Interactive visual tools as triggers of collaborative reasoning in entry-level pathology
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Abstract
The growing importance of medical imaging in everyday diagnostic practices poses challenges for medical education. While the emergence of novel imaging technologies offers new opportunities, many pedagogical questions remain. In the present study, we explore the use of a new tool, a virtual microscope, for the instruction and the collaborative learning of pathology. Fifteen pairs of medical students were asked to solve diagnostic tasks in a virtual microscopy learning environment. The students’ collaborative efforts were analysed on the basis of approximately 20 hours of video recordings. Our analyses show how students use the technology as a mediating tool to organize, manipulate and construct a shared visual field, and later, shared understanding of the problem and solutions. Organization of the visual field is done through multimodal referential practices: gestures, three dimensional manipulation of the image and paced inspection of the specimen. Furthermore, we analyse and describe how the aforementioned practices coincide with students’ medical reasoning in this particular learning context. The analysis of medical students’ diagnostic work illustrates the collaborative potential of the virtual microscopy environment and how such interactive tools render the traditional distinction between collaborating around or through computers irrelevant, as even face to face collaboration becomes enacted through technology. Finally, we argue that as technologies develop, understanding the technical side of image production, or any representation, becomes an integral part of the interpretative process. How this knowledge is communicated to the students may play a substantive role in how students learn to interpret medical images.
Keywords
Medical education Collaboration Virtual microscopy Referential practicesNotes
Acknowledgments
We are grateful to the developers and administrators of WebMicroscope, Dr. Johan Lundin and Dr. Mikael Lundin, for the technical support during our research. We also thank Dr. Raymond Bertram for his extensive comments on draft version of this paper. Finally, we are grateful to nurse Hannele Nysten whose practical assistance in organising the data collections has been invaluable to us.
References
- Alač, M. (2008). Working with brain scans: Digital images and gestural interaction in fMRI laboratory. Social Studies of Science, 38, 483–508.CrossRefGoogle Scholar
- Arnseth, H. C., & Ludvigsen, S. (2006). Approaching institutional contexts: Systemic versus dialogic research in CSCL. International Journal of Computer-Supported Collaborative Learning, 1(2), 167–185.CrossRefGoogle Scholar
- Bransford, J. D., & Schwartz, D. L. (1999). Rethinking transfer: A simple proposal with multiple implications. Review of Research in Education, 24, 61–100.Google Scholar
- Cook, D. (2009). The failure of e-learning research to inform educational practice, and what we can do about it. Medical Teacher, 31(2), 158–162.CrossRefGoogle Scholar
- Crook, C., & Light, P. (2002). Virtual society and the cultural practice of study. In S. Woolgar (Ed.), Virtual xociety? Technology, cyberbole, reality (pp. 153–175). Oxford: Oxford University Press.Google Scholar
- Dillenbourg, P., Järvelä S., & Fischer F. (2009). The evolution of research on computer-supported collaborative learning: From design to orchestration. Technology-Enhanced Learning, Part I, 3–19.Google Scholar
- Engeström, Y. (1987). Learning by expanding. Helsinki: Orienta-Konsultit.Google Scholar
- Eva, K. W. (2009). Diagnostic error in medical education: Where wrongs can make rights. Advances in Health Sciences Education, 14, 71–81.CrossRefGoogle Scholar
- Helin, H., Lundin, M., Lundin, J., Martikainen, P., Tammela, T., van der Kwast, T., & Isola, J. (2005). Web-based virtual microscopy in teaching and standardizing Gleason grading. Human Pathology, 36, 281–286.CrossRefGoogle Scholar
- Hindmarsh, J., & Heath, C. (2000). Embodied reference: A study of deixis in workplace interaction. Journal of Pragmatics, 32, 1855–1878.Google Scholar
- Koschmann, T., & Zemel, A. (2009). Optical pulsars and black arrows: Discoveries as occasioned productions. The Journal of the Learning Sciences, 18(2), 200–246. doi: 10.1080/10508400902797966.CrossRefGoogle Scholar
- Krupinski, E. (2010). Current perspectives in medical imaging. Attention, Perception, & Psychophysics, 72(5), 1205–1217.CrossRefGoogle Scholar
- Kushniruk, A. W., Kaufman, R. D., Patel, V. L., Lévesque, Y., & Lottin, P. (1996). Assessment of a computerized patient record system: A cognitive approach to evaluation of an emerging medical technology. M.D. Computing, Computers in Medical Practice, 13, 406–415.Google Scholar
- Kuutti, K., & Kaptelinin, V. (1997). Rethinking cognitive tools: From augmentation to mediation, ct, pp. 31, 2nd International Conference on Cognitive Technology (CT ‘97), 1997.Google Scholar
- Lehtinen, E. (2003). Computer supported collaborative learning: An approach to powerful learning environments. In E. De Corte, L. Verschaffel, N. Entwistle, & J. Van Merriëboer (Eds.), Unraveling basic components and dimensions of powerful learning environments (pp. 35–53). Amsterdam: Elsevier.Google Scholar
- Lehtinen, E. (2012). Learning of complex competences: On the need to coordinate multiple theoretical perspectives. In A. Koskensalo, J. Smeds, A. Huguet, & R. de Cillia (Eds.), Language: Competencies—contact—change. Berlin: LIT Verlag.Google Scholar
- Lesgold, A., Rubinson, H., Feltovich, P., Glaser, R., Klopfer, D., & Wang, Y. (1988). Expertise in a complex skill: Diagnosing x-ray pictures. The nature of expertise. In M. Chi, R. Glaser, & M. Farr (Eds.), The nature of expertise. Hillsdale: Lawrence Erlbaum Associates.Google Scholar
- Lynch, M. (1985). Art and artifact in laboratory science: A study of shop work and shop talk in research laboratory. Boston: Routledge & Kegan Paul.Google Scholar
- Myles-Worsley, M., Johnston, W. A., & Simons, M. A. (1988). The influence of expertise on X-ray image processing. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14, 553–557.CrossRefGoogle Scholar
- Nivala, M., Säljö, R., Rystedt, H., Kronqvist, P., & Lehtinen, E. (2012). Using virtual microscopy to scaffold learning of pathology: A naturalistic experiment on the role of visual and conceptual cues. Instructional Science. doi: 10.1007/s11251-012-9215-8.
- Norman, G., Coblentz, C., Brooks, L., & Babcook, C. (1992). Expertise in visual diagnosis: a review of the literature. Academic Medicine 67(10), 78–83.Google Scholar
- Overdijk, M., van Diggelen, W., Kirschner, P. A., & Baker, M. (2012). Connecting agents and artifacts in CSCL: Towards a rationale of mutual shaping. International Journal of Computer-Supported Collaborative Learning, 7, 193–210.CrossRefGoogle Scholar
- Patel, V. L., Arocha, J. F., & Zhang, J. (2005). Thinking and reasoning in medicine. In K. Holyoak (Ed.), Cambridge handbook of thinking and reasoning. Cambridge: Cambridge University Press.Google Scholar
- Pathak, S. A., Kim, B., Jacobson, M. J., & Zhang, B. H. (2011). Learning the physics of electricity: A qualitative analysis of collaborative processes involved in productive failure. International Journal of Computer-Supported Collaborative Learning, 6(1), 57–73.CrossRefGoogle Scholar
- Ritella, G., & Hakkarainen, K. (2012). Instrumental genesis in technology-mediated learning: From double stimulation to expansive knowledge practices. International Journal of Computer-Supported Collaborative Learning, 7(2), 239–258.CrossRefGoogle Scholar
- Robbins, S. (2010). Robbins and Cotran pathologic basis of disease (8th ed.). Philadelphia: Saunders/Elsevier. ISBN 9781416031215.Google Scholar
- Roschelle, J. (1992). Learning by collaborating: Convergent conceptual change. The Journal of the Learning Sciences, 2(3), 235–276.CrossRefGoogle Scholar
- Roth, W. (2000). From gesture to scientific language. Journal of Pragmatics, 32, 1683–1714.Google Scholar
- Rystedt, H., Ivarsson, J., Asplund, S., Johnsson, A. A., & Båth, M. (2011). Rediscovering radiology: New technologies and remedial action at the worksite. Social Studies of Science, 41(6), 101–125. doi: 10.1177/0306312711423433.CrossRefGoogle Scholar
- Stahl, G., & Hesse, F. (2009) Paradigms of shared knowledge. International Journal of Computer-Supported Collaborative Learning, 4(4), 365–369.Google Scholar
- Säljö, R. (2009). Learning, learning theories and units of analysis in research. Educational Psychologist, 44(3), 202–208.CrossRefGoogle Scholar
- Säljö, R. (2010). Digital tools and challenges to institutional traditions of learning: Technologies, social memory and the performative nature of learning. Journal of Computer Assisted Learning, 26(1), 53–64.CrossRefGoogle Scholar
- Schoultz, J., Säljö, R., & Wyndham, J. (2001). Heavenly talk: Discourse, artifacts and children’s understanding of elementary astronomy. Human Development, 44, 103–118.CrossRefGoogle Scholar
- Wertsch, J. (1998). Mind as action. New York: Oxford University Press.Google Scholar