In the context of this study, the 2nd and 3rd grade undergraduate students in Medipol University, Department of Physiotherapy and Rehabilitation, will taken into an education program to increase and assess their theoretical knowledge level, clinical decision-making skills and attitudes towards interactive learning with artificial intelligence by applying the ChatGPT-supported PBL module and the results will be compared with traditional teaching methods.
In recent years, the use of artificial intelligence-based applications in the field of health education has been rapidly increasing; especially large language models such as ChatGPT have attracted attention in terms of providing rapid access to information and individualized learning opportunities. Utilizing this potential of artificial intelligence, especially in active learning methods such as problem-based learning (PBL), is seen as an approach that can strengthen student-centered education. It is reported in the literature that ChatGPT-supported learning applications yield positive results in medical education, increase theoretical success and provide significant improvements in clinical skills. However, applications specific to physiotherapy education are still limited in this regard. Physiotherapy education requires students to have not only theoretical knowledge but also versatile skills such as clinical decision-making, problem-solving, and patient communication. Therefore, it is important to systematically investigate the effect of ChatGPT-supported PBL applications on student performance and satisfaction. Professionals should be able to benefit from these systems when they do not know where to start in a different case, and students should be informed about this issue by academicians who are experts in their fields in the university environment. In order to prevent the misuse of these systems, it is thought that academicians should not avoid technology and should benefit from the interactive course processing and correct communication opportunities that these systems can create with patients. Today, teaching students how to use technology instead of telling them not to use it is very important for academic success. In this context, the aim of this study is to evaluate the student's theoretical knowledge level, clinical decision-making skills and attitudes towards interactive learning with artificial intelligence and compare them with traditional teaching methods by applying the ChatGPT-supported PBL module to volunteer groups consisting of undergraduate students of Istanbul Medipol University, Department of Physiotherapy and Rehabilitation.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
OTHER
Masking
DOUBLE
Enrollment
40
This direct involvement of AI and educators aims to improve learning outcomes by leveraging the scalability of AI and the expertise of educators. The question sets created by students and the answers obtained from ChatGPT are discussed within the group and prepared for class presentation, and the instructor provides feedback on accuracy, timeliness, and scientific relevance. This process aims to support students' participation as active questioners and analyzers, rather than passive consumers of information. Intervention will last for 2 weeks, 2 hours of courses each week, in total 4 hours of education will be given. First 2 hours will be the usage parameters and the knowledge about the ChatGPT system and the 2nd week's 2 hours of education will include the presentations and interactive discussion about the case.
The first session will be given by an independent/different instructor about the definition, reasons, evaluation and the treatment of low back pain for 2 hours. Afterwards the students will be informed about the content of the next week's interactive course and supplied with the study sources like book, articles by the other lecturer. A week will be given to the students to study and the other week they will meet with the lecturer to discuss over a specific case. At the beginning and end of the courses, outcome measures will taken from the both groups.
Medipol University İstanbul
Istanbul, Kavacık Beykoz, Turkey (Türkiye)
RECRUITINGTheoretical knowledge test
A 20-question multiple choice exam will be administered at the beginning of the study after the initial theoretical LBP course and at the end of the 2nd week of training, in total 3 times. With this way, distinguishing the effect of the lecturer's initial education and student's own studies and research will be possible at the analysis. The exams will be compared between groups to assess the intervention effect. The maximum score for the exam will be 100, and a score below 80 will be considered a failing grade.
Time frame: 4 weeks
Mini Clinical Evaluation Exam (Mini-CEX)
Participant's history taking, physical assessment and clinical reasoning skills will be observed by an independent assessor using the 9-point Mini-CEX form. Mini-CEX has been widely accepted as an effective and reliable method for assessing clinical skills. It includes student's ability to obtain a patient's history from the patient and family and to perform physical examinations under the guidance of an instructor. The Mini-CEX scoring system uses a nine-point scale and includes seven standards: medical interview skills, physical examination skills, humanistic qualities/professionalism, clinical judgment, counseling skills, organizational efficiency and general clinical competence. The scale ranges from inadequate (1-3 points), satisfactory (4-6 points) to superior (7-9 points). To maintain consistency, all Mini-CEX assessments will be made by a single assessor. The scale is valid and reliable in Turkish.
Time frame: 4 weeks
Student Satisfaction and Attitude Survey
Each student will be asked to complete a self-assessment form, where they evaluate their contributions to the group dynamics and their individual learning process, and a peer-assessment form, where they rate the participation levels of their group mates. Students' satisfaction and the impact of using PBL-ChatGPT on their learning experiences will be assessed with a survey developed from a previous study.
Time frame: 4 weeks
Young Internet Addiction Test
This scale, which is used to determine the internet usage habits of the participants, was developed by Young in 1998. There is also a Turkish version of the short form consisting of 12 items for quick assessment. The psychometric properties of the questionnaire were studied by Kutlu et al. and it is valid and reliable in Turkish. Participants are scored between 12-60, with score 1 indicating never and score 5 indicating always. High scores indicate a high risk of internet addiction.
Time frame: 4 weeks
Adult Reading Motivation Scale
The scale, developed by Schutte and Malouff (2007) to determine adults' reading motivation, consists of 19 items. The scale assesses individuals' reading motivation by asking questions on subheadings such as self, recognition of competence, and reading to be successful in other areas. A score of 1 indicates strongly disagree, a score of 5 indicates strongly agree, and participants receive scores between 19 and 95. High scores indicate high reading motivation and habit. The psychometric properties of the survey were conducted by Yıldız et al. and it is valid and reliable in Turkish.
Time frame: 4 weeks
Artificial Intelligence Self-Efficacy Scale
The Artificial Intelligence Self-Efficacy Scale (AISES) will be used to measure participants' perceptions of competence in using artificial intelligence technologies. The scale was developed by Wang and Chuang (2023) and adapted to Turkish by Uyan and Gültekin (2024) to test its validity and reliability. In the Turkish adaptation study, it was confirmed that the scale consisted of four sub-dimensions (assistance, anthropomorphic interaction, comfort and technological competencies) and contained a total of 21 items. The goodness of fit values were found to be at an acceptable level (CFI=0.887, RMSEA=0.084) and Cronbach's alpha values ranged between 0.708 and 0.782 for the sub-dimensions. The scale to be applied to the participants was structured as a 5-point Likert type (1 = Strongly Disagree, 5 = Strongly Agree).
Time frame: 4 weeks
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