# Innovative Approaches to Dental Education: Active Learning for Erosive Tooth Wear Diagnosis in Online and Face-to-Face Settings

## TL;DR

This study shows that active learning improves dental students' ability to diagnose erosive tooth wear, both online and in person.

## Contribution

The study demonstrates that active learning is more effective than lectures for diagnosing erosive tooth wear and works equally well online and in face-to-face settings.

## Key findings

- Active learning groups outperformed lecture-based groups in diagnosing erosive tooth wear.
- Online active learning improved theoretical knowledge more than online lectures.
- Online students reported higher satisfaction and confidence than face-to-face students.

## Abstract

Objective

Active learning has been effective in improving diagnostic skills for dental caries, but its impact on erosive tooth wear (ETW) remains unclear. Additionally, the influence of online education in dentistry is not well understood. This study aimed to evaluate the impact of active learning, in both online and face-to-face (F2F) formats, on dentistry students' knowledge and diagnostic abilities related to ETW.

Method

Four groups of graduating dentistry students received different educational interventions: lecture online (Lon) (n=8), active online (Aon) (n=8), lecture face-to-face (LF2F) (n=14), and active face-to-face (AF2F) (n=14). The lecture covered theoretical knowledge of ETW, including etiology, diagnosis (including the Basic Erosive Wear Examination (BEWE) index), prevention, and treatment. Active learning involved exercises and discussions using clinical photographs for diagnosing ETW with the BEWE index. To assess the effectiveness of the educational intervention, students underwent two types of evaluation: a 12-item test to gauge their theoretical knowledge of ETW (applied pre- and post-intervention) and a 25-item quiz featuring intraoral photographs to evaluate their diagnosis performance (post-intervention). Additionally, the students' self-perception of the activity was assessed (post-intervention). Data analysis was performed by two-way analysis of variance (ANOVA) followed by the Tukey Test (p<0.05).

Results

In terms of theoretical knowledge of ETW, correct-answer rates increased for AF2F (pre: 57.0% → post: 88.5%), LF2F(pre: 54.8% → post: 86.1%), and Aon (pre: 57.2% → post: 79.1%) in the post-intervention test, with no significant differences among them (p<0.05). Lon did not show significant improvement between pre (58.3%) and post (59.3%) tests (p>0.05). Regarding the clinical diagnosis of ETW, active learning groups (Aon: 69.5% and AF2F: 64.7%) outperformed lecture-based approaches (Lon: 47% and LF2F: 47,8%) (p<0.05). Importantly, there was no difference between online and F2Fsettings (p>0.05). Regarding self-perception, students participating in the online setting reported higher overall satisfaction and self-confidence compared with those in the F2F environment (p<0.001). However, no significant differences were observed between the groups when analyzing dissatisfaction levels (p=0.405).

Conclusion

Active learning enhances clinical diagnosis performance for ETW in both online and F2F settings and can improve theoretical understanding in the online context.