FACTOR ANALYSIS OF PROBLEM – BASED LEARNING DIGITAL GAME TO ENHANCE PROBLEM SOLVING ABILITY IN SCIENCE SUBJECT FOR ELEMENTARY STUDENTS

Problem-based learning digital games are able to provide a fun and motivating environment for teaching and learning of certain subjects. However, most learning digital game factors do not address the learning elements of problem-based educational games. This study aims to analyze factors of problem–based learning digital game. The sample populations targeted in this study were 300 respondent, the samples were from three main fields by stratified random sampling and simple random. Each of a hundred of primary school teachers, digital game developers, and educational technologist responded the questionnaires. Exploratory factor analysis was used in the study. Exploratory factor analysis indicated there were eight factors. The KMO result indicated that the sampling was quite adequate. The KMO was 0.946 Bartlett’s test was significant. The Oblimin rotation was used. Cronbach’s alpha reliabilities for overall factors were 0.963. The data was analyzed using SPSS program version 18. Eight separate factor analyses with Oblimin rotation were done to validate whether the respondents perceived the independent, mediating and dependent variables were distinct constructs. Researcher used the same criterion that was suggested by Field (2013) to identify and interpret factors which were: each item should load 0.50 or greater on one factor and 0.3 or lower on the other factor. The results for the factor analysis for this measure yielded a eight factor solution with eigenvalues greater than 1.0 and the total variance explained was 64.676% of the total variance. KMO measure of sampling adequacy was 0.946 indicating sufficient intercorrelations while the Bartlett’s test of Sphericity was significant (Chi square =9572.365, p< 0.01). This study was analyzed to ascertain the factors of problem–based learning digital game. Eight factor themes emerged through data collection and analysis factors that were studied include Problem-based learning, evaluation, facilitator, reinforcement, feedback, authentic problem, environment, and role game. Hence, the results of this study have implications for developers can use this factor to facilitate to be Problem-based learning digital games.