THE IMPACT OF GENDER ON THE ACCEPTANCE OF VIRTUAL LEARNING ENVIRONMENTS
K. Milis1, P. Wessa2, S. Poelmans1, C. Doom1, E. Bloemen1
1 HUBrussel (BELGIUM)
2 Lessius (BELGIUM)
E-learning systems, or virtual learning environments (VLEs), are systems that use modern ICT technology to support educational and training efforts. This paper discusses the implementation of a new VLE, that supports non-rote learning of exploratory and inductive statistics within the paradigm of social constructivism. More specifically, it focuses on gender based differences in the adoption of the VLE.
The new computational framework that was especially constructed for the VLE allows us to create an electronic research environment where students are empowered to interact with reproducible computations from peers and the educator. The underlying technology was constructed in such a way that it effectively supports social interaction (communication), knowledge construction, collaboration, and scientific experimentation even if the student population is very large. Moreover, the VLE allows us to obtain physical measurements of the actual learning process of students based on detailed information about the use of the statistical software, and the socially constructivist learning activities.
The VLE was thoroughly tested in three undergraduate statistics courses with large student populations. During these courses a large number of physical and survey-based measurements were obtained and studied. In line with the recent stream of research, Davis’ technology acceptance model (TAM) was used to study the success of the VLE. System and information quality were measured using several dimensions for each concept. Multiple items were used per construct and scales from the literature were adapted or completed if required.
Though, in opposite to previous attempts to use the TAM model on VLE environments (ex. Sun et al., 2008; Marins et al., 2004) an attempt was made to link acceptance to gender specific elements. For every dimension of the two concepts, an attempt was made to trace possible gender-based differences, applying standard anova techniques. Hence, this paper gives insights into the way gender-specific issues impact acceptance of virtual learning environments.