Effect of AI Chatbot-Assisted Versus Traditional Case-Based Learning on Clinical Reasoning in Occupational Therapy Students: A Study on Parkinson's Disease (AI-PD-OT25)

Effect of AI Chatbot-Assisted Case-Based Learning on Clinical Reasoning in Occupational Therapy Students: A Post-Test Only Controlled Trial in Parkinson's Disease Education

This study aims to examine whether using an artificial intelligence (AI) chatbot can enhance occupational therapy students' learning during a case-based activity focused on Parkinson's disease. The research compares two groups of students: one using traditional learning materials, and another using both traditional resources and a conversational AI chatbot. Students in both groups work in teams to analyze the same clinical case and propose assessment and treatment strategies for a hypothetical patient. The main purpose of the study is to evaluate whether the AI chatbot helps improve students' performance in three learning domains: cognitive (knowledge and understanding), affective (empathy and attitudes), and psychomotor (planning and action skills). Students' performance is assessed through a structured written examination. The hypothesis is that students who use the AI chatbot will achieve higher scores, especially in the cognitive and psychomotor domains, compared to those who rely on traditional methods only. The study also examines how students interact with the chatbot and whether they use it to support deeper clinical reasoning. By exploring the role of AI in occupational therapy education, this research seeks to inform future teaching strategies and support the thoughtful integration of digital tools in health professions training.

Study Overview

• Status: Completed
• Conditions: Parkinson Disease; Clinical Reasoning; Neurologic Rehabilitation; Occupational Therapy Students
• Intervention / Treatment: Behavioral: AI Chatbot-Assisted Case-Based Learning; Behavioral: Traditional Case-Based Learning with Standard Materials

Detailed Description

This study investigates the impact of an artificial intelligence (AI) chatbot on occupational therapy (OT) students' clinical reasoning skills within the context of neurological rehabilitation, specifically focusing on Parkinson's disease. The study uses a post-test only control group design and adopts a mixed-methods approach to assess educational outcomes across three learning domains: cognitive, affective, and psychomotor.

A total of 25 OT undergraduate students enrolled in a Neurological Rehabilitation course are randomly assigned to one of two groups: (1) Chatbot Group and (2) Classic Group. Both groups receive the same didactic instruction and engage in a small-group, case-based learning session featuring a hypothetical Parkinson's disease case. The Classic Group uses traditional learning resources such as lecture notes and textbooks, while the Chatbot Group additionally interacts with an AI language model simulating a patient. The chatbot allows students to ask open-ended questions to gather occupational history, explore symptoms, and plan interventions.

After the learning task, all students complete a six-item written exam assessing their performance in the cognitive, affective, and psychomotor domains. Two independent raters, blinded to group assignment, evaluate student responses using a predefined rubric. Inter-rater reliability is calculated. To account for possible differences in baseline academic performance, Grade Point Average (GPA) is used as a covariate in the statistical analysis.

The study also includes a qualitative component in which students in the Chatbot Group submit the queries they posed during the interaction. These queries are analyzed inductively using a content analysis approach to explore how students engage with AI support-whether for conceptual clarification, procedural guidance, or ethical reasoning.

This research addresses a growing interest in how AI-based tools may enhance, supplement, or potentially limit professional training in occupational therapy. Although AI chatbots may offer convenient access to information and support student creativity, concerns remain about their effectiveness in fostering reflective and ethical clinical reasoning. By analyzing both performance data and interaction patterns, this study aims to offer evidence-based insights into the role of digital tools in OT education.

• Study Type: Interventional
• Enrollment (Actual): 25
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Turkey
  • Çankırı, Turkey, 14100
    • Faculty of Health Sciences

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

• Currently enrolled as an undergraduate student in an occupational therapy program
• Registered in the "Neurological Rehabilitation" course during the study semester
• Aged between 20 and 23 years
• Provided written informed consent to participate in the study

Exclusion Criteria:

• Previously completed the "Neurological Rehabilitation" course in a prior semester
• Refused or failed to provide informed consent
• Participated in a similar case-based learning study within the past 6 months

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Other
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: AI Chatbot-Assisted Case-Based Learning; Participants in this arm completed a Parkinson's disease case analysis using an AI chatbot designed to simulate interaction with a virtual client. The chatbot provided real-time, natural language responses to student queries. Students worked in small groups to develop problem lists, goals, and intervention plans based on the simulated interaction.	Behavioral: AI Chatbot-Assisted Case-Based Learning; Participants in this intervention used a conversational AI chatbot integrated into a case-based learning activity focused on Parkinson's disease. The chatbot simulated a virtual client and responded to student questions in natural language. Students used the chatbot to gather occupational history, clarify symptoms, and explore intervention planning options during a structured 90-minute session.
Active Comparator: Traditional Case-Based Learning; Participants in this arm completed the same Parkinson's disease case analysis using traditional learning resources, such as lecture notes and textbooks. They worked in small groups to develop problem lists, goals, and intervention plans without access to the AI chatbot or any digital simulation tool.	Behavioral: Traditional Case-Based Learning with Standard Materials; Participants in this intervention completed the same Parkinson's disease case analysis using only traditional educational materials, such as lecture notes, textbooks, and class handouts. No digital or AI-based tool was used. The session was instructor-guided and lasted 90 minutes, during which students worked collaboratively to assess the case and develop intervention plans.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Total Post-Test Score (0-24 points)	The total score on a six-item written examination measuring clinical reasoning performance in occupational therapy students. The test includes items covering cognitive, affective, and psychomotor domains. Each item is scored by two independent, blinded raters. The total possible score is 24 points. Higher scores indicate better clinical reasoning performance.	Immediately after the intervention (within the same session)

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Cognitive Domain Score (0-8 points)	Subscore from the written examination assessing knowledge and understanding of clinical reasoning in occupational therapy. Scored by two blinded raters. Higher scores indicate better performance in the cognitive domain.	Immediately after the intervention
Affective Domain Score (0-8 points)	Subscore from the written examination evaluating empathy, professional attitude, and reflective thinking in clinical reasoning. Scored by two blinded raters. Higher scores reflect stronger affective learning outcomes.	Immediately after the intervention
Psychomotor Domain Score (0-8 points)	Subscore from the written examination assessing planning and implementation of occupational therapy interventions. Scored by two blinded raters. Higher scores indicate better applied reasoning and intervention planning.	Immediately after the intervention

Collaborators and Investigators

• Sponsor: Ceyhun Türkmen

Publications and helpful links

General Publications

• Veltkamp DMJ, Nijhoff MF, van den Broek DAJ, Buntinx M, Kers J, Engelse MA, Huurman VAL, Roelen DL, Heidt S, Alwayn IPJ, de Koning EJP, de Vries APJ. Chronic Pancreas Allograft Rejection Followed by Successful HLA-Incompatible Islet Alloautotransplantation: A Novel Strategy? Transpl Int. 2023 Aug 24;36:11505. doi: 10.3389/ti.2023.11505. eCollection 2023.

Study record dates

Study Major Dates

• Study Start (Actual): July 1, 2025
• Primary Completion (Actual): July 2, 2025
• Study Completion (Actual): July 3, 2025

Study Registration Dates

• First Submitted: June 22, 2025
• First Submitted That Met QC Criteria: June 22, 2025
• First Posted (Actual): July 1, 2025

Study Record Updates

• Last Update Posted (Estimated): July 8, 2025
• Last Update Submitted That Met QC Criteria: July 3, 2025
• Last Verified: July 1, 2025

More Information

Terms related to this study

• Keywords: Parkinson Disease; Artificial Intelligence; Chatbot; Clinical Reasoning; Occupational Therapy Education; Case-Based Learning
• Additional Relevant MeSH Terms: Synucleinopathies; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Neurodegenerative Diseases; Movement Disorders; Parkinsonian Disorders; Basal Ganglia Diseases; Parkinson Disease
• Other Study ID Numbers: F109843008AF4827

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Individual participant data will not be shared due to the educational context of the study, the small sample size, and institutional privacy policies. The data were collected solely for internal academic evaluation and are not intended for secondary use.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No