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Clinical procedural skills training is a cornerstone of preclinical education for dental students. While technological aids such as virtual reality and simulators are increasingly integrated into training, direct instructor guidance remains fundamental to skill development. Artificial intelligence（AI）， as an emerging technology, is now gradually being adopted in medical education. This medical education trial, aimed at evaluating the potential of artificial intelligence in dental education, seeks to address two key questions: 1) Can AI assistance enhance the skill performance of dental students? 2) How can AI be effectively integrated into modern medical education? Researchers will compare the effects of AI and video-based instruction on skill acquisition, assessing differences in skill performance outcomes. Participants will engage in skill acquisition using either AI or video-based instruction over a one-week period.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Artificial intelligence-assisted learning group | Experimental | After completing theoretical knowledge learning, students can use artificial intelligence for skills learning. AI provides steps for specific skill operations, points to note, as well as the desired performance and potential consequences of the operations. |
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| Control group | Active Comparator | This group is provided with detailed videos of specific clinical procedures, recorded by experienced physicians and educators, which demonstrate proper techniques and expected outcomes. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Artificial intelligence | Other | Incorporating artificial intelligence as an aid to video-based skill learning |
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| Measure | Description | Time Frame |
|---|---|---|
| Operational test scores | Operational testing is a common method used to measure participants' proficiency in skill operation. At the conclusion of the experiment, participants completed a 15-minute operational test in a desktop VR environment. Scores were automatically calculated by the VR system, ensuring objectivity in the results. | through study completion, an average 1 week |
| spatial ability | Spatial ability, also known as visual-spatial ability (VSA) encompasses critical cognitive functions that enable individuals to understand, interpret, and manipulate spatially related information. The Purdue Spatial Visualization Test: Rotations (PSVT: R) - served as the measurement tool for analyzing subjects' mental rotation skills. This standardized evaluation contains 30 items that measure how effectively individuals can manipulate imagined three-dimensional figures. Each question includes an example and five choices, with only one being correct. Participants were tasked to rotate the given figure mentally in a similar manner as it was rotated in the example and to select the appropriate choice. | Baseline |
| cognitive load | Cognitive load refers to the resources required by working memory for a particular task. Eye-tracking technology has gained increasing popularity in investigating learners' visual attention distribution and cognitive load. As one of the key indicators, pupil diameter has been used to measure cognitive load during learning. In this study, we used eye-tracking devices to record the pupil diameter of participants during learning to quantify cognitive load. | through study completion, an average 1 week |
| Measure | Description | Time Frame |
|---|---|---|
| learning motivation | Motivation is a motivational tendency guiding and sustaining a student's learning behavior toward specific academic goals.This study employed questionnaires to measure it. The questionnaire contains five items focusing on the motivation domain . Each item was coded according to a five-point Likert rating scale (1 = "strongly disagree", 2 = "disagree", 3 = "neutral", 4 = "agree", 5 = "strongly agree"). |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Yang Dong, PhD | State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University | Study Chair |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| School & Hospital of Stomatology, Wuhan University | Wuhan | Hubei | 430079 | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 40424023 | Derived | Huang S, Wen C, Bai X, Li S, Wang S, Wang X, Yang D. Exploring the Application Capability of ChatGPT as an Instructor in Skills Education for Dental Medical Students: Randomized Controlled Trial. J Med Internet Res. 2025 May 27;27:e68538. doi: 10.2196/68538. |
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| ID | Term |
|---|---|
| D001185 | Artificial Intelligence |
| D014743 | Videotape Recording |
| ID | Term |
|---|---|
| D000465 | Algorithms |
| D055641 | Mathematical Concepts |
| D013637 | Tape Recording |
| D001296 | Audiovisual Aids |
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| Video | Other | Skill learning solely through videos |
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| through study completion, an average 1 week |
| self-efficacy | Self-efficacy, a concept first developed by Bandura, refers to people's subjective judgments regarding their ability to successfully perform an achievement behavior. The questionnaire contains five items focusing on the motivation domain . Each item was coded according to a five-point Likert rating scale (1 = "strongly disagree", 2 = "disagree", 3 = "neutral", 4 = "agree", 5 = "strongly agree"). | through study completion, an average 1 week |
| D018961 |
| Educational Technology |
| D013672 | Technology |
| D013676 | Technology, Industry, and Agriculture |
| D013690 | Television |