 2026¶

Hilliger, I., Pérez-Sanagustín, M., González, C., Villalobos, E. and Celis, S. (2026). A GAI-Based Chatbot for Scaffolding Self-Regulated Learning: Insights from a Design-Based Research Approach. Journal of Learning Analytics, 13(1), 74–88. https://doi.org/10.18608/jla.2026.9143

q2 · i? · design · r3

Authors' interpretation from the broad evaluation of qualitative data across three design cycles. The study suggests explicit instruction in prompting, goal-setting, and reflective questioning is essential to unlock AI-supported reflection.

"What is particularly novel in this work is the identification of dialogic competence as a prerequisite for meaningful engagement with LLMs. Students struggled to initiate and sustain purposeful interactions"

Discussion¶

Related Claims¶

• Chatbot engagement was highly uneven: 8 of 15 voluntary users interacted continuously while 7 interacted superficially — related
• Students primarily used the Socratic-tutor chatbot as a study aid aligned with existing study habits rather than for the intended Socratic reflection — related
• Telegram-based chatbot use declined after initial novelty, with platform friction cited as a barrier — related
• A student-facing chatbot was pulled after it reinforced a student's self-deprecating views about math, illustrating substantial risk of direct AI engagement with students — related
• Pilot engagement was strong with month-over-month user retention, and teachers used the AI primarily for consumption rather than creation — related
• Meaningful engagement with AI as a co-regulatory partner is more likely from middle childhood onwards — related
• Course design created frictions: undeclared programming prerequisites, copied AI-generated tutorial solutions, intimidating blackboard turns, and AI-guessing cycles for students lacking evaluation knowledge — related
• Chatbot usage analytics show substantial after-hours demand, with 36.8% of interactions occurring outside standard working hours — related
• Students dynamically switched between Socratic Inquiry and Transactional Delegation as deadlines approached and task novelty changed (the Strategic Dance) — a narrower finding that bears on this claim
• Iterative prompt refinement shifted a generative-AI tutor from tutorial-style explanation delivery toward dialogic Socratic support for K-12 beginners — related
• Qualitatively, Socratic prompts supported reflective monitoring while directive feedback was associated with overload and resistance — related