A model for predicting the educational use of information and communication technologies

Citation
B. Collis et al., A model for predicting the educational use of information and communication technologies, INSTR SCI, 29(2), 2001, pp. 95-125
Citations number
12
Categorie Soggetti
Education
Journal title
INSTRUCTIONAL SCIENCE
ISSN journal
00204277 → ACNP
Volume
29
Issue
2
Year of publication
2001
Pages
95 - 125
Database
ISI
SICI code
0020-4277(200103)29:2<95:AMFPTE>2.0.ZU;2-1
Abstract
This study of 550 persons. predominately education professionals, was desig ned to test an integrated theoretical model (the 4-E Model) for predicting the likelihood of the use of telecommunications-related technological innov ations tin particular, e-mail, the WWW, and videoconferencing) in learning- related settings. The four Es in the model, derived from a series of previo us studies (Collis & Pals, 1999), are environmental factors, effectiveness, ease of use, and (personal) engagement. The model was first tested using f actor-analytic procedures on the results of a 54-item questionnaire adminst ered via the WWW to a sample of 550 persons from 39 countries. Twelve facto rs with eigenvalues greater than 1.00 were extracted and latent variables w ere 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 subas pects. In addition, a series of variables related to likelihood of use of e -mail, the WWW, and videoconferencing in educational settings was also subj ected to a factor analysis, resulting in three latent variables representin g 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 relat ing to the organization, as well as the engagement subfactor relating to th e individual's self-confidence with respect to technology use to the predic tion 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 M odel were identified as key to implementation prediction. These variables w ere used in a series of analyses of key subgroups in the sample, relating t o 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.