Students' Navigational Pattern and Performance in An E-Learning Environment: A Case from UP Open University, Philippines

Year 2015, Volume: 16 Issue: 1, 101 - 111, 27.02.2015

Ricardo T. Bagarınao

https://doi.org/10.17718/tojde.47684

Abstract

The study analyzed the navigational patterns of learners in an online course in Science, Technology, and Society using movement ecological concept. The course site consists of five important pages, namely: home page, resource page, user page, forum page, forum discussion page, and forum add post page. About 11,413 logged data were mined and analyzed for the learners’ mean number of visits (NOV) in each page. The computed mean NOV was correlated with the learners’ performance, which was measured through their final grades. Results indicate that learners had visited more frequently the pages that contained information they need to accomplish the course requirements: home page (mean NOV=87.38); resource page (mean NOV=40.33); and discussion forum page (mean NOV=56.29). Those who had visited the resource page were more likely to visit the discussion forum page, participate in the on-going discussion, and/or create a new thread of discussion. These patterns show that learners seek information that is necessary in their learning transactions. The patterns of navigation however did not show a significant relationship with learners’ performance (p>0.05). Other factors may have contributed to their performance, and they must be identified as well to create a virtual environment that can maximize the learners’ learning experience.

Keywords

Navigational pattern analysis, science, technology and society, navigation behaviour, UP Open University, movement ecology, open and distance e-learning

References

• Ajiboye, J. & Tella, A. (2007). University undergraduate students’ information seeking behaviour: implications for quality in higher education in Africa. The Turkish Online Journal of
• Educational Technology, 6 (1): 40-52. Retrieved June 5, 2013 from http://www.tojet.net/articles/v6i1/614.pdf
• Alomyan, H. (2004). Individual differences: implications for web-based learning design.
• International Education Journal, 4(4): 188-196. Retrieved June 20, 2013 from http://iej.cjb.net
• Balaji, M. S. & Chakrabarti, D. (2010). Student interactions in online discussion forum: empirical research from ‘media richness theory’ perspective. Journal of Interactive Online
• Learning, 9(1): 1-22. Retrieved June 9, 2013 from http://www.ncolr.org/jiol/issues/pdf/9.1.1.pdf
• Banks, HT., Kareiva, P. M., & Murph, K. (1987). Parameter estimation techniques for interaction and distribution models: a predator-prey example. Oecologia, 74, 356-362.
• Bereiter, C. (1994). Implications of postmodernism for science, or, science as progressive discourse. Educational Psychologist, 29(1), 3-12.
• Bon, A. B. (1980). Optimal foraging in a uniform habitat: the search mechanism of the green lacewing. Animal Behavior, 28, 10-19.
• Bouhnik, D. & Marcus, T. (2005). Interaction in Distance-Learning Courses. Journal of the American Society for Information Science and Technology, 57(3):299–305. DOI: 1002/asi.20277.
• Bousbia, N., Rebaï, I., Labat, J., & Balla, A. (2010). Learners' navigation behavior identification based on trace analysis. User Modeling and User-Adapted Interaction, 20(5): 455-494.
• Burton, L. & Goldsmith, D. (2002). Students’ experiences in online courses: a study using asynchronous online focus groups. Connecticut Distance Learning Consortium. Retrieved June 5, 2013 from http://www.ctdlc.org/ResourceDocs/evaluation/StudentExperience.pdf
• Carbo, J.M., Mor, E., & Minguillion, J. (2005). User navigational behavior in e-learning virtual environments. Proceedings of the 2005 IEEE/WIC/ACM International
• Conference on Web Intelligence (WI’05). Retrieved January 28, 2012 from http://i- learn.uitm.edu.my/resources/journal/j4.pdf
• Chen, S. Y. & Macredie, R. D. (2002). Cognitive Styles and Hypermedia Navigation:
• Development of a Learning Model. Journal of the American Society for Information Science and Technology, 53(1): 3-15. Crist, T. O., Guertin, D. S., Weins, J. A., & Milne, B. T. (1992). Animal movement in heterogeneous landscapes: an experiment with eleodes beetles in shortgrass prairie.
• Functional Ecology, 6, 536-544. Dennen, V.P., Darabi, A. A., & Smith, L.J. (2007). Instructor–Learner Interaction in Online
• Courses: The relative perceived importance of particular instructor actions on performance and satisfaction. Distance Education, 28(1): 65-79. Retrieved June 9, 2013 from http://research.susanconrad.com/wp-content/uploads/2012/07/Dennen-Darabi-and- Smithpdf
• Dillon, C. L., Gunawardena, C. N., & Parker, R. (1992). Learner support: The critical link in distance education. Distance Education, 13(1), 29-45.
• Eveland, W. P. Jr. & Dunwoody, S. (1998). Users and navigation patterns of a science World
• Wide Web Site for the public. Public Understanding of Science 7, 285-311. Gephi.org. (2012). The open graph viz platform. Retrieved June 5, 2013 from https://gephi.org/
• Graf, S., Liu, T.C. & Kinshuk. (2010). Analysis of learners' navigational behaviour and their learning styles in an online course. Journal of Computer Assisted Learning, 26: 116–131. doi: 1111/j.1365-2729.2009.00336.x
• Greenwood, P.J. & Swingland, I.R. (1984). Animal movement: approaches, adaptations, and constraints. In I.R. Swingland and P.J. Greenwood (eds.). The Ecology of Animal Movement.
• Clarendon Press, Oxford. pp 1-6. Herder, E., & Juvina, I. (2004). Discovery of individual user navigation styles. In G. D. Magoulas
• & S. Y. Chen (Eds.), Adaptive Hypermedia AH2004 Workshop on Individual Differences in
• Adaptive Hypermedia. Eindhoven. http://www.ascilite.org.au/conferences/perth04/procs/sims.html Hung, J & Zhang, K. (2008). Revealing online learning behaviors and activity patterns and making predictions with data mining techniques in online teaching. MERLOT Journal in Online
• Learning and Teaching, 4(4): 426-437. Retrieved 31 January 2014 from http://jolt.merlot.org/vol4no4/hung_1208.pdf
• Levin, S. A. (1974). Dispersion and population interactions. American Naturalist, 108, 207-228.
• MacGregor, S. (1999). Hypermedia Navigation Profiles: Cognitive Characteristics and Information Processing Strategies. Journal of Educational Computing Research, 20(2): 189- 20
• McConnell, D. (2006). E-learning groups and communities. Berkshire, England: Open University
• Press. Retrieved 31 January 2014 from http://www.google.com.ph/books?hl=en&lr=&id=nULf91HI6eQC&oi=fnd&pg=PP1&dq=McConnell,+D.+
• (2006).+Elearning+groups+and+communities.+Berkshire,+England:+Open++University+Press&ots=jE8 v-wUAL6&sig=zQV5JYXOxbemjdvMzwpSDDyw3rA&redir_esc=y#v=onepage&q&f=false
• Murdie, G. & Hassell, M.P. (1973). Food distribution, searching success, and predator-prey models. In M.S. Bartlett and R.W. Hiorns. The Mathematical Theory of the Dynamics of
• Biological Populations. Academic Press, London. Pp. 87-101
• Neuhauser, C. (2002), Learning Style and Effectiveness of Online and Face-to-Face Instruction.
• American Journal of Distance Education 16(2), 99-113. Okubo, A. (1980). Diffusion and ecological problems: Mathematical Models. Springer-Verlag, New York.
• Onuoha, U.D. & Awoniyi, A.A. (2011). Comparative analysis of students’ information seeking behaviour in Adventist universities: a survey of Babcock and Solusi Universities. Library
• Philosophy and Practice, p.100. Retrieved June 9, 2013 from http://connection.ebscohost.com/c/articles/77410659/students-level-study-user-library- resources-nigerian-universities-comparative-study
• Pyke, G. H. (1984). Animal movements: on optimal foraging approach. In Swingland, I.R. and P.J. Greenwood (eds.). The Ecology of Animal Movement. Clarendon Press, Oxford. pp. 7-31.
• Sims, R. & Bovard, B. (2004). Interacting with online learners: How new elaborations of online presence can foster critical thinking and reflection. In R. Atkinson, C. McBeath, D. Jonas-Dwyer
• & R. Phillips (Eds), Beyond the comfort zone: Proceedings of the 21st ASCILITE Conference (pp. 841-850). Perth, 5-8 December. Siniff, D. B., & Jessen, C.R. (1969). A simulation model of animal movement patterns. Advances in Ecological Research, 6, 185-219
• Smith, J. N. M. (1974). The food searching behavior of two European thrushes: I. Description and analysis of the search paths. Behavior 48, 276-302.
• Somyürek, S., Güyer, T., & Atasoy, B. (2008). The effects of individual differences on learner’s navigation in a courseware. The Turkish Online Journal of Educational Technology, 7(2): 32-40.
• Stamps, J. A., Buechner, M., & Krishnan, V.V. (1987). The effects of edge permeability and habitat geometry on emigration from patches of habitat. American Naturalist, 129, 533-552.
• Stein, D. S., Wanstreet, C. E., & Glazer, H. R. (2010). Knowledge Building in Process: Adult
• Learners’ Perceptions of Participating in Collaborative Knowledge-building Communities. In 29th Annual Midwest Research-to-Practice Conference In Adult, Continuing, Community and Extension Education (p. 207). https://www.msu.edu/~mwr2p/SteinWanstreetGlazer-MR2P- 20pdf Retrieved 31 January 2014.
• Steinwendner, J. (2002). Graph-theoretic issues in remote sensing and landscape ecology.
• EnviroInfo. Environmental Communication in the Information Society -Proceedings of the 16th Conference, IGU/ISEP (Wien). ISBN: 3-9500036-7-3. Retrieved June 9, 2013 from http://www.academia.edu/1863849/Graph- theoretic_issues_in_remote_sensing_and_landscape_ecology
• Swihart, R.K., Slade, N.A., & Bergstrom, B.J. (1988). Relating body size to the rate of home range in mammals. Ecology, 69, 393-399.,
• Thomas, M.J.W. (2002). Learning within incoherent structures: the space of online discussion forums. Journal of Computer Assisted Learning, 18: 351-366. http://homepages.abdn.ac.uk/n.coutts/pages/Radio4/Articles/thomas_2002.pdf Retrieved on June 19, 2013.