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User acceptance of learning innovation: A structural equation modelling based on the GUAM framework

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The continuing quest to ensure user acceptance is an ongoing management challenge and one that has occupied information systems researchers to such an extent that technology acceptance research is now… Click to show full abstract

The continuing quest to ensure user acceptance is an ongoing management challenge and one that has occupied information systems researchers to such an extent that technology acceptance research is now considered to be among the more mature areas of exploration. Several models have been developed and validated in different contexts to help explain technology acceptance. Among these models, UTAUT is the most robust, and influential model in predicting acceptance of information technology by its users. Despite being a robust model, UTAUT was limited (throttled) by its poor variance on Learning Innovations. Hence, inappropriate for learning innovation adoption. Aiming to solve this problem, this study proposed and validated a generic usability and acceptance model (GUAM) with a view to measure behavioural intention in accepting and using learning innovations. Our proposed GUAM incorporates four constructs: user expectancy, institutional supports, social influence, and perceived system expectations. Individual differences—such as, age, gender, awareness, accessibility, and experience—were hypothesized to moderate the effects of these constructs on behavioral intention and innovation use. Measures for the study were developed while some were adopted from previous studies, and a questionnaire tagged Learning Innovations Adoption Questionnaire was used. Exploratory and confirmatory factor analyses were used to test and better understand the underlying structure of the proposed model, using structural equation modelling (SEM). Results from the survey with learning innovation use data, of 1357 respondents supported our generic model. Compared to UTAUT, the proposed GUAM produced a substantial improvement in the variance explained in behavioral intention (72%) and technology use (63%) of learning innovations. This study proved that domain-based model outperforms a general adoption model, which attempts to address several classes of technologies.

Keywords: model; guam; user acceptance; learning innovations; learning innovation; acceptance

Journal Title: Education and Information Technologies
Year Published: 2021

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