Academic Journal
Contemporary educational methods in periodontology.
| Title: | Contemporary educational methods in periodontology. |
|---|---|
| Authors: | Preshaw, Philip M., Ramseier, Christoph A., Loos, Bruno G., Balčiūnaitė, Aušra, Crnić, Tin, Davey, Kevin, Dommisch, Henrik, Ettmayer, Johanna B., Roberts, Anthony, Verheijck, E. Etienne, Walter, Clemens, Zappalà, Graziano |
| Source: | Journal of Clinical Periodontology; Nov2024 Supplement 27, Vol. 51, p117-192, 76p |
| Subject Terms: | Digital technology, Medical information storage & retrieval systems, Graduate education, Dental education, Grey literature, Course evaluation (Education), Undergraduate programs, Artificial intelligence, Teaching methods, Confidence, Descriptive statistics, Systematic reviews, MEDLINE, Simulation methods in education, Virtual reality, Periodontics, Medical databases, Professional employee training, Online education, Learning strategies, Online information services, Student attitudes, Continuing education, Communication education, Quality assurance, COVID-19 pandemic |
| Abstract: | Aim: The 1st European Workshop on Periodontal Education in 2009 made recommendations regarding the scope of periodontal education at undergraduate (UG), postgraduate (PG) and continuing professional development (CPD) levels, defining competencies and learning outcomes that were instrumental at the time in helping to define periodontal teaching curricula. The 19th European Workshop on Periodontology and 2nd European Consensus Workshop on Education in Periodontology (Education in Periodontology in Europe) was held in 2023 to identify changes and future developments in periodontal education (including those informed by the COVID‐19 pandemic) and embracing methods and formats of periodontal teaching and training. The aim of this review was to assess current knowledge regarding education methods in periodontology, including traditional face‐to‐face (F2F) teaching and the move to student‐centred methods, virtual learning methods and use of digital technology, as well as blended teaching and learning (including teaching delivery and assessment) at UG, PG and CPD levels. Materials and Methods: Systematic searches were conducted to identify relevant studies from the literature. Data were extracted and descriptive summaries collated. Results: The pandemic was a major disruptor of traditional F2F teaching but provided opportunities for rapid implementation of alternative and supplementary teaching methods. Although online learning has become an integral part of periodontal education, teachers and learners alike favour some form of F2F teaching. Blended teaching and learning are feasible in many areas of periodontal education, both for knowledge and skills acquisition as well as in assessment. Student‐centred methods and blended approaches such as the flipped classroom seem highly effective, and online/virtual classrooms with both synchronous and asynchronous lectures are highly valued. Learning with haptic methods and virtual reality (VR) enhances the educational experience, especially when VR is integrated with traditional methods. The quality of the teacher continues to be decisive for the best knowledge transfer in all its forms. Conclusions: Live F2F teaching continues to be highly trusted; however, all types of student‐centred and interactive forms of knowledge transfer are embraced as enhancements. While digital methods offer innovation in education, blended approaches integrating both virtual and traditional methods appear optimal to maximize the achievement of learning outcomes. All areas of periodontal education (UG, PG and CPD) can benefit from such approaches; however, more research is needed to evaluate their benefits, both for knowledge transfer and skills development, as well as in assessment. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Clinical Periodontology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Complementary Index |
Be the first to leave a comment!