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Examining CEGEP students’ acceptance of computer-based learning environments: A test of two models

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Abstract

As the use of technology in education advances and broadens, empirical research around its use assumes increased importance. Yet literature investigating technology acceptance in certain populations remains scarce. We recently argued that technology acceptance investigations should also consider the modality of the antecedent belief, to distinguish between beliefs of conditionality, and necessity, such that sometimes we are constrained to act by circumstance, and other times we act to obtain a certain outcome, which differently affects our appraisals of situations (Doleck et al. 2016). In this vein, we propose to study technology acceptance with a population that is constrained in their acceptance of certain technologies, such as university or college students’ tacit acceptance of classroom computer applications. In the present paper, we pose the question: what factors affect Collège d’enseignement général et professionnel (CEGEP) students’ technology acceptance, specifically, what are the antecedents to their computer-based learning environment (CBLE) use. To explore this question, we employ a structural equation modeling approach, specifically a partial least square (PLS) approach, using the technology acceptance framework. The present study applies two well-known models of acceptance, the Technology Acceptance Model (TAM; Davis in MIS Quarterly, 13(3), 319–340 1989) and the Unified Theory of Acceptance and Use of Technology (UTAUT; Venkatesh et al. in MIS Quarterly, 27(3), 425–478 2003) to investigate the acceptance of CBLEs among CEGEP students and attempts to address technology acceptance in forced-choice situations.

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  1. McGill University, 3700 McTavish St., Montreal, QC, H3A 1Y2, Canada

    Tenzin Doleck, Paul Bazelais & David John Lemay

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  1. Tenzin Doleck
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  2. Paul Bazelais
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Correspondence to Tenzin Doleck.

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Doleck, T., Bazelais, P. & Lemay, D.J. Examining CEGEP students’ acceptance of computer-based learning environments: A test of two models. Educ Inf Technol 22, 2523–2543 (2017). https://doi.org/10.1007/s10639-016-9559-9

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