ITEM 2006: Knowledge Management for Educational Innovation pp 107-114 | Cite as
Individual Learning Pattern Related to Intention
Abstract
In an e-learning system, it is difficult to grasp the learner’s condition for learning. In the face-to-face learning environment, we tend to notice if there is something unusual about learners and help them out of difficulties. In addition, we often cannot keep learners from dropping out of the e-learning course. This suggests a requirement for a research study specially focused on how to predict the learner’s condition with the learning log data in the e-learning system. Therefore, we drew up a learning model with biological knowledge from the latest molecular biology and brain science. In this paper, results from our learning model were verified by comparison with real learning log data in an e-learning system. Our model suggests that there is a learning type with high intention who prefers to learn in a short term in order to construct his/her knowledge. Then we examined the data related to intention, and it correlated closely with the learning period of one exercise.
Keywords
Knowledge construction learning pattern biological model dopamine5. References
- Bliss, T.V. and Collingridge, G.L., 1993. A synaptic model of memory: long-term potentiation in the hippocampus. Nature, Vol.361, pp.31–39.CrossRefGoogle Scholar
- Botto, L.D. and Khoury, M.J., 2001. Facing the challenge of the gene-environment interaction: The two by for table and beyond. American Journal of Epidemiology, Vol.157, pp.1011–1020.Google Scholar
- Bush, G. et al., 2000. Cognitive and emotional influences in the anterior cingulated cortex. Trends in Cognitive Sciences, Vol.4, pp.215–222.CrossRefGoogle Scholar
- Cooper, R.M. and Zubek, J.P., 1958. Effects of enriched and restricted early environments on the learning ability of bright and dull rats. Canadian Journal of Psychology. Vol.12, pp. 159–164.Google Scholar
- Damasio, A.R., 1994. Descartes’ Error: Emotion, Reason and the Human Brain. Putnam Pub Group Published, NY, USA.Google Scholar
- Damasio, A.R., 1999. The Feeling of What Happens: Body and Emotion in the Making of Consciousness. Harcourt Published, CA, USA.Google Scholar
- Dubnau, J., et al., 2003. The staufen/pumilio pathway is involved in Drosophila long-term memory. Current Biology, Vol. 13, pp.286–296.CrossRefGoogle Scholar
- Eagan, M.F., et al., 2003. The BDKF val66met polymorphism affects activity-dependent secretion of BDNF and human memory and hippocampal function. Cell, Vol. 112, pp.257–269.CrossRefGoogle Scholar
- ELeGI org., 2005/7. GRID Technology for Learning: the “European Learning GRID Infrastructure” project. http://www.elegi.org/.Google Scholar
- Gainetdinov, R.R., et al. 1999. Role of serotonin in the paradoxical calming effect of psychostimulants on hyperactivity. Science, Vol.283. pp.397–402.CrossRefGoogle Scholar
- Grabinger, S. and Dunlop, J. 1995. Rich environments for active learning. Association for Learning Technology Journal, 3(2), pp5–34.Google Scholar
- Gross, C., et al., 2002. Serotonin 1A receptor acts during development to establish normal anxiety-like behavior in the adult. Nature, Vol.416, pp.396–400.CrossRefGoogle Scholar
- Kandel, E.R., 2001. The molecular biology or memory storage: a dialogue between genes and synapses. Science, Vol.294, pp.1030–1038.CrossRefGoogle Scholar
- Hariri, A.R., et al., 2002. Serotonin transporter genetic variation and the response of the human amygdala. Science, Vol.297, pp.400–403.CrossRefGoogle Scholar
- LaHoste, G.J. et al., 1996. Dopamine D4 receptor gene polymorphism is associated with attention deficit hyperactivity disorder. Molecular Psychiatry, Vol. 1, pp.121–124.Google Scholar
- Milner, B. et al., 1998. Cognitive neuroscience and the study of memory. Neuron, Vol.20, pp.445–468.CrossRefGoogle Scholar
- Murphy, D.L., et al., 2001. Genetic perspectives on the serotonin transporter. Brain Research Bulletin, Vol.56, pp.487–494.CrossRefGoogle Scholar
- Ninomiya, T. et al., 2005. Social and biological model of cognitive development and learning pattern. CELDA 2005, pp.18–25.Google Scholar
- Nunes, J.M. and McPherson, M.A. 2002. Pedagogical and implementation models for e-learning continuing professional distance education (CPDE) emerging from action research. International Journal of Management Education, 2(3), pp16–25.Google Scholar
- Poo, M.M., 2001. Neurotrophins as synaptic modulators. Nature Reviews Neuroscience, Vol.2, pp.24–32.CrossRefGoogle Scholar
- Swanson, J. et al., 1998, Cognitive neuroscience of attention deficit hyperactivity disorder and hyperkinetic disorder. Current Opinion in Neurobiology, Vol.8, pp.263–271.CrossRefMathSciNetGoogle Scholar
- Tang, Y.P.,. et al., 1999. Genetic enhancement of learning and memory in mice. Nature, Vol.401, pp.63–69.CrossRefGoogle Scholar