Analysis of Relationship of Academic Personnel Data for Management Teaching with Method Adjustment of K-Means Combined with Association Rules
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Abstract
This article aimed to propose the guideline for selecting academic personnel in computer with K-Means combined with Association rules (K-MAs). Data were collected from the questionnaire on computer instruction according to curricula approved by the Office of the Higher Education Commission (OHEC). In this study, key informants were academic personnel of the Faculty of Science and Technology in Rajamangala University of Technology Suvarnabhumi that encountered problems in the differences in instructional ability, causing the difficult and complicated instructional management that will affect potential curriculum improvement. For this reason, the researcher searched for the solutions by using K-MAs, which dividing data set of academic personnel method adjustment of K-Means combined with association rules. However, K-Mas could produce the results that consider the importance of the instructors and know the group members. Besides, the rule of associations indicate that members of the group were able to instruct the same course. Therefore, it could be concluded that K-MAs technique could be used to support instructor management under the balance between instructor competency and proficient profession and to enhance human relations with fellow scholars due to the realization of professional groups. The results of this research showed that under the classification of instructor groups based on suitable professional group, there were five professional groups. Up to 3 instructors could instruct interchangeably using 18 association rules. The evaluative results of the web application for selecting academic personnel indicated that overall evaluation result was at a good level. An aspect with the lowest mean was clear and easy-to-read size of fonts (mean = 3.71). An aspect with the highest mean was accurate instructor data (mean = 4.86). Therefore, it could be concluded that the developed web application could be usefully applied to analyze computer instructor management methods with K-Means combined with Association rules.
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References
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