STUDENTS’ BEHAVIORAL INTENTION TO ADOPT COGNITIVE LOAD OPTIMIZATION TO TEACH STEM IN GRADUATE STUDIES
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Abstract
The Cognitive Load Optimization (CLO) method provides a quantitative metric for measuring Intrinsic Cognitive Load (ICL), which is a measure of complex knowledge that is hard to teach. CLO provides guidelines to assist in the presentation of information in order to optimize intellectual performance. Using this method, it is possible to produce the simplest learning sequence with the minimum ICL. Business courses, such as IT technology management, require students to study STEM technical subjects such as IT infrastructure. However, business students typically do not have a technical background. The research objective of this study is to investigate students’ behavioral intention to adopt CLO to teach STEM disciplines in graduate studies in Bangkok. This research tool is a quantitative approach using a questionnaire method to collect around 210 participants of graduate students who study by using CLO approach in remote learning systems environment in various programs. There were collected from online survey by using stratified random sampling and purposive sampling methods. The survey was distributed electronically via choose yourself and learning management channels which provide by the university. The study is applied the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. The conceptual framework focuses to determine the factors that influence the students’ intention to adopt CLO-learning via remote learning systems. Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM) techniques selected to analyze the data to confirm goodness-of-fit of the model and hypothesis testing. The results pointed out that performance expectancy, effort expectancy, lecturers’ influence, facilitating condition, perceived usefulness, perceived ease of use, and personal innovativeness have a significant effect on students’ behavioral intention to adopt/use cognitive load optimization to teach STEM disciplines in graduate studies; however, the relative advantage illustrated in a non-significant variable only in this study.
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