| Title |
Individual class evaluation and effective teaching characteristics in integrated curricula
|
|---|---|
| Published in |
BMC Medical Education, December 2017
|
| DOI | 10.1186/s12909-017-1097-7 |
| Pubmed ID | |
| Authors |
Jung Eun Hwang, Na Jin Kim, Meiying Song, Yinji Cui, Eun Ju Kim, In Ae Park, Hye In Lee, Hye Jin Gong, Su Young Kim |
| Abstract |
In an integrated curriculum, multiple instructors take part in a course in the form of team teaching. Accordingly, medical schools strive to manage each course run by numerous instructors. As part of the curriculum management, course evaluation is conducted, but a single, retrospective course evaluation does not comprehensively capture student perception of classes by different instructors. This study aimed to demonstrate the need for individual class evaluation, and further to identify teaching characteristics that instructors need to keep in mind when preparing classes. From 2014 to 2015, students at one medical school left comments on evaluation forms after each class. Courses were also assessed after each course. Their comments were categorized by connotation (positive or negative) and by subject. Within each subject category, test scores were compared between positively and negatively mentioned classes. The Mann-Whitney U test was performed to test group differences in scores. The same method was applied to the course evaluation data. Test results for course evaluation showed group difference only in the practice/participation category. However, test results for individual class evaluation showed group differences in six categories: difficulty, main points, attitude, media/contents, interest, and materials. That is, the test scores of classes positively mentioned in six domains were significantly higher than those of negatively mentioned classes. It was proved that individual class evaluation is needed to manage multi-instructor courses in integrated curricula of medical schools. Based on the students' extensive feedback, we identified teaching characteristics statistically related to academic achievement. School authorities can utilize these findings to encourage instructors to develop effective teaching characteristics in class preparation. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 50% |
| Spain | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 36 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 14% |
| Student > Master | 4 | 11% |
| Student > Ph. D. Student | 4 | 11% |
| Student > Doctoral Student | 2 | 6% |
| Student > Postgraduate | 2 | 6% |
| Other | 7 | 19% |
| Unknown | 12 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 6 | 17% |
| Psychology | 3 | 8% |
| Social Sciences | 3 | 8% |
| Nursing and Health Professions | 2 | 6% |
| Arts and Humanities | 2 | 6% |
| Other | 5 | 14% |
| Unknown | 15 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 December 2017.
All research outputs
#17,922,331
of 23,011,300 outputs
Outputs from BMC Medical Education
#2,632
of 3,366 outputs
Outputs of similar age
#306,916
of 439,142 outputs
Outputs of similar age from BMC Medical Education
#89
of 103 outputs
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