Table 2.
Cluster Analysis of Lecture Features*
| Cluster 1 | R2with Own Cluster | Cluster 2 | R2with Own Cluster | Cluster 3 | R2with Own Cluster | Cluster 4 | R2with Own Cluster |
|---|---|---|---|---|---|---|---|
| Lecture clarity | .901 | ARS after | .745 | Case-based | .712 | Uses humor | 1.00 |
| Engaging | .901 | ARS during | .673 | Board simulation | .583 | ||
| Identifies points | .838 | ARS before | .267 | Date of lecture | .398 | ||
| Slides, understandable | .817 | Time of lecture | .095 | ||||
| Slides, clear format | .776 | ||||||
| Relevance of material | .629 | ||||||
| Proportion of the variance explained by all clusters = .667 | |||||||
*
The lecture features are sorted into groups in which they are most closely associated. Overall the features represent 4 areas: lecturer's presentation techniques, method of using technology, specific lecture structure/format, and humor (which does not closely associate with any of the 3 previous categories, so it is categorized separately). ARS indicates audience response system.