An Analysis and Clustering of Relationships of Digital Literacy Instructors' data Using Unsupervised Learning of Data Mining Techniques บทความวิจัย

Abstract

          The objectives of this research were: 1) to develop and evaluate the efficiency of a web application designed to survey instructors' data for analyzing and clustering relationships among digital literacy instructors using K-means techniques and 2) to analyze and cluster the relationships among digital literacy instructors' data using K-means techniques. The target group for this research comprised instructors from Surindra Rajabhat University who teach subjects related to computers, spanning five fields: 1) Computer Science, 2) Computer, 3) Computer Technology, 4) Computer Innovation for Business Communications, and 5) Digital Technology for Education. The study involved 20 instructors with experience in teaching digital literacy. Research instruments included: 1) A questionnaire assessing aptitude in teaching content via web applications, 2) A questionnaire evaluating relationships in teaching via web applications, and 3) A performance evaluation form from experts. Data analysis employed mean statistics and standard deviation.

          Key findings include 1) the web application developed for surveying instructors' data and analyzing relationships among digital literacy instructors using the K-means technique, which consists of two main components: (1) system data management and (2) a questionnaire. Overall efficiency was high (= 4.42, SD = 0.56), and 2) Analysis of instructors' data using K-means techniques and association rule creation with the Apriori algorithm method resulted in instructors being classified into four groups: (1) centroid = 3.00, (2) centroid = 4.10, (3) centroid = 4.41, and (4) centroid = 4.91, with 21 association rules identified. These findings demonstrate the web application's successful development and effective use in analyzing and clustering relationships among digital literacy instructors, providing valuable insights into instructional practices and grouping patterns.