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Educational exploration along the shortest paths in conceptual networks based on co-occurrence, language ability levels and frequency ranking
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, Aalto University School of Science, Finland, Finland

E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, in Kona, Hawaii, United States Publisher: Association for the Advancement of Computing in Education (AACE), San Diego, CA

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Abstract

We propose a new computational method to support learning that relies on adaptive exploration of the shortest paths in conceptual networks that have been formed based on co-occurrences of concepts in suitable text samples and selecting concepts corresponding to desired language ability levels and frequency ranking. Relying on Google Web 1T 5-gram database we have built a conceptual co-occurrence network reaching the coverage of 3018 unique concepts and 54 610 unique pairs of co-occurring concepts thus approximately matching with a vocabulary size suggested to be enough for sufficient comprehension and with the highest language ability levels of English Vocabulary Profile. Our method offers to the learner recommendations about suitable exploration paths along the shortest connecting paths between the concepts belonging to a desired learning topic vocabulary, computed with Yen's algorithm. By indicating for each concept the language ability level and the frequency ranking position in British National Corpus enables to prioritize such shortest paths of concepts that most best match the current suitabe comprehension level of the learner. Our preliminary experiment showed that the method can pedagogically intuitively support cumulative adoption of knowledge in the context of study entities belonging to a core curriculum.

Citation

Lahti, L. (2015). Educational exploration along the shortest paths in conceptual networks based on co-occurrence, language ability levels and frequency ranking. In Proceedings of E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 31-36). Kona, Hawaii, United States: Association for the Advancement of Computing in Education (AACE). Retrieved May 31, 2023 from .

© 2015 Association for the Advancement of Computing in Education (AACE)

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  1. Nation, P., & Waring, R. (1997). Vocabulary size, text coverage, and word lists. In Schmitt, N., & McCarthy, M. (eds.), Vocabulary: Description, Acquisition, Pedagogy. Cambridge University Press, New York, USA, 6-19.
  2. Duyck, W., Vaderelst, D., Desmet, T., & Hartsuiker, R. (2008). The frequency effect in second-language visual word recognition. Psychonomic Bulletin& Review, 15(4), 850-855.
  3. Anderson, J. (1983). A spreading activation theory of memory. Journal of verbal learning and verbal behavior. 22(3), 261295.
  4. Dix, A., Kafifori, A., Lepouras, G., Vassilakis, C., & Shabir, N. (2010). Spreading activation over ontology-based resources: from personal context to Web scale reasoning. International Journal of Semantic Computing (IJSC), 4(1), 59-102.
  5. Ingawale, M., Dutta, A., Roy, R., & Seetharaman, P. (2009). The small wordls of Wikipedia: implications for growth, quality and sustainability of collaborative knowledge networks. Proc. Americas Conference on Infromation Systems (AMCIS 2009).
  6. Wang, J., Zuo, X., & He, Y. (2010). Graph-based network analysis of resting-state functional MRI. Frontiers in Systems Neuroscience, 4:16.
  7. Masucci, A., Kalampokis, A., Eguíluz, V., & Hernández-García, E. (2011). Wikipedia information flow analysis reveals the scale-free architecture of teh semantic space. Public Library of Science ONE (PLoS ONE), 6(2), e17333.
  8. Bullmore, E., & Sporns, O. (2009). Complex brain networks: graph theoretical analysis of structural and functional systems. Nature Reviews Neuroscience, 10(3), 186-198.
  9. Morais, A., Olsson, H., & Schooler, L. (2013). Mapping the structure of semantic memory. Cognitive Science, 37, 125-145.
  10. Redero-Merino, L., Fernández Anta, A., López, L., & Cholvi, V. (2010). Perforamance of random walks in one-hop replication networks. Computer Networks, 54, 781-796.
  11. Capel, A. (2013). Completing the English Vocabulary Profile: C1 and C2 vocabulary. English Profile Journal, 3, e1. Online database of English Vocabulary Profile provided by Cambridge University Press available at http://vocabulary.englishprofile.org/dictionary//word-list/uk/a1_c2/A.Leech,G.,Rayson,P.,&Wilson,A.(2001).WordfrequenciesinwrittenandspokenEnglish:basedontheBritishNationalCorpus.Longman,London,UK.ISBN0582-32007-0.(Acompanionwebsite:http://ucrel.lancs.ac.uk/bncfreq/flists.html ;
  12. Yen, J. (1971). Finding the k shortest loopless paths in a network. Management Science, 17(11), 712-716.
  13. Finnish National Board of Education (2014). Finnish national core curriculum for compulsory basic education (in Finnish). Http://www.oph.fi/download/163777_perusopetuksen_opetussuunnitelman_perusteet_2014.pdf

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