Teaching Motivational Interviewing Skills Using Deliberate Practice with Artificial Intelligence Scoring and Feedback

Background/Objectives: We analyzed 6555 written motivational interviewing (MI) skill attempts from 437 second-year dental students to (a) construct an inductive taxonomy of skill-enactment errors, (b) test whether error prevalence decreased after instruction, and (c) determine whether formative-error profiles predicted summative performance. Methods: We used a mixed-methods design. Students responded to patient prompts using specific MI skills (open-ended questions, affirmations, and reflections; 4 per skill) after brief instruction (T1) and during a midterm examination (T2; 3 items). Claude Artificial Intelligence (AI) performed initial coding using a qualitative constant-comparison protocol; the code registry reached saturation at n = 200. Five independent human coders validated the AI-generated codes. Results: Claude AI coded MI skill attempts with high agreement with the gold standard (linearly weighted kappa = 0.93). The two most prevalent (of seven derived) errors at T1 were the fixing reflex (advising or correcting the patient; 79%) and responding to or eliciting sustain talk (75%). All error types decreased significantly by T2 (ps < 0.001). Structural errors (e.g., wrong form) fell below 8%, whereas the fixing reflex (16%) and sustain-talk responding (52%) proved more durable. Latent profile analysis identified three groups: Attuned (64%; hallmark: successful enactment), Misaligned (17%; hallmark: fixing reflex), and Unanchored (18%; hallmark: generic responding). Misaligned students scored significantly lower at T2; Unanchored students matched the Attuned group. Conclusions: Structural errors yield to standard teaching, whereas the fixing reflex and sustain-talk responding require deliberate practice focused on subcomponents of affirming and reflecting. AI made it possible to provide individualized, criterion-referenced feedback to 437 students and to systematically code nearly 7000 responses.