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Innovation attributes and pedagogical quality: a concretization of joint theories on course management systems acceptance

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  • Shinyi Lin
  • Shueh-Fen Chen

Abstract

The utilization of information and communication technologies in support of teaching and learning is still on its way to expand its potentials in higher education. Facing different venues of course delivery, computer-mediated communication technologies seem to be the most efficient and cost-effective. Since the mid-1990s, course management systems (CMSs) have gradually evolved, and taken an irreplaceable important role in higher education. From the perspectives of pedagogical impact and instructional resource consumption, Morgan ( 2003 ) considered that CMSs form the academic system equivalent of enterprise resource planning systems. Based on an extensive review on the Technology Acceptance Model (TAM) and Innovation Diffusion Theory (IDT) at the outset, this study bridges the TAM and IDT, and proposes a conceptual model of the acceptance of CMSs to acknowledge antecedents (i.e., innovation attributes, self-efficacy (SE), pedagogical quality (PQ) and perceived evaluation of function (EF)). Theoretically, the perceived innovation attributes of CMSs impact users’ perceived usefulness (PU) and actual use (AU). The antecedents, such as SE, PQ, and EFs, are also anticipated to have impacts on the AU and use of perception. PU is influenced by perceived ease of use (PEOU), while behavioral intention (BI) is concurrently influenced by PEOU and PU. Moreover, AU is influenced by BI. Finally, discussion and suggestions for future research of the proposed model are also provided. Copyright Springer Science+Business Media B.V. 2013

Suggested Citation

  • Shinyi Lin & Shueh-Fen Chen, 2013. "Innovation attributes and pedagogical quality: a concretization of joint theories on course management systems acceptance," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(4), pages 2309-2317, June.
    • Handle: RePEc:spr:qualqt:v:47:y:2013:i:4:p:2309-2317
    DOI: 10.1007/s11135-011-9657-0
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    References listed on IDEAS

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    1. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    2. Igbaria, M. & Iivari, J., 1995. "The effects of self-efficacy on computer usage," Omega, Elsevier, vol. 23(6), pages 587-605, December.
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