Factors influencing the behavioural intention to adopt the flipped classroom amongst computer science academics: An Extended UTAUT predictive model

Abstract

Many computer science academics have employed information technology, such as the flipped classroom, in their teaching. As one of the blended learning approaches, the flipped classroom (FC) has been tested and applied in teaching computing courses. The last few years have seen an increase in the adoption of the FC; a move that has led many academics in computer science departments to shift from a traditional teaching approach to a more student-centered one. The research evaluating this new teaching method presents promising evidence of its efficiency. Importantly, the literature review identified the lack of a technology acceptance model to predict the behavioural intention of computer science instructors to adopt the flipped classroom. It has been shown that instructors’ acceptance of the flipped classroom as a teaching approach could be influenced by many different factors. This study, therefore, aims to fill the gap in the literature on the flipped classroom by examining the factors that affect the behavioural intention of computer science instructors to adopt the flipped classroom. This study introduces an extended Unified Theory of Acceptance and Use of Technology (UTAUT) model to predict the factors that could influence the behavioural intention of computer science instructors to adopt the flipped classroom. The model, which was validated and tested using both qualitative and quantitative research methods, and followed the sequential design outlined below. First, to explore the relevant factors, a review of the literature that applied the UTAUT model in similar studies was conducted. As a result, a preliminary model based on the UTAUT model was proposed. The model included the following five factors: performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating condition (FC), and technology self-efficacy (TSEF). Second, the extended model was evaluated by conducting semi-structured interviews with 14 flipped classroom practitioners, mainly from the perspectives of computer science instructors. The findings were analysed using thematic analysis. The results provide evidence given by the participants on the significance of each of the five proposed factors, particularly the first three: performance expectancy, effort expectancy, and social influence. Further, the practitioners recommended seven additional factors that were added to the model: time availability (TA), course type (CT), communication-interaction (CI), student readiness (SR), professional security (PS), mitigating the English barrier (MEB), and reward availability (RA). Third, following the semi-structured interviews, a quantitative study was undertaken with global computer science instructors to explore the significance of the factors. Fifty-six global computer science instructors completed the online questionnaire. The results revealed that 10 out of 12 factors were statistically significant. Those factors were performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), and technology self-efficacy (TSEF), along with time availability (TA), communication Interaction (CI), student readiness (SR), mitigating the English barrier (MEB), and reward availability (RA). Finally, after exploring the significant factors from global computer science instructors, a second quantitative explanatory study was undertaken with the Saudi Arabian computer science instructors. One hundred thirty-four computer science instructors completed the online questionnaire. The principal component analysis suggested nine factors. In addition, the results from a multiple regression analysis indicated that seven independent variables were the predictors of the dependent variable (the behavioural intention of the instructors to adopt the flipped classroom). Overall, the model accounted for 56 percent of the variance in the computer science instructors’ behavioural intention to adopt the flipped classroom. The instructors’ behavioural intention is primarily predicted by the communication and interaction-CI factor and, to a lesser extent, by the social influence-SI factor. Thus, the computer science instructors’ behavioural intention was predicted by seven independent variables, as follows: instructor experience expectancy (IEE), communication-interaction (CI), mitigating the English barrier (MEB), performance expectancy (PE), effort expectancy (EE), social influence (SI), and technology self-efficacy (TSEF). This study contributes to the knowledge on technology adoption models, particularly the UTAUT model, and serves as a powerful tool for future research in the technology adoption studies related to emerging new learning technology from the perspectives of computer science instructors. Thus, the findings of this study provide computer science academics, department heads, deans, and decision-makers with a model that predicts the most significant factors that influence the behavioural intention of computer science academics to adopt the flipped classroom

More information

Identifiers

Catalogue record

Export record