Implementation strategies and the technology acceptance model: Is "ease of use" really useful or easy to use in implementation?

The large investment in information technology in the education sector has made the investigation of technology acceptance important for this sector. In this paper, a questionnaire was given to 282 one-year full-time postgraduate students in education to assess their computer acceptance and intended professional usage in the future. The Technology Acceptance Model (TAM) was used as the framework for analysis. Results of the study suggest an overall consistency of TAM factors examined for explaining usage; however, several areas were identified where individual teacher acceptance differed in their computer acceptance decision-making when compared with previous studies. Specifically, the pre-service teachers in this study made computer acceptance decisions largely based on the usefulness of the computer while ease of use was limited to being only a secondary consideration. However, significant gender differences exist in our findings as well, with male respondents most likely to indicate an insignificant effect on the ease of use factors in influencing usage intention, and with female prospective teachers indicating a influence of ease of use similar to what has been found in prior TAM studies. Implications of gender and context on the significant differences in the determinant, ease of use, are discussed.

[1]  Viswanath Venkatesh,et al.  Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model , 2000, Inf. Syst. Res..

[2]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[3]  Fred D. Davis,et al.  A Model of the Antecedents of Perceived Ease of Use: Development and Test† , 1996 .

[4]  France Bélanger,et al.  Gender differences in perceptions of web-based shopping , 2002, CACM.

[5]  Olivia R. Liu Sheng,et al.  Examining the Technology Acceptance Model Using Physician Acceptance of Telemedicine Technology , 1999, J. Manag. Inf. Syst..

[6]  Wynne W. Chin,et al.  On the use, usefulness, and ease of use of structural equation modeling in MIS research: a note of caution , 1995 .

[7]  Mark Vandenbosch,et al.  Research Report: Richness Versus Parsimony in Modeling Technology Adoption Decisions - Understanding Merchant Adoption of a Smart Card-Based Payment System , 2001, Inf. Syst. Res..

[8]  Bernadette Szajna,et al.  Software Evaluation and Choice: Predictive Validation of the Technology Acceptance Instrument , 1994, MIS Q..

[9]  Peter A. Todd,et al.  Perceived Usefulness, Ease of Use, and Usage of Information Technology: A Replication , 1992, MIS Q..

[10]  Marios Koufaris,et al.  Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior , 2002, Inf. Syst. Res..

[11]  Viswanath Venkatesh,et al.  Why Don't Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior , 2000, MIS Q..

[12]  Kieran Mathieson,et al.  Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior , 1991, Inf. Syst. Res..

[13]  Paul Jen-Hwa Hu,et al.  Investigating healthcare professionals' decisions to accept telemedicine technology: an empirical test of competing theories , 2002, Inf. Manag..

[14]  Viswanath Venkatesh,et al.  Creation of Favorable User Perceptions: Exploring the Role of Intrinsic Motivation , 1999, MIS Q..

[15]  Neal G. Shaw Strategies for Managing Computer Software Upgrades , 2000 .