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Лабораторія СЕТ | Дослідження, статті, розробки | Публікації | CONCEPT MAPS, THEIR APPLICATION TYPES AND METHODS IN INFORMATION AND LEARNING SYSTEMS

CONCEPT MAPS, THEIR APPLICATION TYPES AND METHODS IN INFORMATION AND LEARNING SYSTEMS

CONCEPT MAPS, THEIR APPLICATION TYPES AND METHODS IN INFORMATION AND LEARNING SYSTEMS

Tytenko, S.V. CONCEPT MAPS, THEIR APPLICATION TYPES AND METHODS IN INFORMATION AND LEARNING SYSTEMS. KPI Science News, no. 4, pp. 70–78, 2020. doi: 10.20535/kpisn.2020.4.227090

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Keywords:

concept map, ontologies in education, educational systems, information and learning systems, e-learning, knowledge graph, conceptual graph, lifelong learning

Abstract

Background. The hypermedia environment, which has received a powerful technical infrastructure thanks to the WWW, has led to the study and emergence of new forms and tools of information and educational content presentation. Various methods and means of visualization of educational information increase clarity and facilitate the process of new knowledge perception. Such tools include a wide range of concept maps that have become widespread in many areas related to information technology and education. The challenge here is to find comprehensive solutions that will reduce computing and labor costs for the multifunctional use of concept maps in information and learning systems.

Objective. The work is focused on the review of concept maps, research of preconditions for their origin, analysis of their types and purposes of application in the educational process and learning systems. The main task is to analyze the requirements for interactive concept maps in ontology-oriented information systems to support lifelong learning.

Methods. The use of concept maps in educational systems is based on knowledge modeling, graph theory, ontological modeling of educational content and methods of adaptive e-learning systems. The paper reviews and analyzes the application of concept maps and requirements for them within the information and learning systems.

Results. Concept maps have significant foundation in cognitive and educational psychology, computational linguistics, knowledge engineering and have widespread application in computer supported learning. Concept maps are used as a means of meaningful learning when constructed by students, used to assess knowledge, as well as a means of navigating information resources. Concept maps in educational systems are used to present knowledge to users and serve as interfaces in the process of exploratory search and review of study areas. Information systems provide enrichment of concept maps by means of interactivity, which allows diversifying and expanding its use.

Conclusions. The key requirements for interactive concept maps in information and learning systems are formed, including automation of interactive concept map construction, availability of wide navigation capabilities together with cognitive load control, implementation of interdisciplinary links, media annotation of map elements, complex application of graph interfaces for different parts of the system and adaptation to mobile devices.

References

  1. O. Gagarin and S. Tytenko, “Research and analysis of methods and models of lifelong learning intelligent systems”, Research Bulletin NTUU “KPI”, vol. 6, no. 56, pp. 37–48, 2007.
  2. J.D. Novak and A.J. Cañas, “Theoretical origins of concept maps, how to construct them, and uses in education”, Refl. Educ., vol. 3, no. 1, pp. 29–42, 2007.
  3. N. Chomsky, Aspects of the theory of syntax. Cambridge, MA: M.I.T. Press, 1965.
  4. M.R. Quillian, “Word concepts: A theory and simulation of some basic semantic capabilities”, Behav. Sci., vol. 12, no. 5, pp. 410–430, 1967. doi: 10.1002/bs.3830120511
  5. Example of a semantic network. [Online]. Available: https://en.wikipedia.org/wiki/Semantic_network#/media/File:Semantic_Net.svg
  6. D.P. Ausubel, The Psychology of Meaningful Verbal Learning. New York: Grune & Stratton, 1963.
  7. D.P. Ausubel, “The use of advance organizers in the learning and retention of meaningful verbal material”, J. Educ. Psych., vol. 51, no. 5, pp. 267–272, 1960. doi: 10.1037/h0046669
  8. A.P. Johnson, Essential Learning Theories: Applications to Authentic Teaching Situations. Rowman & Littlefield, 2019.
  9. J.F. Sowa, “Conceptual graphs for a data base interface”, IBM J. Res. Developm., vol. 20, no. 4, pp. 336–357, 1976. doi: 10.1147/rd.204.0336
  10. J.F. Sowa, Conceptual structures: Information processing in mind and machine. Reading, MA: Addison-Wesley, 1984.
  11. J.F. Sowa, “Semantics of conceptual graphs,” in Proc. 17th annual meeting on Association for Computational Linguistics, 1979, pp. 39–44. doi: 10.3115/982163.982175
  12. D.R. Corbett and C. Rouff, “Self optimization using conceptual graphs for NASA autonomous systems,” in Proc. Third IEEE International Workshop on Engineering of Autonomic & Autonomous Systems (EASE`06), 2006. doi: 10.1109/EASE.2006.11
  13. G.F. Luger, Artificial Intelligence: Structures and Strategies for Complex Problem Solving, 5th ed. Pearson, 2005.
  14. D.F. Dansereau, “Node-link mapping principles for visualizing knowledge and information,” in Knowledge and Information Visualization. Lecture Notes in Computer Science, vol. 3426, S-O. Tegran and T. Keller, Eds. Berlin, Heidelberg: Springer, 2005, pp. 61–81. doi: 10.1007/11510154_4
  15. D.F. Dansereau et al. (1993). Mapping new roads to recovery. A self-paced training manual designed for substance abuse counselors and case workers interested in node-link mapping [Online]. Available: https://core.ac.uk/download/pdf/34718088.pdf
  16. T. Buzan, Using both sides of the brain. New York: E.P. Dutton, 1974.
  17. S.V. Tytenko, “Interactive concept maps in ontology-oriented information and learning web-systems”, KPI Sci. News, no. 2, pp. 24–36, 2019. doi: 10.20535/kpi-sn.2019.2.167515
  18. Mindmap sample [Online]. Available: https://assets.xmind.net/www/assets/images/home/home-hero-ui@3x-64881d8d06.png
  19. J.D. Novak, “Concept maps and Vee diagrams: Two metacognitive tools for science and mathematics education”, Instr. Sci., vol. 19, no. 1, pp. 29–52, 1990. doi: 10.1007/BF00377984
  20. J.C. Nesbit and O.O. Adesope, “Learning with concept and knowledge maps: A meta-analysis”, Rev. Educ. Res., vol. 76, no. 3, pp. 413–448, 2006. doi: 10.3102/00346543076003413
  21. I.M. Kinchin et al., “Uncovering types of knowledge in concept maps”, Educ. Sci., vol. 9, no. 2, p. 131, 2019. doi: 10.3390/educsci9020131
  22. S. Puntambekar et al., “Improving navigation and learning in hypertext environments with navigable concept maps”, Human–Comput. Interact., vol. 18, no. 4, pp. 395–428, 2003. doi: 10.1207/s15327051hci1804_3
  23. H. Li et al., “A multi-layer map-oriented resource organization system for web-based self-directed learning combined with community-based learning”, Res. Pract. Technol. Enhanc. Learn., vol. 10, no. 1, 2015. doi: 10. 10.1186/s41039-015-0012-2
  24. M. Eldefrawi et al., “Bootstrapping domain knowledge exploration using conceptual mapping of Wikipedia”, Int. J. Advanc. Comput. Sci. Applicat., vol. 4, no. 8, 2013. doi: 10.14569/IJACSA.2013.040813
  25. R.J. Shavelson et al., “On concept maps as potential “authentic” assessments in Science” CRESST, UCLA, Los Angeles, CA, CSE Techn. Rep. 388, Aug. 1994.
  26. Topic Maps, ISO/IEC 13250, 2002.
  27. A. Valerio et al., “Using automatically generated concept maps for document understanding: A human subjects experiment,” in Fifth International Conf. on Concept Mapping, Valetta, Malta, 2012, pp. 438–445.
  28. T. Falke. “Automatic structured text summarization with concept maps,” Ph.D dissertation, Technische Universität Darmstadt, Hessen, Deutschland, 2019.
  29. B. Sarrafzadeh and E. Lank, “Improving exploratory search experience through hierarchical knowledge graphs,” in Proc. 40th International ACM SIGIR Conf. on Research and Development in Information Retrieval, 2017, pp. 145–154. doi: 10.1145/3077136.3080829
  30. Semantic Portal [Online]. Available: http://semantic-portal.net
  31. A. Handler et al., “Summarizing relationships for interactive concept map browsers,” in Proc. of the 2nd Workshop on New Frontiers in Summarization, 2019, pp. 111–115. doi: 10.18653/v1/D19-5414
  32. Gw-J. Hwang et al., “An interactive concept map approach to supporting mobile learning activities for natural science courses”, Comput. & Educ., vol. 57, no. 4, pp. 2272–2280, 2011. doi: 10.1016/j.compedu.2011.06.011
  33. T. Sumner et al., “Linking learning goals and educational resources through interactive concept map visualizations”, Int. J. Digit. Librar., vol. 5, no. 1, pp. 18–24. 2005. doi: 10.1007/s00799-004-0112-x
  34. M. Roser et al. (2015). Internet [Online]. Available: https://ourworldindata.org/internet

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