Abstract
In this chapter, we outline principles and practices for designing future education in the biomedical and life sciences that aim to support the development of adaptive expertise. We draw on examples from training in health professions and literature from cognitive psychology and learning sciences to make the case for a new way forward, emphasizing the development of the learner as a future expert. This goal of developing adaptive experts concurrently promotes both applying learners’ past knowledge to solve known problems and preparing learners to create new knowledge and solutions when faced with novelty, complexity, and ambiguity. We propose that when instruction is designed to support the ongoing development of adaptive expertise, learners benefit longer term, both in terms of retention and application/transfer of knowledge. We argue that rather than an exclusively process-based focus on the learner experience and the modality by which instruction is delivered, educators should approach curriculum design with a lens that values outcomes of learning (e.g., clinical competencies) and underlying mechanisms that must be invoked to achieve these desired outcomes. As an example, when the biomedical sciences are explicitly integrated with clinical instruction, learners develop better conceptual knowledge, which will be retained long term and utilized when learning novel but related concepts or when solving future problems. When the purpose of education is redirected to focus on desired outcomes of learner, educators can shift their attention to incorporating evidence-informed processes into their curricula that can have profound effects on student learning.
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References
Adesope, O. O., Trevisan, D. A., & Sundararajan, N. (2017). Rethinking the use of tests: A meta-analysis of practice testing. Review of Educational Research, 87(3), 659–701.
Agarwal, P. K. (2019). Retrieval practice & Bloom’s taxonomy: Do students need fact knowledge before higher order learning? Journal of Educational Psychology, 111(2), 189–209.
Association of Faculties of Medicine of Canada. (2010). The future of medical education in Canada (FMEC): A collective vision for MD education. https://afmc.ca/sites/default/files/pdf/2010-FMEC-MD_EN.pdf. Accessed 3 Nov 2020.
Auerbach, L., Santen, S. A., Cutrer, W. B., Daniel, M., Wilson-Delfosse, A. L., & Roberts, N. K. (2020). The educators’ experience: Learning environments that support the master adaptive learning. Medical Teacher, 42(11), 1270–1274.
Baghdady, M., Carnahan, H., Lam, E. W. N., & Woods, N. N. (2013). Integration of basic sciences and clinical sciences in oral radiology education for dental students. Journal of Dental Education, 77(6), 757–763.
Baghdady, M., Carnahan, H., Lam, E. W. N., & Woods, N. N. (2014). Test-enhanced learning and its effect on comprehension and diagnostic accuracy. Medical Education, 48(2), 181–188.
Benner, P., Sutphen, M., Leonard, V., & Day, L. (2010). Educating nurses: A call for radical transformation. The Carnegie Foundation for the Advancement of Teaching.
Bereiter, C., & Scardamalia, M. (1993). Surpassing ourselves: An inquiry into the nature and implications of expertise. Open Court.
Black, P., & Wiliam, D. (1998). Inside the black box: Raising standards through classroom assessment. Phi Delta Kappan, 80(20), 139–148.
Bransford, J. D., Brown, A. L., & Cocking, R. R. (2000). How people learn: Brain, mind, experience, and school. National Academy Press.
Bransford, J. D., & Schwartz, D. L. (1999). Rethinking transfer: A simple proposal with multiple implications. Review of Research in Education, 24(1), 61–100.
Brydges, R., Tran, J., Goffi, A., Lee, C., Miller, D., & Mylopoulos, M. (2020). Resident learning trajectories in the workplace: A self-regulated learning analysis. Medical Education, 54(12), 1120–1128.
Chamberland, M., Mamede, S., St-Onge, C., Rivard, M.-A., Setrakian, J., Lévesque, A., Lanthier, L., Schmidt, H. G., & Rikers, R. M. J. P. (2013). Students’ self-explanations while solving unfamiliar cases: The role of biomedical knowledge. Medical Education, 47(11), 1109–1116.
Chamberland, M., Mamede, S., St-Onge, C., Setrakian, J., Bergeron, L., & Schmidt, H. (2015a). Self- explanation in learning clinical reasoning: The added value of examples and prompts. Medical Education, 49(2), 193–202.
Chamberland, M., Mamede, S., St-Onge, C., Setrakian, J., & Schmidt, H. G. (2015b). Does medical students’ diagnostic performance improve by observing examples of self-explanation provided by peers or experts. Advances in Health Sciences Education, 20(4), 981–993.
Chamberland, M., St-Onge, C., Setrakian, J., Lantheir, L., Bergeron, L., Bourget, A., Mamed, S., Schmidt, H., & Rikers, R. (2011). The influence of medical students’ self-explanations on diagnostic performance. Medical Education, 45(7), 688–695.
Chaudhary, Z. K., Mylopoulos, M., Barnett, R., Sockalingam, S., Hawkins, M., O’Brien, J. D., & Woods, N. N. (2019). Reconsidering basic: Integrating social and behavioral sciences to support learning. Academic Medicine, 94(11S), S73–S78.
Cheung, J. J. H., Kulasegaram, K. M., Woods, N. N., Moulton, C.-A., Ringsted, C. V., & Brydges, R. (2018). Knowing how and knowing why: Testing the effect of instruction designed for cognitive integration on procedural skills transfer. Advances in Health Sciences Education, 23(1), 61–74.
Chi, M. T., Leeuw, N. D., Chiu, M.-H., & LaVancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18(3), 439–477.
Chi, M. T. H. (2000). Self-explaining expository texts: The dual process of generating inferences and repairing mental models. In R. Glaser (Ed.), Advances in instructional psychology (pp. 161–238). Lawrence Erlbaum Associates.
College of Nurses of Ontario. (2018). Entry-to-practice competencies for registered nurses. https://www.cno.org/globalassets/docs/reg/41037-entry-to-practice-competencies-2020.pdf. Accessed 27 Nov 2020.
de Bruin, A. B. H. (2020). Debunking myths in medical education: The science of refutation. Medical Education, 54(1), 6–8.
Dean, D., & Kuhn, D. (2006). Direction instruction vs. discovery: The long view. Science Education, 91, 384–397.
DeCaro, M. S., & Rittle-Johnson, B. (2012). Exploring mathematics problems prepares children to learn from instruction. Journal of Experimental Child Psychology, 113(4), 552–568.
Derry, S. J., Hmelo-Silver, C. E., Nagarajan, A., Chemobilsky, E., & Beitzel, B. (2006). Cognitive transfer revisited: Can we exploit new media to solve old problems on a large scale? Journal of Educational Computing Research, 35(2), 145–162.
Dobson, J., Linderholm, T., & Perez, J. (2018). Retrieval practice enhances the ability to evaluate complex physiology information. Medical Education, 52(5), 513–525.
Dochy, F., Segers, M., Van den Bossche, P., & Gijebs, D. (2003). Effects of problem-based learning: A meta-analysis. Learning and Instruction, 13(5), 533–568.
Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14(1), 4–58.
Finnerty, E. P., Chauvin, S., Bonaminio, G., Andrews, M., Carroll, R. G., & Pangaro, L. N. (2010). Flexner revisited: The role and value of the basic sciences in medical education. Academic Medicine, 85(2), 349–355.
Frank, J. R., Snell, L., & Sherbino, J. eds. (2015). CanMEDS 2015 physician competency framework. Royal College of Physicians and Surgeons of Canada. http://canmeds.royalcollege.ca/uploads/en/framework/CanMEDS%202015%20Framework_EN_Reduced.pdf. Accessed 27 Nov 2020.
Goldszmidt, M., Minda, J. P., Devantier, S. L., Skye, A. L., & Woods, N. N. (2012). Expanding the basic science debate: The role of physics knowledge in interpreting clinical findings. Advances in Health Sciences Education, 17(4), 547–555.
Grainger, R., Liu, Q., & Geertshuis, S. (2021). Learning technologies: A medium for the transformation of medical education? Medical Education, 55(1), 23–29.
Heeneman, S., Oudkerk, P. A., Schuwirth, L. W. T., van der Vleuten, C. P. M., & Driessen, E. W. (2015). The impact of programmatic assessment on student learning: Theory versus practice. Medical Education, 49(5), 487–498.
Hendrick, C., & Heal, J. (2020). Just because they are engaged, it doesn’t mean that they are learning. Retrieved March 1, 2021, from https://impact.chartered.college/article/just-because-theyre-engaged-doesnt-mean-learning/
Hmelo, C. E. (1998). Problem-based learning: Effects on the early acquisition of cognitive skill in medicine. Journal of the Learning Sciences, 7(2), 173–236.
Howard-Jones, P. A., Jay, T., & Galeano, L. (2020). Professional development on the science of learning and teachers’ performative thinking – A pilot study. Mind, Brain, and Education, 14(3), 267–278.
Irby, D. M., Cooke, M., & O’Brien, B. C. (2010). Calls for reform of medical education by the Carnegie Foundation for the Advancement of Teaching: 1910 and 2010. Academic Medicine, 85(2), 220–227.
Kalyuga, S., & Renkl, A. (2010). Expertise reversal effect and its instructional implications: Introduction to the special issue. Instructional Science, 38(3), 209–215.
Kalyuga, S., Rikers, R., & Paas, F. (2012). Educational implications of expertise reversal effects in learning and performance of complex cognitive and sensorimotor skills. Educational Psychology Review, 24(2), 313–337.
Kapur, M. (2008). Productive failure. Cognition and Instruction, 26(3), 379–424.
Kapur, M. (2014). Productive failure in learning math. Cognitive Science, 38(5), 1008–1022.
Kapur, M. (2016). Examining productive failure, productive success, unproductive failure, and unproductive success in learning. Educational Psychologist, 51(2), 289–299.
Kapur, M., & Bielaczyc, K. (2012). Designing for productive failure. Journal of the Learning Sciences, 21(1), 45–83.
Koens, F., Custers, E. J. F. M., & ten Cate, O. T. J. (2006). Clinical and basic science teachers’ opinions about the required depth of biomedical knowledge for medical students. Medical Teacher, 28(3), 234–238.
Koens, F., Rademakers, J. J. D. J. M., & ten Cate, O. T. J. (2005). Validation of core medical knowledge by postgraduates and specialists. Medical Education, 39(9), 911–917.
Kromann, C. B., Jensen, M. L., & Ringsted, C. (2009). The effect of testing on skills learning. Medical Education, 43(1), 21–27.
Kulasegaram, K., Myolopoulos, M., Tonin, P., Bernstein, S., Bryden, P., Law, M., Lazor, J., Pittini, R., Sockalingam, S., Tait, G. R., & Houston, P. (2018). The alignment imperative in curriculum renewal. Medical Teacher, 40(5), 443–448.
Kulasegaram, K. M., Manzone, J. C., Ku, C., Skye, A., Wadey, V., & Woods, N. N. (2015). Cause and effect: Testing a mechanism for cognitive integration of basic science. Academic Medicine, 90, S63–S69.
Kulasegaram, K. M., Martimianakis, M. A., Mylopoulos, M., Whitehead, C. R., & Woods, N. N. (2013). Cognition before curriculum: Rethinking the integration of basic science and clinical learning. Academic Medicine, 88(10), 1578–1585.
Kulasegaram, K. M., & Rangachari, P. K. (2018). Beyond “formative”: Assessment to enrich student learning. Advances in Physiology Education, 42(1), 5–14.
Larsen, D. P., Butler, A. C., Lawson, A. L., & Roediger, H. L., III. (2013a). The importance of seeing the patient: Test-enhanced learning with standardized patients and written tests improves clinical application of knowledge. Advances in Health Sciences Education, 18(3), 409–425.
Larsen, D. P., Butler, A. C., & Roediger, H. L., III. (2013b). Comparative effects of test-enhanced learning and self-explanation on long-term retention. Medical Education, 47(7), 674–682.
Leppink, J., Broers, N. J., Imbos, T., van der Vleuten, C. P. M., & Berger, M. P. F. (2012). Prior knowledge moderates instructional effects on conceptual understanding of statistics. Educational Research and Evaluation, 18(1), 37–51.
Lisk, K., Agur, A. M. R., & Woods, N. N. (2016). Exploring cognitive integration of basic science and its effect on diagnostic reasoning in novices. Perspectives on Medical Education, 5(3), 147–153.
Lisk, K., Agur, A. M. R., & Woods, N. N. (2017). Examining the effect of self-explanation on cognitive integration of basic and clinical sciences in novices. Advances in Health Sciences Education, 22(5), 1071–1083.
Ludmerer, K. M. (1999). Time to Heal: American medical education from the turn of the century to the era of managed care. Oxford University Press.
Murphy, G. L., & Medin, D. L. (1985). The role of theories in conceptual coherence. Psychology Review, 92(3), 289–314.
Mylopoulos, M., Brydges, R., Woods, N. N., Manzone, J., & Schwartz, D. L. (2016). Preparation for future learning: A missing competency in health professions education? Medical Education., 50(1), 115–123.
Mylopoulos, M., Kulasegaram, M., & Woods, N. N. (2018). Developing the experts we need: Fostering adaptive expertise through education. Journal of Evaluation in Clinical Practice., 24(3), 674–677.
Mylopoulos, M., & Woods, N. N. (2009). Having our cake and eating it too. Seeking the best of worlds in expertise research. Medical Education, 43(5), 406–413.
Mylopoulos, M., & Woods, N. N. (2014). Preparing medical students for future learning using basic science instruction. Medical Education, 48(7), 667–673.
Park, D., Gunderson, E. A., Tsukayama, E., Levine, S. C., & Beilock, S. L. (2016). Young children’s motivational frameworks and math achievement: Relation to teacher-reported instructional practices, but not teach theory of intelligence. Journal of Education Psychology, 108(3), 200–313.
Patel, V. L., & Groen, G. J. (1986). Knowledge based solution strategies in medical reasoning. Cognitive Science., 10(1), 91–116.
Patel, V. L., Groen, G. J., & Scott, H. M. (1988). Biomedical knowledge in explanations of clinical problems by medical students. Medical Education, 22(5), 398–406.
Paul, G., Hinman, G., Dottl, S., & Passon, J. (2009). Academic development: A survey of academic difficulties experienced by medical students and support services provided. Teaching and Learning in Medicine, 21(3), 254–260.
Peixoto, J. M., Mamede, S., de Faria, R. M. D., Moura, A. S., Santos, S. M. E., & Schmidt, H. G. (2017). The effect of self-explanation of pathophysiological mechanisms of diseases on medical students’ diagnostic performance. Advances in Health Sciences Education, 22(5), 1183–1197.
Postsecondary Education Quality Assessment Board. (2020). Manual for public organizations (including ontario colleges). http://www.peqab.ca/Publications/Handbooks%20Guidelines/MANUAL_COLLEGES_PUBLICS%20November2020.pdf. Accessed 1 Oct 2020.
Rey, G. D., & Fischer, A. (2013). The expertise reversal effect concerning instructional explanations. Instructional Science, 41, 407–429.
Roediger, H. L., & Karpicke, J. D. (2006). The power of testing memory: Basic research and implications for educational practice. Perspectives on Psychological Science, 1(3), 181–276.
Schuwirth, L. W. T., & Van der Vleuten, C. P. M. (2011). Programmatic assessment: From assessment of learning to assessment for learning. Medical Teacher, 33(6), 478–485.
Schwartz, D., & Bransford, J. D. (1998). A time for telling. Cognition and Instruction, 16(4), 475–5223.
Schwartz, D. L., Bransford, J. D., & Sears, D. (2005). Efficiency and innovation in transfer. In J. P. Mestre (Ed.), Transfer of learning from a modern multidisciplinary perspective (pp. 1–52). Information Age Publishing.
Schwartz, D. L., Chase, C. C., Oppezzo, M. A., & Chin, D. B. (2011). Practicing versus inventing with contrasting cases: The effects of telling first on learning and transfer. Journal of Educational Psychology, 103(4), 759–775.
Schwartz, D. L., Cheng, K. M., Salehi, S., & Wieman, C. (2016). The half empty questions for socio-cognitive interventions. Journal of Educational Psychology, 108(3), 397–404.
Schwartz, D. L., & Martin, T. (2004). Inventing to prepare for future learning: The hidden efficiency of encouraging original student production in statistics instruction. Cognition and Instruction, 22(2), 129–184.
Selvig, D., Holaday, L. W., Purkiss, J., & Hortch, M. (2015). Correlating students’ educational background, study habits, and resource usage with learning success in medical histology. Anatomical Sciences Education, 8(1), 1–11.
Selwyn, N., & Facer, K. (2014). The sociology of education and digital technology: Past, present and future. Oxford Review of Education, 40(4), 482–496.
Squires, D. (2012). Curriculum alignment research suggests that alignment can improve student achievement. The Clearing House: A Journal of Educational Strategies, Issues and Ideas, 85(4), 129–135.
Steenhof, N., Van Woods, N. N., Gerven, P. W. M., & Mylopoulos, M. (2019). Productive failure as an instructional approach to promote future learning. Advances in Health Sciences Education, 24(4), 739–749.
Swan Sein, A., Rashid, H., Meka, J., Amiel, J., & Pluta, W. (2020). Twelve tips for embedding assessment for and as learning practices in a programmatic assessment system. Medical Teacher, 43(3), 300–306.
The Quality Assurance Agency for Higher Education. (2019). Subject benchmark statement for biomedical sciences. https://www.qaa.ac.uk/docs/qaa/subject-benchmark-statements/subject-benchmark-statement-biomedical-sciences.pdf?sfvrsn=2bf2c881_12. Accessed 3 Nov 2020.
Valentine, K. D., & Bolyard, J. J. (2018). Creating a classroom culture that supports productive struggle: Pre-service teachers’ reflections on teaching mathematics.
van Gog, T., & Rummel, N. (2010). Example-based learning: Integrating cognitive and social cognitive research perspectives. Educational Psychology Review, 22(2), 155–174.
Versteeg, M., van Blankenstein, F. M., Putter, H., & Steendijk, P. (2019). Peer instruction improves comprehension and transfer of physiological concepts: A randomized comparison with self-explanation. Advances in Health Sciences Education, 24(1), 151–165.
Whitehead, C. R. (2013). Scientist or science-stuffed? Discourses of science in north American medical education. Medical Education, 47(1), 26–32.
Whitehead, C. R. (2017). Getting off the carousel: de-centring the curriculum in medical education. Perspectives in Medical Education, 6(5), 283–285.
Whitehead, C. R., Hodges, B. D., & Austin, Z. (2013). Captive on a carousel: Discourses of new in medical education 1910-2010. Advances in Health Sciences Education, 18(4), 755–768.
Woods, N. N. (2007). Science is fundamental: The role of biomedical knowledge in clinical reasoning. Medical Education, 41(12), 1173–1177.
Woods, N. N., Brooks, L. R., & Norman, G. R. (2005). The value of basic science in clinical diagnosis: Creating coherence among signs and symptoms. Medical Education, 39(1), 107–112.
Woods, N. N., Brooks, L. R., & Norman, G. R. (2007). The role of biomedical knowledge in diagnosis of difficult clinical cases. Advances in Health Sciences Education, 12(4), 417–426.
Woods, N. N., Neville, A. J., Levinson, A. J., Howey, E. H., Oczkowski, W. J., & Norman, G. R. (2006). The value of basic science in clinical diagnosis. Academic Medicine., 81(10S), S124–S127.
Young, A. J. (1997). I think, therefore I’m motivated: The relations among cognitive strategy use, motivational orientation and classroom perceptions over time. Learning and Individual Differences, 9(3), 249–283.
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Lisk, K., Mylopoulos, M., Woods, N.N. (2022). The Future of Biomedical and Life Science Education: Evidence-Based Future Directions. In: Witchel, H.J., Lee, M.W. (eds) Technologies in Biomedical and Life Sciences Education. Methods in Physiology. Springer, Cham. https://doi.org/10.1007/978-3-030-95633-2_18
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