Exploring Case Specificity in Medical Students’ Clinical Reasoning PROCEEDING
Tenzin Doleck, McGill University, Canada ; Eric Poitras, University of Utah, United States ; Susanne Lajoie, McGill University, Canada
E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, in Vancouver, British Columbia, Canada ISBN 978-1-939797-31-5 Publisher: Association for the Advancement of Computing in Education (AACE), Chesapeake, VA
Advances in educational technology have provided various promising solutions for yielding useful insights about learning from learner-system interaction data Previous research has suggested the existence of case-specificity in clinical reasoning (Doleck, Jarrell, Poitras, Chaouachi, & Lajoie, 2016; Fitzgerald et al, 1994) Thus, in the present study we examine the data streams generated by learners’ interactions with a medical learning system called BioWorld, to detect such a phenomenon
Doleck, T., Poitras, E. & Lajoie, S. (2017). Exploring Case Specificity in Medical Students’ Clinical Reasoning. In J. Dron & S. Mishra (Eds.), Proceedings of E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 572-577). Vancouver, British Columbia, Canada: Association for the Advancement of Computing in Education (AACE). Retrieved November 16, 2018 from https://www.learntechlib.org/primary/p/181232/.
© 2017 Association for the Advancement of Computing in Education (AACE)
- Berland, M., Baker, R., & Blikstein, P. (2014). Educational Data Mining and Learning Analytics: Applications to Constructionist Research. Technology, Knowledge And Learning, 19(1-2), 205-220.
- Doleck, T., Basnet, R., Poitras, E., & Lajoie, S. (2015). Mining learner–system interaction data: implications for modeling learner behaviors and improving overlay models. Journal Of Computers In Education, 2(4), 421-447.
- Feng, M., Heffernan, N., & Koedinger, K. (2009). Addressing the assessment challenge with an online system that tutors as it assesses. User Modeling And User-Adapted Interaction, 19(3), 243-266.
- Gobert, J., Sao Pedro, M., Raziuddin, J., & Baker, R. (2013). From Log Files to Assessment Metrics: Measuring Students' Science Inquiry Skills Using Educational Data Mining. Journal Of The Learning Sciences, 22(4), 521-563.
- Hadwin, A., Nesbit, J., Jamieson-Noel, D., Code, J., & Winne, P. (2007). Examining trace data to explore selfregulated learning. Metacognition And Learning, 2(2-3), 107-124. Http://dx.doi.org/10.1007/s11409-007-9016-7Hwang,H.(2008).VisualGSCA1.0-A graphical user interface software program for generalized structured component analysis. In K. Shigemasu, A. Okada, T. Imaizumi, & T. Hoshino (Eds.) New Trends in Psychometrics (pp. 111-120). Tokyo: University Academic Press.
- Hwang, H. (2011). GeSCA User’s Manual. Retrieved from http://www.sem-gesca.org/GeSCA_Manual.pdf Hwang, H. & Takane, Y. (2004). Generalized structured component analysis. Psychometrika, 69(1), 81-99.
- Lajoie, S. (2003). Transitions and Trajectories for Studies of Expertise. Educational Researcher, 32(8), 21-25.
- Naismith, L. (2013). Examining motivational and emotional influences on medical students’ attention to feedback in a technology-rich environment for learning clinical reasoning (Unpublished doctoral dissertation). McGill University, Canada.
- Norman, G. (2005). Research in clinical reasoning: past history and current trends. Medical Education, 39(4), 418427.
- Poitras, E.G., Lajoie, S.P., Doleck, T., & Jarrell, A. (2016). Subgroup Discovery with User Interaction Data: An Empirically Guided Approach to Improving Intelligent Tutoring Systems. Educational Technology& Society,19(2), 204–214.
- Romero, C., & Ventura, S. (2007). Educational data mining: A survey from 1995 to 2005. Expert Systems With Applications, 33(1), 135-146.
- Segedy, J., Kinnebrew, J., & Biswas, G. (2015). Using Coherence Analysis to Characterize Self-Regulated Learning Behaviours in Open-Ended Learning Environments. Journal of Learning Analytics, 2(1), 13-48.
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