Estimation of Technology Acceptance Model (TAM) on the Adoption of Technology in the Learning Process Using Structural Equation Modeling (SEM) with Bayesian Approach

Elok Fitriani Rafikasari, 198909212018012001 and Nur Iriawan, 196210151988031002 (2021) Estimation of Technology Acceptance Model (TAM) on the Adoption of Technology in the Learning Process Using Structural Equation Modeling (SEM) with Bayesian Approach. 2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI), 1 (1). pp. 86-91. ISSN 978-1-6654-4002-8

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Abstract

Employing computers in the learning technology becomes very important in every classroom learning activity. In fact, the use of computers technology in classroom, however, is often ignored and very rare. Therefore, it is necessary to do a research on teachers’ perception of acceptance in the use of computers technology in their teaching and learning process inside classroom. The most appropriate method to measure the level of acceptance technology adoption is TAM. This method is structured as a hierarchical structure and the analysis requires an appropriate statistical analysis tools, namely SEM. There are some assumptions which must be fulfilled in the SEM analysis, including large sample size, and all of the observed value must be multivariate normally distributed. These requirements are frequently cannot match with the conditions in the real world therefore, SEM would not be applicable. This research was conducted to only 30 teachers on SMP BSS Malang by employing Bayesian SEM which is proposed to overcome the restriction to fulfill the SEM requirement. The results show that technology acceptance during the learning process in this school are influenced by Perceived Ease of Use and Perceived Usefulness which are dominated significantly by Subjective Norm, Innovativeness, Training, Experience and Facilitating Conditions.

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