Successful lecturing: a prospective study to validate attributes of the effective medical lecture.
OBJECTIVE
In a study conducted over 3 large symposia on intensive review of internal medicine, we previously assessed the features that were most important to course participants in evaluating the quality of a lecture. In this study, we attempt to validate these observations by assessing prospectively the extent to which ratings of specific lecture features would predict the overall evaluation of lectures.


RESULTS
After each lecture, 143 to 355 course participants rated the overall lecture quality of 69 speakers involved in a large symposium on intensive review of internal medicine. In addition, 7 selected participants and the course directors rated specific lecture features and overall quality for each speaker. The relations among the variables were assessed through Pearson correlation coefficients and cluster analysis. Regression analysis was performed to determine which features would predict the overall lecture quality ratings. The features that most highly correlated with ratings of overall lecture quality were the speaker's abilities to identify key points (r =.797) and be engaging (r =.782), the lecture clarity (r =.754), and the slide comprehensibility (r =.691) and format (r =.660). The three lecture features of engaging the audience, lecture clarity, and using a case-based format were identified through regression as the strongest predictors of overall lecture quality ratings (R2 = 0.67, P = 0.0001).


CONCLUSIONS
We have identified core lecture features that positively affect the success of the lecture. We believe our findings are useful for lecturers wanting to improve their effectiveness and for educators who design continuing medical education curricula.
Copeland
H L
HL
Division of Education, Cleveland Clinic Foundation, OH 44195, USA.
Longworth
D L
DL
Hewson
M G
MG
Stoller
J K
JK
D004502:Education, Medical, Continuing; D006801:Humans; D007388:Internal Medicine / Q000193:education*; D011446:Prospective Studies; D012044:Regression Analysis; D013663:Teaching / Q000379:methods*