Theory-Guided Socratic AI Scaffolding for Clinical Reasoning in Nursing Students

NCT07838792 | Completed

• 1 other identifier: 202401895B0
• Study Type: interventional
• Target: 127
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this study was to compare two approaches to using generative artificial intelligence (AI) to support clinical reasoning in undergraduate nursing students. The study examined whether a theory-guided Socratic AI scaffold based on Tanner's Clinical Judgment Model could better support clinical reasoning, case-based knowledge, and confidence than the naturalistic use of general-purpose generative AI. Participants were undergraduate nursing students enrolled in a pediatric nursing course. Before the intervention, students' perceived barriers to clinical reasoning were identified and used to inform the theory-guided AI scaffold. Classes were then assigned to either Tanner-Structured Socratic AI Scaffolding or General-Purpose Generative AI. Both groups worked with the same pediatric fever case for the same amount of time. Students in the Tanner-Structured Socratic AI Scaffolding group received step-by-step guidance through Noticing, Interpreting, Responding, and Reflecting using Socratic questions, hints, feedback, and prompts for reflection. Students in the General-Purpose Generative AI group used freely available generative AI tools as they normally would for learning. The study compared the two groups on clinical reasoning performance, case-based knowledge, and confidence in clinical reasoning.

Conditions

Clinical Reasoning in Nursing Education

Keywords

clinical reasoning; nursing education; Generative Artificial Intelligence

Outcome Measures

Primary Outcomes (1)

• Clinical Reasoning Performance

  Clinical reasoning performance was assessed using the Clinical Reasoning Performance Rubric (CRPR), a 15-point criterion-referenced rubric. Participants identified three priority nursing problems, ranked them by urgency, and proposed three evidence-based interventions for each problem. Total scores ranged from 0 to 15, with higher scores indicating better clinical reasoning performance.

  Immediately after the intervention

Secondary Outcomes (2)

• Case-Based Knowledge

  Baseline and immediately after the intervention

• Clinical Reasoning Confidence

  Baseline and immediately after the intervention

Study Arms (2)

Tanner-Structured Socratic AI Scaffolding

EXPERIMENTAL

Participants used a theory-guided AI chatbot structured around Tanner's Clinical Judgment Model. The chatbot guided participants through Noticing, Interpreting, Responding, and Reflecting using Socratic questions, graduated hints, metacognitive prompts, and constructive feedback rather than providing direct answers.

Other: Tanner-Structured Socratic AI Scaffolding

General-Purpose Generative AI

ACTIVE COMPARATOR

Participants used freely accessible general-purpose generative AI tools as they normally would for learning. They formulated their own task-focused queries without a Tanner-structured sequence or standardized Socratic prompts.

Other: General-Purpose Generative AI

Interventions

Tanner-Structured Socratic AI Scaffolding OTHER

Participants used a research-team-developed AI chatbot structured around Tanner's Clinical Judgment Model. The chatbot guided participants sequentially through Noticing, Interpreting, Responding, and Reflecting using Socratic questions, graduated hints, metacognitive prompts, and constructive feedback rather than providing direct answers. The scaffolding was informed by learner-identified barriers to clinical reasoning.

Tanner-Structured Socratic AI Scaffolding

General-Purpose Generative AI OTHER

Participants used freely accessible general-purpose generative AI tools as they normally would for learning. They formulated their own task-focused queries and received no Tanner-structured sequence or standardized Socratic prompts.

General-Purpose Generative AI

Eligibility Criteria

• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

• Undergraduate nursing students enrolled in the required Pediatric Nursing course.
• Completion of core medical-surgical nursing courses.
• No prior practicum experience in specialized pediatric units.

You may not qualify if:

• Students repeating the Pediatric Nursing course.
• Students with prior pediatric specialty rotation experience.

Sponsors & Collaborators

• Chang Gung University of Science and Technology: lead

Study Sites (1)

Chang Gung University of Science and Technology

Taoyuan, Taiwan

Location

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: DOUBLE
• Who Masked: INVESTIGATOR, OUTCOMES ASSESSOR
• Purpose: OTHER
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate Professor

Study Record Dates

• First Submitted: September 18, 2026
• First Posted: September 24, 2026
• Study Start: September 15, 2025
• Primary Completion: February 5, 2026
• Study Completion: February 5, 2026
• Last Updated: September 24, 2026

Record last verified: 2026-09

Data Sharing

• IPD Sharing: Will not share

Locations

TW (1)