Introduction: Navigating terminology in EMI dental education
As higher education globalizes, more dental students study in English-medium instruction (EMI) outside their home countries. In non-Anglophone settings like Malaysia, students from diverse linguistic backgrounds must simultaneously master complex dental terminology and academic English. This dual demand can create cognitive load that hinders participation and achievement in foundational subjects such as oral anatomy, which requires precise vocabulary for understanding structures, functions, and clinical relevance.
Why AI-assisted terminology support matters
Artificial intelligence tools, particularly those leveraging natural language processing, offer adaptive scaffolding for multilingual learners. ChatGPT can simplify dense terminology, contextualize unfamiliar words, and provide iterative, non-judgmental explanations. When embedded thoughtfully, AI-assisted learning has the potential to reduce extraneous cognitive load, enabling students to focus on core anatomical concepts while building confidence to contribute more actively in class.
The study at a glance
A pilot mixed-methods study explored how ChatGPT supports terminology learning among 35 Chinese international dental students at SEGi University, Malaysia, enrolled in a mandatory oral anatomy course. Participants used ChatGPT twice weekly over eight weeks to clarify terms, explore functions, and compare anatomical structures. The intervention aimed to answer three questions: Does AI-assisted terminology support improve comprehension? How do multilingual students experience ChatGPT in EMI? What ethical considerations emerge from AI use in this context?
Key findings: Strong signals for learning and engagement
Terminology comprehension showed a remarkable increase: average scores rose from 10.4 to 16.1 on a 20-item test (p<0.001), with a large effect size. Engagement, measured with an adapted Utrecht Work Engagement Scale for Students (UWES-S), also improved significantly across vigor, dedication, and absorption. Usage patterns revealed a typical weekly engagement of 2.6 sessions, with most queries (about 45%) centered on clarifying terms, 32% on clinical relevance, and 23% on comparing structures. Qualitative insights from focus groups highlighted enhanced clarity, autonomy, and confidence in class discussions, alongside concerns about accuracy and the need for ongoing ethical guidance.
What drives these gains?
- <strongReduction of extraneous cognitive load: ChatGPT helped learners offload linguistic hurdles so they could concentrate on anatomical concepts.
- <strongAutonomy and motivation: Students described ChatGPT as a private tutor, supporting self-directed learning aligned with Self-Determination Theory.
- <strongStructured yet flexible learning: The tool complemented traditional pedagogy without replacing faculty oversight, addressing the need for both independence and guidance.
Pedagogical and ethical considerations
Even with positive outcomes, the study underscored important cautions. Students noted that AI outputs could be inaccurate or too general at times, underscoring the necessity for faculty oversight, cross-checking, and critical appraisal. Ethical safeguards—such as clear usage guidelines, privacy protections, and non-participatory faculty roles—helped sustain responsible AI engagement. The findings reinforce a hybrid approach: AI-assisted terminology support as a supplement to, not a substitute for, teacher-led instruction and curricular alignment.
Implications for dental education and EMI contexts
For linguistically diverse cohorts—especially in resource-constrained EMI programs—AI tools like ChatGPT can democratize access to disciplinary vocabulary and conceptual frameworks. The study aligns with Cognitive Load Theory (reducing extraneous load) and Self-Determination Theory (supporting autonomy and competence). It also resonates with disciplinary literacy concepts, emphasizing not only vocabulary acquisition but fluency in dental discourse practices. Institutions should invest in AI literacy for both students and faculty, develop ethical guidelines, and explore longitudinal designs to assess sustained impact across terms and courses.
Limitations and avenues for future research
As a pilot without a control group, results should be interpreted cautiously. Future work should incorporate larger, more diverse samples, systematic measurement of prior English proficiency and digital literacy, and longitudinal designs to evaluate long-term outcomes. Investigations into educator perspectives and co-designed AI integration strategies will help scale responsible, equitable adoption in dental and health professions education.
Conclusion
ChatGPT-enabled terminology learning shows promise for multilingual EMI dental programs, enabling clearer understanding of oral anatomy terms, greater student engagement, and more autonomous study. When guided by ethical safeguards and integrated with faculty oversight, AI can be a powerful ally in advancing equitable, effective health professions education.
