Research in Engineering Education Symposium 2011 - rees2009

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Universidad Politécnica de Madrid (UPM) Página 716 de 957 be a close correlation between system events and learner reported issues, or a significant divergence. Either of these outcome has can generate significant findings about the research question, as either scenario can give a strong indication of the importance of QoS in online learning environments. In line with best practice in diary studies (Bernard, 2006), students who have kept logs will be asked to do a telephone debrief to clarify the data they have recorded. This will allow the researchers to follow up on and triangulate the data from the first two instruments. For example, if there is an event reported in the log instrument which raises questions when compared to the monitor data, this can be investigated by asking targeted questions about the event. Furthermore, the significance of the events for the participants can be clarified. This adds validity to the methodology employed. Even as a case study, the methodological framework being employed demonstrates sound theoretical validity (Yin, 2009), by allowing for all of the factors that impact on quality of experience in learning to be captured in the data. Conclusion This paper discussed the outcomes of a pilot study that explores relevant factor that impact on the performance of online learning systems. Key outcomes of this investigation include that students do not necessarily identify learning tools as such and this might impact on their quality perception. The development of the research methodology and analysis of the pilot study have highlighted some significant issues for the field of research which the main study will attempt to pursue and address. The main study will be undertaken in the second half of 2011. Until the significance of quality of service for online learning environments is explored, it is unknown how the existing literature on quality of service can inform the design of effective online learning environments. It is vital that the above issues be explored and understood if further research into quality of service for online learning is to be fruitful. Results will remain relevant as the use of multimedia and other learning technologies will continue to increase in the foreseeable future. References Bernard, H. R. (2006). Research methods in anthropology : qualitative and quantitative approaches (4th ed.). Lanham, MD: Altamira Press. Brooks, P., & Hestnes, B. (2010). User measures of quality of experience: why being objective and quantitative is important. Network, IEEE, 24(2), 8-13. Department of Education, Queensland. (2002). Productive Pedagogies: Classroom reflection manual. Retrieved from http://education.qld.gov.au/public_media/reports/curriculumframework/productive-pedagogies/html/manual.html. Gilbert, J., Morton, S., & Rowle, J. (2007). e-Learning: The student experience. British Journal of Educational Technology, 38(4), 560-573. Proceedings of Research in Engineering Education Symposium 2011 Madrid, 4 th - 7 th October 2011
Universidad Politécnica de Madrid (UPM) Página 717 de 957 Harman, G. (1990). The intrinsic quality of experience. Philosophical Perspectives, Ridgeview, 4, 31-52. Herrington, J., Oliver, R., & Reeves, T. C. (2003). Patterns of engagement in authentic online learning environments. Australian Journal of Educational Technology, 19(1), 59-71. Kilkki, K. (2008). Quality of Experience in Communications Ecosystem. Journal of Universal Computer Science, 14(5), 615-624. Killen, R. (2009). Effective teaching strategies : lessons from research and practice (5th ed.). South Melbourne, Vic.: Cengage Learning. Kist, A. A., & Gibbings, P. (2010). Inception and management of remote access laboratory projects. Paper presented at the AaeE 2010: 21st Annual Conference of the Australasian Association for Engineering Education, Sydney, Australia. Kuipers, F., Kooij, R., De Vleeschauwer, D., & Brunnström, K. (2010). Techniques for Measuring Quality of Experience. In E. Osipov, A. Kassler, T. Bohnert & X. Masip- Bruin (Eds.), Wired/Wireless Internet Communications (Vol. 6074, pp. 216-227): Springer Berlin / Heidelberg. Mayer, R. E. (1989). Models for Understanding. Review of Educational Research, 59(1), 43- 64. Mayer, R. E. (2003). The promise of multimedia learning: using the same instructional design methods across different media. Learning and Instruction, 13(2), 125-139. Moebs, S. A. (2008). A learner, is a learner, is a user, is a customer: QoS-based experienceaware adaptation. Paper presented at the Proceeding of the 16th ACM international conference on Multimedia, Vancouver, British Columbia, Canada. Moller, S., Engelbrecht, K. P., Kuhnel, C., Wechsung, I., & Weiss, B. (2009, 29-31 July 2009). A taxonomy of quality of service and Quality of Experience of multimodal humanmachine interaction. Paper presented at the Quality of Multimedia Experience, 2009. QoMEx 2009. International Workshop on. Sambrook, S. (2001). Factors influencing learners' perceptions of the quality of computer based learning materials. Journal of European Industrial Training, 25(2/3/4), 157- 167. Soldani, D., Li, M., & Cuny, R. (2006). QoS and QoE management in UMTS cellular systems. Chichester: John Wiley and Sons. Wu, W., Arefin, A., Rivas, R., Nahrstedt, K., Sheppard, R., & Yang, Z. (2009). Quality of experience in distributed interactive multimedia environments: toward a theoretical framework. Paper presented at the Proceedings of the 17th ACM international conference on Multimedia, Beijing, China. Proceedings of Research in Engineering Education Symposium 2011 Madrid, 4 th - 7 th October 2011
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