Learner Engagement and Teaching Effectiveness in CME Case Study

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Study Purpose and Design

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The aim of the research was to examine the connection between effective instruction and student participation in live, in-person continuing medical education (CME). This is a relevant issue in light of the need to provide the best possible learning outcomes and the increasing trend of online modalities in the wake of the COVID-19 pandemic.

Strengths

This study investigates a current topic in medical education and provides enlightening perspectives on the effectiveness of live-streamed CME (Continuing Medical Education) programmes (Stephenson et al., 2022). In order to assess the level of efficacy and engagement, the research employs the Learner Engagement Inventory (LEI) and the CME Teaching efficacy (CMETE) as complete measures, offering a multidimensional perspective. The study by Bharath, Balamuralidhara, and Gowrav (2021) looks into a number of topics, such as comparing live-streamed and in-person modalities and examining presentation-related topics like using audience response systems (ARS), creating pre- and post-tests, and planning presentations for different times of the day. The comprehensive approach indicated earlier provides a comprehensive viewpoint.

Method

The paper's methodology provides a thorough understanding of how teaching approaches are changing, particularly in light of the COVID-19 pandemic. The study's use of a non-randomized cohort design allows it to capture changes over time. Although the study's credibility is enhanced by the inclusion of well-respected tools such as the LEI and CMETE, significant reliance on self-reported measures may add bias or subjectivity (Stephenson et al., 2022). The method of data analysis is praiseworthy, particularly the use of non-parametric tests in cases of skewed data. However, there is a chance that the outcomes will be impacted by possible problems like how to handle missing data and the impact of confounding variables like the learners' mental state during the epidemic. Furthermore, the details of informed consent are still unclear even when ethical factors like IRB approval have been taken into account. All things considered, the study is topical and pertinent, but careful interpretation of its results is required due to its inherent design limitations. The study of Stephenson et al (2020), also depicted the same types of prospectus as this research process. 

Limitations and Areas of Concern

The present study acknowledges the potential occurrence of survey fatigue and its consequential impact on the results, as a result of participants being required to complete the LEI and CMETE following each presentation.

The study exhibits a low response rate, perhaps constraining its ability to be generalised. Self-selection bias may contribute to the observed discrepancies between live-streamed and in-person sessions, since learners who choose live-streaming may possess innate characteristics that distinguish them from those who choose in-person sessions. The utilisation of Audience Response Systems (ARS) as an evaluative instrument in the field of medicine presents several limitations, particularly when questions are introduced prior to the delivery of relevant content (Stephenson et al., 2022). Although most studies yielded statistical significance, the absolute differences observed were frequently of a diminutive nature, indicating that their practical educational implications may be constrained.

Implications

There are a number of fascinating implications from the new study on the relationship between learner engagement and teaching efficacy in live-streamed Continuing Medical Education (CME), especially for the fields of e-learning and medical education.

Furthermore, the research confirms the notion that interaction does not always equate to engagement. It stands to reason that learners would be more engaged in an interactive learning environment. The results of the investigation cast doubt on this assumption, though. The amount of presentation views or the use of audience response systems (ARS) are two examples of metrics that did not clearly correspond with increased student engagement or enhanced teaching effectiveness (Stephenson et al., 2022). This realisation is crucial for e-learning platforms and teachers who could otherwise spend a lot of money on interactive tools under the mistaken assumption that doing so will improve student learning. It emphasises how important it is to understand more about what, exactly, makes for meaningful interaction in the context of digital learning.

On the contrary, there appears to be a discrepancy between the results and earlier research. Conventionally, it is expected that perceived student engagement and medical knowledge are directly correlated; the more engaged a learner is, the better they understand the subject. However, our study shows that this pattern is not followed. Particularly when it comes to live-streamed CME, the fact that learner involvement was regarded differently than medical knowledge indicates a gap in our understanding. As per the research paper of Janice Bain Sibley (2022), suggests that live-streamed CME may have special dynamics that are still being investigated. It highlights how important it is to conduct a more focused study in this area to make sure the subtleties of live-streamed medical education are not missed. Further, the research provides Practical Recommendations in addition to Theory. The study offers practical insights for medical educators and organisations who are adopting or switching to digital learning approaches. It raises questions about the possible benefits of engagement-boosting technologies like ARS and instructional techniques like the pre/post-test structure. Even while interaction may not ensure engagement by itself, some tools and techniques may be essential to maximising the learning process in a live-streamed environment.

The live-streamed CME study serves as a helpful reminder of how complex the digital learning environment is (Stephenson et al., 2022). It is critical that they continuously review and improve our tactics as the field of online education develops to make sure they are supported by data and adapted to the changing demands of students.

Conclusion

In conclusion, the research offers a crucial analysis of the shift in instructional approaches, especially in light of the COVID-19 epidemic. The study's dedication to thorough research is highlighted by the application of reputable instruments and a thorough methodological approach. The technique used provides a solid basis for comprehending learner engagement and the efficacy of instruction in both live-streamed and in-person settings, but because self-reported measures may contain biases, it is important to approach the results cautiously. Research like this one provides a useful benchmark as education continues to adjust to shifting global conditions, but it also emphasises the necessity for ongoing investigation and improvement in pedagogical research.

References

• Bharath, B.C., Balamuralidhara, V. and Gowrav, M.P. (2021). Role of real world data and real world evidence in regulatory decision making. RESEARCH JOURNAL OF PHARMACY AND TECHNOLOGY, 14(2), pp.1177–1182. doi:https://doi.org/10.5958/0974-360x.2021.00210.9.
• Janice Bain Sibley (2022). Meeting the Future: How CME Portfolios Must Change in the Post-COVID Era. Journal of European Continuing Medical Education, 11(1). doi:https://doi.org/10.1080/21614083.2022.2058452.
• Stephenson, C.R., Bonnes, S.L., Sawatsky, A.P., Richards, L.W., Schleck, C.D., Mandrekar, J.N., Beckman, T.J. and Wittich, C.M. (2020). The relationship between learner engagement and teaching effectiveness: a novel assessment of student engagement in continuing medical education. BMC Medical Education, 20(1). doi:https://doi.org/10.1186/s12909-020-02331-x.
• Stephenson, C.R., Yudkowsky, R., Wittich, C.M. and Cook, D.A. (2022). Learner Engagement and Teaching Effectiveness in Live Streamed vs In?person CME. Medical Education. doi:https://doi.org/10.1111/medu.14996.