Elsevier

Computers in Human Behavior

Volume 34, May 2014, Pages 315-322
Computers in Human Behavior

Predicting teachers’ generative and receptive use of an educational portal by intention, attitude and self-reported use

https://doi.org/10.1016/j.chb.2013.12.024Get rights and content

Highlights

  • An educational portal can be used for different purposes: receptive and generative.

  • Receptive use: downloads, pageviews, logins; generative use: uploads or reactions.

  • Questionnaire data is coupled to longitudinally collected use behavior.

  • Acceptance measures predict teachers’ receptive use of an educational portal.

  • Uploaders differ fundamentally from non-uploaders.

Abstract

This study takes off where most acceptance studies stop, namely by investigating the link between acceptance and different aspects of actual usage of an educational portal. Both receptive (logins, downloads and pageviews) and generative use behavior (uploads and reactions) of 864 teachers was collected on two occasions, and linked to their responses on an acceptance questionnaire based upon C-TAM-TPB. Two research questions were put forward: (1) which dimensions of actual use are predicted by attitude, intention and self-reported use; and (2) can C-TAM-TPB discern uploaders from non-uploaders. Regression analyses showed that receptive use (logins, downloads, pages viewed) was predicted by attitude, intention and self-reported use (variance explained in the range .13–.16). Generative use (uploading and reacting) was not explained by these self-reported measures (Adj. R2 .01 and .04). Uploaders scored higher on all use parameters and almost all scales. A logistic regression showed that the more positive teachers’ attitudes towards the portal and the higher their perceptions of control; the more likely they will upload information. This study is a call for more research on the factors that influence different dimensions of actual educational technology use, and should be an onset for more research on the link between intention and behavior in different settings, user populations, and technologies.

Section snippets

Rationale

While introducing novel educational technologies to teachers, institutions are unsure as to whether the newly introduced technology will be adopted by the teachers, and used in the way the technology was designed to. For example, in the case of digital learning environments (DLE) that draw heavily on user-generated content, it is important to know (1) how teachers use the DLE: purely receptive (reading, consulting, downloading) or also generative (sharing knowledge or learning material), and

Technology acceptance

Acceptance models emerged from two distinct research traditions: on the one hand from base social psychology theories such as the Theory of Reasoned Action (Fishbein & Ajzen, 1975) and the Social Cognitive Theory (Bandura, 1986), and on the other hand from sociology with the Diffusion of Innovations Theory (Rogers, 1995). An overview can be found in Venkatesh et al. (2003) or in Pynoo et al. (2013).

In the past, researchers put much effort in the search for the optimal set of variables to

Technology: KlasCement

The technology under study is an educational portal (www.klascement.net), targeted at Flemish and Dutch teachers, that builds upon user-generated content that is available for the other members of the portal under a creative commons license. This portal is supported by the Flemish Ministry of Education and is accessible to anyone who registers. The aim of KlasCement is to promote collaboration and communication between teachers regardless of their institution, or region. Use of the portal is on

Descriptive statistics

First, descriptive statistics are calculated. These are displayed in Table 2. Next to an overall mean, we also investigate whether differences can be observed between male and female teachers, and between uploaders and non-uploaders.

Teachers evaluate the portal as quite useful and easy to use, without pressure from the social environment to use the portal. Teachers also experience a large amount of control over their use of the portal. With regard to the acceptance measures, teachers hold a

Descriptive statistics

Descriptive statistics (Table 2) revealed quite some significant differences between teachers who share learning material (uploaders) and teachers who do not share (non-uploaders). Based upon these findings, it could be argued that teachers who upload are innovators or early adopters in terms of Rogers (1995) who are better informed and more aware of the latest educational innovations, and who are more skilled in using the computer. Consistent with Pynoo et al. (2012b), these findings also

Conclusion

This study takes off where most acceptance studies stop, namely by investigating the link between acceptance and different aspects of actual technology usage. Hereto, questionnaire data of 864 teachers/members of KlasCement – an educational portal – was coupled to their use data extracted from the portal’s logs. Acceptance was measured as behavioral intention, attitude, and self-reported frequency and intensity of use, whereas five use parameters were extracted: the number of logins, downloads,

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