This study attempted to combine the benefits of multimedia learning, adaptive interfaces, and learning style theory by constructing a novel e-learning environment. The environment was designed to accommodate individual learning styles while students progressed through an introductory course on computer programming.
The accommodation of learning styles with different forms of instruction has been shown to improve learning gain and learner attitudes in several classroom-based studies. In a classroom environment, one instructor usually teaches many learners simultaneously and as such, individualised instruction can be tedious and time-consuming. In comparison, an e-learning environment can respond to every learner and his or her needs individually with a timely and precise adaptation of learning materials.
Despite these benefits and a growing worldwide e-learning market, there is a paucity of guidance on how to effectively accommodate learning styles in an online environment. Several existing learning-style adaptive environments base their behaviour on an initial assessment of the learner's profile, which is then assumed to remain stable. Consequently, these environments rarely offer the learner choices between different versions of content. However, these choices could cater for flexible learning styles, promote cognitive flexibility and increase learner control.
The first research question underlying the project asked how learning styles could be accommodated in an adaptive e-learning environment. The second question asked whether a dynamically adaptive environment that provides the learner with a choice of media experiences is more beneficial than a statically adapted environment.
To answer these questions, an adaptive e-learning environment named "iWeaver" was created and experimentally evaluated. iWeaver was based on an introductory course in java programming and offered learning content as style-specific media experiences, assisted by additional learning tools. These experiences and tools were based on the perceptual and information processing dimension of an adapted version of the Dunn and Dunn learning styles model.
An experimental evaluation of iWeaver was conducted with 63 multimedia students. The analysis investigated the effect of having a choice of multiple media experiences (compared to having just one static media experience) on learning gain, enjoyment, perceived progress, and motivation. In addition to these quantitative measurements, learners provided qualitative feedback at the end of each lesson.
Data from 27 participants were sufficiently complete to be analysed. The initial analysis revealed no significant differences between the two conditions. However, a small negative effect on learning gain was observed for the choice condition. To further investigate this unexpected effect, participants were divided into two groups of high and low interest in programming and Java, then into two groups of high and low experience with computers and the Internet. Both group comparisons revealed statistically significant differences for the effect of choice. Having a choice of media experiences proved beneficial for learners with low experience but detrimental for learners with high experience or interest. An analysis of the contextualised qualitative feedback from participants moderately supported the quantitative findings.
These findings suggest that the relationship between media choice and the dependent variables is not as trivial as equating more choice with a comprehensive benefit for the learner. Conversely, the effect of choice appears to be strongly influenced by the learner's background. Thus, it seems only worthwhile to provide low experience learners with a choice of media experiences. It is hypothesised that encouraging a more active learner role in educational systems would expand the positive influence of choice to a wider range of learners.
The study has contributed some weight to the argument that for certain groups of learners, it is constructive to view learning style as a flexible, rather than a stable construct. As a practical implication, it seems advisable to collect data on prior experience, interest, as well as the initial learning style distribution of the target audience before developing environments comparable to iWeaver.