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MISSED – Studying Students’ Development of Misconceptions in Hybrid Courses

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8038))

Abstract

We implemented a methodology for studying how learners develop misconceptions during the situated experience of teaching and learning as well as during the situated experience of cognitive and behavioral expression of what has been learned during real-world application. This methodology now has been embedded into software-hardware platforms suitable for use by learning management systems (LMS) and massive open online courses (MOOCs). These types of platforms together constitute an educational environment we call the MISSED – Misconception Instantiation as Students Study Educational Domains. MISSED can be used to assess learners’ conceptual and performance competencies in ways allowing cognitive and behavioral mapping that reveals patterns of misconception development.

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References

  1. Tashiro, J., Hung, P.C.K., Martin, M.V.: Evidence-Based Educational Practices and a Theoretical Framework for Hybrid Learning. In: Kwan, R., Fong, J., Kwok, L.-F., Lam, J. (eds.) ICHL 2011. LNCS, vol. 6837, pp. 51–72. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  2. Tashiro, J., Hung, P.C.K., Martin, M.V.: ROAD-MAP for Educational Simulations and Serious Games. In: Tsang, P., Cheung, S.K.S., Lee, V.S.K., Huang, R. (eds.) ICHL 2010. LNCS, vol. 6248, pp. 186–204. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  3. Garcia-Ruiz, M.A., Tashiro, J., Kapralos, B., Vargas Martin, M.: Crouching Tangents, Hidden Danger: Assessing Development of Dangerous Misconceptions Within Serious Games For Health care Education. In: Hai-Jew, S. (ed.) Virtual Immersive and 3D Learning Spaces: Emerging Technologies and Trends, pp. 269–306. IGI Global, Hershey (2011)

    Google Scholar 

  4. National Research Council: How Students Learn: History, Mathematics, and Science in the Classroom. National Academy Press, Washington, DC (2005)

    Google Scholar 

  5. American Association for the Advancement of Science: Invention and Impact: Building Excellence in Undergraduate Science, Technology, Engineering and Mathematics (STEM) education. American Association for the Advancement of Science, Washington, DC (2004)

    Google Scholar 

  6. Federation of American Scientists: Summit on Educational Games – Harnessing the power of Video Games for Learning. Federation of American Scientists, Washington, DC (2006)

    Google Scholar 

  7. Rudak, L., Sidor, D.: Taxonomy of E-courses. In: Islander, M., Kapila, V., Karim, M.A. (eds.) Technological Developments in Education and Automation, pp. 275–280. Springer Science and Business Media, New York (2010)

    Chapter  Google Scholar 

  8. Gasparini, I., Eyharabide, V., Schiaffino, S., Pimenta, M.S., Amandi, A., de Oliveira, J.P.M.: Improving user profiling for a richer personalization: Modeling context in e-Learning. In: Graf, S., Lin, F., McGreal, R. (eds.) Intelligent and Adaptive Learning Systems: Technology Enhanced Support for Learners and Teachers, pp. 182–197. IGI Information Science Reference, Hershey (2012)

    Google Scholar 

  9. Khribi, M.K., Jemni, M., Nasraoui, O.: Automatic Recommendations for e-Learning personalization based on web usage mining techniques and information retrieval. Educational Technology & Society 12(4), 30–42 (2009)

    Google Scholar 

  10. Tan, J., Hung, P., Dohan, M., Trojer, T., Farwick, M., Tashiro, J.: Gateway to Quality Living for the Elderly: Charting an Innovative Approach to Evidence-based E-Health Technologies For Serving the Chronically Ill. In: Proceedings of the 13th IEEE International Conference on Computational Science and Engineering, CSE-2010, Hong Kong, December 11-13, pp. 11–13 (2010)

    Google Scholar 

  11. Kelly, M., Ort, M., Semken, S., Tashiro, J.: Virtual reality excursions – Exploring earth’s environment. Prentice-Hall, Upper Saddle River (2000)

    Google Scholar 

  12. Fulcher, G.: Virtual Medical Office for Bonwit-West’s Clinical Procedures for Medical Assistants, 6th edn. Elsevier-Saunders, Philadelphia (2007)

    Google Scholar 

  13. Mathers, D.: Virtual Clinical Excursions – For Black and Hawks Medical-Surgical Nursing: Clinical Management for Positive Outcomes, 7th edn. PAL Elsevier Saunders, Philadelphia (2006)

    Google Scholar 

  14. Tashiro, J.T., Sullins, E.S., Long, G.: Virtual Clinical Excursions for Fundamental Concepts and Skills for Nursing. St. Louis, Mosby (2003)

    Google Scholar 

  15. Sorden, S.D.: A Cognitive Approach to Instructional Design for Multimedia Learning. Informing Science Journal 8, 263–279 (2005)

    Google Scholar 

  16. Mayer, R.E., Fennell, S., Farmer, L., Campbell, J.: A Personalization Effect in Multimedia Learning: Students Learn Better When Words Are in Conversational Style Rather Than Formal Style. Journal of Educational Psychology 96(2), 389–395 (2004)

    Article  Google Scholar 

  17. Tashiro, J., Hung, P.C.K.: Method for Assessing an Individual’s Physical and Psychosocial Abilities. No. 61/549,5789. U.S. Patent and Trademark Office, Washington, DC (2011)

    Google Scholar 

  18. Tashiro, J., Choate, D.: Method to assess a Person’s Knowledge of a Subject Area. US Patent (pending) No. 60/521,329. U.S. Patent and Trademark Office, Washington, DC (2004)

    Google Scholar 

  19. Martin, L., Haskard-Zolnierek, K., DiMatteo, M.R.: Health Behavior Change and Treatment Adherence: Evidence-based Guidelines for Improving Healthcare. Oxford University Press, New York (2010)

    Google Scholar 

  20. Prochaska, J.O., Redding, C.A., Evers, K.E.: The Transtheoretical Model and stages of change. In: Glanz, K., Rimer, B., Viswanath, K. (eds.) Health Behavior and Health Education, pp. 97–121. Jossey-Bass, San Francisco (2008)

    Google Scholar 

  21. DiMatteo, M.R., DiNicola, D.: Achieving Patient Compliance. Pergamon Press, New York (1982)

    Google Scholar 

  22. Fishbein, M., Hennessey, M., Kamb, M., Bolan, G., Hoxworth, T., Latesta, M., et al.: Using Intervention Therapy to Model Factors Influencing Behavior Change: Project Respect. Evaluation and Health Professions 24(4), 363–384 (2001)

    Article  Google Scholar 

  23. Bensley, R., Mercer, N., Brusk, J., Underhile, R., Rivas, J., Anderson, J., et al.: The e-Health Behavior Management Model: A Stage-based Approach to Behavior Change and Management. Preventing Chronic Disease 1(4), A14 (2004)

    Google Scholar 

  24. Baranowski, T., Cullen, K., Nicklas, T., Thompson, D., Baranowski, J.: Are Current Health Behavioral Change Models Helpful in Guiding Prevention of Weight Gain Efforts? Obesity Research (Suppl.), 23S–43S (2003)

    Google Scholar 

  25. Leventhal, H., Halm, E., Horowitz, C., Leventhal, E., Ozakinci, G.: Living with chronic Illness: A Contextualized, Self-Regulation Approach. In: Sutton, S., Baum, A., Johnston, M. (eds.) Handbook of Health Psychology, pp. 159–194. Sage Publications, London (2004)

    Google Scholar 

  26. Fernandez, A., Regts, M., Tashiro, J., Vargas Martin, M.: Neural network prediction model for a digital media learning environment. In: International Conference on Information and Knowledge Engineering, Las Vegas, USA, July 16-19 (2012)

    Google Scholar 

  27. Fernandez, A.: Cluster techniques and prediction models for a digital media learning environment. Thesis: Master of Computer Science. University of Ontario Institute of Technology (August 2012)

    Google Scholar 

  28. Regts, M., Fernandez, A., Vargas Martin, M., Tashiro, J.: Methodology for studying health science students’ development of misconceptions. In: International Conference on Advances in Databases, Knowledge, and Data Applications, Reunion Island, March 1-5, pp. 112–119 (2012)

    Google Scholar 

  29. Regts, M.: A look at simulated online learning environments and undergraduate health science students’ development of misconceptions. Thesis: Master of Health Informatics. University of Ontario Institute of Technology (December 2012)

    Google Scholar 

  30. De Feijter, J.M., De Grave, W.S., Muijtjens, A.M., Scherpbier, A.J.J.A., Koopmans, R.P.: a comprehensive overview of medical errors in hospitals using incident-reporting systems, patient complaints and chart review of inpatient deaths. PLoS One 7(2), e31125 (2012)

    Article  Google Scholar 

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© 2013 Springer-Verlag Berlin Heidelberg

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Tashiro, J., Vargas Martin, M., Hung, P.C.K. (2013). MISSED – Studying Students’ Development of Misconceptions in Hybrid Courses. In: Cheung, S.K.S., Fong, J., Fong, W., Wang, F.L., Kwok, L.F. (eds) Hybrid Learning and Continuing Education. ICHL 2013. Lecture Notes in Computer Science, vol 8038. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39750-9_34

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  • DOI: https://doi.org/10.1007/978-3-642-39750-9_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39749-3

  • Online ISBN: 978-3-642-39750-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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