Contribution to effective e-learning systems design

The study found that inclusion of personality in the user model would improve

adaptive-learning systems. Although only at the prototype stage, the study empirically demonstrated that it is possible for a user model to encompass personality type in an effective way. Compared to the complexity of the previous studies using other personal characteristics (Felder & Brent, 2005; Ford et al., 2001; Holodnaya, 2002;

Humanmetrics, 2006; Stash & De Bra, 2004) it would appear that this enables the system to categorise learners more efficiently and direct them effectively to appropriate instruction. The study implies that the user model in adaptive e-learning systems should accommodate learners’ different learning styles.

We hope that the contribution will convince developers of e-learning systems to consider the personality feature in the current user model.

9.2.2 Contribution to pedagogy and teaching practice

The teaching challenge with which this research began should not be forgotten, as its contribution to pedagogy could be even more significant. This research contributes to ongoing debates about how to teach more effectively to different personalities and learning styles, and whether e-learning can do the job a sensitive teacher can do.

Initially the research sought a solution to a classroom instructor’s problems, but while focussing on how to make e-learning more responsive to personality differences, it should not be surprising that it could have more general impact on teaching practice. Teachers acknowledge that knowing the personality of the learners helps the teacher match lessons to student’s needs. This research clearly identifies a significant way that students (of any age) could be grouped (by level of extraversion), which could be beneficial for group work and the management of classes. English language teachers commented (personal communication, April 2007) that they could directly apply the design of collaborative learning in this study to their own teaching. These findings could also contribute to the Human Resources domain on selection and training for specific occupations, for example training the trainers of computer programmers.

9.3 Limitations

The following limitations of the study should be noted. Most of all, the small numbers of participants in Experiment 5 and 6 were the main limitation of this thesis. It is partly because the participants were voluntarily recruited, and partly because the experiments took quite a long time, so there were many instances of attrition. Secondly, the

experiments in this study were limited to the two Universities samples (one from the Gulf States University and the other one from New Zealand), so that the results may not be widely generalisable to the broader population of other cultural contexts. Thirdly, we have not used any other content apart from the computer science courses, so if the

course content is different, for example humanity courses, the result might vary. Fourthly, all the participants were from the Computer Science department, for the convenience of collecting data. IF a larger sample is taken the result may be different. Fifthly, more qualitative research is needed, for example on learners’ feedback on their learning experience for more interpretation. Finally, although we used MBTI, currently more advanced psychological theory can be used such as the Keirsey indicator, which may provide a more candid and effective account of the personality issue, including information about certain types of intelligences, associated with the temperaments. Actually, based on Keirsey’s personality study, ongoing research is planned to repeat the same experiment in other cultural contexts, using Keirsey’s indicator instead of MBTI to justify the finding from the thesis.

Therefore, future research would go through the issues presented and gain new insights into the learners’ learning process in order to generalise the findings of this thesis.

9.4 Future work

It is hoped that this thesis will serve as a springboard for future work in adaptive e- learning and pedagogy. The study in this thesis showed that the newly proposed user model that includes personality in the current user model significantly enhances the effectiveness of learning performance with adaptive e-learning. Yet, the understanding discussed in this thesis still requires more thorough validation and testing for a wide range of e-learning applications, in particular for adaptive e-learning systems.

In the near future, we are planning to perform all the experiments that have been done in this study with more participants to substantiate our findings considering the problems described in section 9.3. Also, they could be extended to embrace other

For example, in other cultural contexts, more experiments are needed to explore whether other personality features apart from introverted and extraverted may affect learners’ performance. Further research would test the effects of the proposed user model in this thesis on different content rather than those from the Computer Science discipline. We are also planning to approach to ELM-ART developers to combine this study in their design of adaptive e-learning systems. This may provide some directions for future research in this area and perhaps it opens the way to fit the learners’