Journal
INSTRUCTIONAL SCIENCE
Volume 29, Issue 2, Pages 95-125Publisher
KLUWER ACADEMIC PUBL
DOI: 10.1023/A:1003937401428
Keywords
4-E Model; factors influencing implementation; implementation; likelihood of use
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This study of 550 persons. predominately education professionals, was designed to test an integrated theoretical model (the 4-E Model) for predicting the likelihood of the use of telecommunications-related technological innovations tin particular, e-mail, the WWW, and videoconferencing) in learning-related settings. The four Es in the model, derived from a series of previous studies (Collis & Pals, 1999), are environmental factors, effectiveness, ease of use, and (personal) engagement. The model was first tested using factor-analytic procedures on the results of a 54-item questionnaire adminstered via the WWW to a sample of 550 persons from 39 countries. Twelve factors with eigenvalues greater than 1.00 were extracted and latent variables were generated to correspond with the factors. The factors as interpreted by items with loadings <0.500 supported the 4-E Model, but indicated that the four theoretical e dimensions could be further expressed in terms of subaspects. In addition, a series of variables related to likelihood of use of e-mail, the WWW, and videoconferencing in educational settings was also subjected to a factor analysis, resulting in three latent variables representing the dependent variables for a causal model. The causal model linking the latent variables was tested using a series of LISREL analyses, one fur each of the derived dependent variables. The results, which again supported the 4-E Model, showed a strong contribution of the environment subfactor relating to the organization, as well as the engagement subfactor relating to the individual's self-confidence with respect to technology use to the prediction of implementation success. Based on the results of the factor analysis and the model validation, six of the latent variables related to the 4-E Model were identified as key to implementation prediction. These variables were used in a series of analyses of key subgroups in the sample, relating to educational sector, educational role, to gender, and to age, in order to examine key discriminating variables. The results are discussed in terms of their theoretical and practical implications, including the development of a WWW-based instrument.
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