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From Psychology Laboratory to Student Development: Untangling Momentary Engagement from Longer-Term Engagement in Bioscience Education

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Technologies in Biomedical and Life Sciences Education

Part of the book series: Methods in Physiology ((METHPHYS))

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Abstract

Student engagement and its measurement remain contested by different research disciplines that aim to evaluate education. In computer analytics, engagement is momentary, and longer-term engagement arises from accumulated momentary engagement. By contrast, policymakers see engagement as fundamentally longer-term, emerging from the student’s identification and sense of belonging. The definition of engagement is a long-debated topic, and this lack of agreement is a major problem for the field. Behavioral engagement is dedicated time and effort, which may be necessary and is certainly contributory to the outcomes of learning and development. Various engagement theories have included behavioral, cognitive, emotional, and social elements. Some engagement paradigms have subsumed other contributors to learning, such as motivation, cognitive strategies, and social communities. Despite much recent progress in our understanding of learning science, the relationship of the benefits of momentary to longer-term engagement is insufficiently researched. We and others have attempted to tease apart engagement’s causes and consequences. Some technological approaches (e.g., gamification) boost momentary engagement to kindle longer-term engagement; this may be the mechanism of active learning and frequent formative assessments. The opposite pedagogical approach uses longer-term, internalized motivation as a substrate that allows consistent triggering of momentary engagement by traditional pedagogies. Whereas metrics of behavioral engagement are sometimes agreed upon, the emotional-cognitive-behavioral meta-construct of engagement may cause more confusion than clarity when evaluating outcomes such as development and learning. Thus, using engagement as an outcome, instead of measuring learning and development directly, solves some policy problems, but it exacerbates many scientific problems regarding mechanism.

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Notes

  1. 1.

    Note that in this text “necessary” and “sufficient” are not absolute or binary but act in degrees. They could be called “facilitatory,” but the distinguishing features in this model would be lost.

References

  • ACER. (2011). Student engagement briefing, 2011 AUSSE survey. Australian Council for Educational Research. https://www.acer.org/files/AUSSE_2011-Australasia-University-Engagement-Briefing.pdf

    Google Scholar 

  • Allen, D. (1999). Desire to finish college: An empirical link between motivation and persistence. Research in Higher Education, 40(4), 461–485.

    Article  Google Scholar 

  • Angelo, T. A., & Cross, K. P. (1993). Classroom assessment techniques (2nd ed., pp. 119–158). Jossey Bass.

    Google Scholar 

  • Aparicio, G., Iturralde, T., & Maseda, A. (2021). A holistic bibliometric overview of the student engagement research field. Journal of Further and Higher Education, 45(4), 540–557. https://doi.org/10.1080/0309877X.2020.1795092

    Article  Google Scholar 

  • Ashwin, P., & McVitty, D. (2015). The meanings of student engagement: Implications for policies and practices. In A. Curaj, L. Matei, R. Pricopie, J. Salmi, & P. Scott (Eds.), The European higher education area. Springer. https://doi.org/10.1007/978-3-319-20877-0_23

    Chapter  Google Scholar 

  • Astin, A. (1993). What matters in college? Four critical years revisited. Jossey-Bass.

    Google Scholar 

  • Azevedo, R. (2015). Defining and measuring engagement and learning in science: Conceptual, theoretical, methodological, and analytical issues. Educational Psychologist, 50(1), 84–94. https://doi.org/10.1080/00461520.2015.1004069

    Article  Google Scholar 

  • Balim, A. G. (2009). The effects of discovery learning on students’ success and inquiry learning skills. Eurasian Journal of Educational Research, 35, 1–20. https://www.academia.edu/2167480/The_Effects_of_Discovery_Learning_on_Students_Success_and_Inquiry_Learning_Skills?from=cover_page

    Google Scholar 

  • Baron, P., & Corbin, L. (2012). Student engagement: Rhetoric and reality. Higher Education Research and Development, 31(6), 759–772. https://doi.org/10.1080/07294360.2012.655711

    Article  Google Scholar 

  • Barrows, H. S., & Tamblyn, R. M. (1980). Problem-based learning: An approach to medical education (Vol. 1). Springer.

    Google Scholar 

  • Benjamin, A. S., & Tullis, J. (2010). What makes distributed practice effective? Cognitive Psychology, 61(3), 228–247.

    Article  PubMed  PubMed Central  Google Scholar 

  • Bjork, R. A., & Allen, T. W. (1970). The spacing effect: Consolidation or differential encoding? Journal of Verbal Learning and Verbal Behavior, 9, 567–572.

    Article  Google Scholar 

  • Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5(1), 7–74. https://doi.org/10.1080/0969595980050102

    Article  Google Scholar 

  • Bobulescu, I. A. (2020). The Old West analogy for acid-base buffering. Advances in Physiology Education, 44(2), 210–211. https://doi.org/10.1152/advan.00033.2020

    Article  PubMed  PubMed Central  Google Scholar 

  • Bonwell, C. C., & Eison, J. A. (1991). Active learning: Creating excitement in the classroom. 1991 ASHE-ERIC higher education reports. ERIC Clearinghouse on Higher Education, The George Washington University.

    Google Scholar 

  • Boud, D., & Molloy, E. (2013). Rethinking models of feedback for learning: The challenge of design. Assessment & Evaluation in Higher Education, 38(6), 698–712. https://doi.org/10.1080/02602938.2012.691462

    Article  Google Scholar 

  • Brunmair, M., & Richter, T. (2019). Similarity matters: A meta-analysis of interleaved learning and its moderators. Psychological Bulletin, 145(11), 1029–1052.

    Article  PubMed  Google Scholar 

  • Butler, A. C., & Roediger, H. L. (2008). Feedback enhances the positive effects and reduces the negative effects of multiple-choice testing. Memory & Cognition, 36, 604–616. https://doi.org/10.3758/MC.36.3.604

    Article  Google Scholar 

  • Cadaret, C. N., & Yates, D. T. (2018). Retrieval practice in the form of online homework improved information retention more when spaced 5 days rather than 1 day after class in two physiology courses. Advances in Physiology Education, 42, 305–310.

    Article  PubMed  PubMed Central  Google Scholar 

  • Cain, J., Black, E. P., & Rohr, J. (2009). An audience response system strategy to improve student motivation, attention, and feedback. American Journal of Pharmaceutical Education, 73(2), 21. https://doi.org/10.5688/aj730221

    Article  PubMed  PubMed Central  Google Scholar 

  • Cameron, J. (2001). Negative effects of reward on intrinsic motivation—A limited phenomenon: Comment on Deci, Koestner, and Ryan (2001). Review of Educational Research, 71(1), 29–42.

    Article  Google Scholar 

  • Cameron, J., Banko, K. M., & Pierce, W. D. (2001). Pervasive negative effects of rewards on intrinsic motivation: The myth continues. The Behavior Analyst, 24(1), 1–44.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Cameron, J., & Pierce, W. D. (1994). Reinforcement, reward, and intrinsic motivation: A meta-analysis. Review of Educational Research, 64(3), 363–423.

    Article  Google Scholar 

  • Campbell, C. M., & Cabrera, A. F. (2011). How sound is NSSE?: Investigating the psychometric properties of NSSE at a public, research-extensive institution. The Review of Higher Education, 35(1), 77–103.

    Article  Google Scholar 

  • Carey, P. (2013). Student as co-producer in a marketised higher education system: A case study of students’ experience of participation in curriculum design. Innovations in Education and Teaching International, 50(3), 250–260.

    Article  Google Scholar 

  • Carnine, D. (2000). Why education experts resist effective practices. Report of the Thomas B. Fordham Foundation. Thomas B. Fordham Foundation. https://files.eric.ed.gov/fulltext/ED442804.pdf

    Google Scholar 

  • Carpenter, S. K. (2014). Spacing and interleaving of study and practice. In V. A. Benassi, C. E. Overson, & C. M. Hakala (Eds.), Applying the science of learning in education: Infusing psychological science into the curriculum (pp. 131–141). Society for the Teaching of Psychology.

    Google Scholar 

  • Carvalho, P. F., & Goldstone, R. L. (2019). When does interleaving practice improve learning? In J. Dunlosky & K. A. Rawson (Eds.), The Cambridge handbook of cognition and education (pp. 411–436). Cambridge University Press.

    Chapter  Google Scholar 

  • Cech, T., & Kennedy, D. (2005). Doing more for Kate. Science, 310(5755), 1741–1742.

    Article  CAS  PubMed  Google Scholar 

  • Cepeda, N. J., Vul, E., Rohrer, D., Wixted, J. T., & Pashler, H. (2008). Spacing effects in learning: A temporal ridgeline of optimal retention. Psychological Science, 19, 1095–1102.

    Article  PubMed  Google Scholar 

  • Chan, R. Y. (2016). Understanding the purpose of higher education: An analysis of the economic and social benefits for completing a college degree. Journal of Education Policy, Planning and Administration, 6(5), 1–40.

    Google Scholar 

  • Chauncey, H., & Ebel, R. L. (1962). Testing, tests, and testing service organizations. American Behavioral Scientist, 6(3), 74–77.

    Article  Google Scholar 

  • Cheng, L. T., & Wang, J. W. (2018). Enhancing learning performance through classroom response systems: The effect of knowledge in a global economic environment. Journal of Teaching in International Business, 29(1), 49–61.

    Article  Google Scholar 

  • Chib, V. S., De Martino, B., Shimojo, S., & O’Doherty, J. P. (2012). Neural mechanisms underlying paradoxical performance for monetary incentives are driven by loss aversion. Neuron, 74(3), 582–594.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Chipchase, L., Davidson, M., Blackstock, F., Bye, R., Clothier, P., Klupp, N., Nickson, W., Turner, D., & Williams, M. (2017). Conceptualising and measuring student disengagement in higher education: A synthesis of the literature. International Journal of Higher Education, 6(2), 31–42.

    Article  Google Scholar 

  • Cook-Sather, A., Bovill, C., & Felten, P. (2014). Engaging students as partners in learning and teaching: A guide for faculty. Jossey-Bass.

    Google Scholar 

  • Corno, L., & Mandinach, E. B. (1983). The role of cognitive engagement in classroom learning and motivation. Educational Psychologist, 18(2), 88–108.

    Article  Google Scholar 

  • Cowan, N. (2008). What are the differences between long-term, short-term, and working memory? Progress in Brain Research, 169, 323–338.

    Article  PubMed  PubMed Central  Google Scholar 

  • Cowan, N. (2014). Working memory underpins cognitive development, learning, and education. Educational Psychology Review, 26(2), 197–223.

    Article  PubMed  Google Scholar 

  • Crouch, C. H., & Mazur, E. (2001). Peer instruction: Ten years of experience and results. American Journal of Physics, 69(9), 970–977.

    Article  Google Scholar 

  • Davidesco, I., & Milne, C. (2019). Implementing cognitive science and discipline-based education research in the undergraduate science classroom. CBE Life Sciences Education, 18, es4.

    Article  PubMed  PubMed Central  Google Scholar 

  • Davis, M. H., & Harden, R. M. (1999). AMEE medical education guide no 15: Problem-based learning: A practical guide. Medical Teacher, 21(2), 130–140.

    Article  CAS  PubMed  Google Scholar 

  • Deci, E. L. (1971). Effects of externally mediated rewards on intrinsic motivation. Journal of Personality and Social Psychology, 18(1), 105–115.

    Article  Google Scholar 

  • Deci, E. L., Koestner, R., & Ryan, R. M. (2001). Extrinsic rewards and intrinsic motivation in education: Reconsidered once again. Review of Educational Research, 71(1), 1–27.

    Article  Google Scholar 

  • Deci, E. L., Ryan, R. M., & Williams, G. C. (1996). Need satisfaction and the self-regulation of learning. Learning and Individual Differences, 8(3), 165–183.

    Article  Google Scholar 

  • Deng, F., Gluckstein, J. A., & Larsen, D. P. (2015). Student-directed retrieval practice is a predictor of medical licensing examination performance. Perspectives on Medical Education, 4(6), 308–313.

    Article  PubMed  PubMed Central  Google Scholar 

  • Deslauriers, L., McCarty, L. S., Miller, K., Callaghan, K., & Kestin, G. (2019). Measuring actual learning versus feeling of learning in response to being actively engaged in the classroom. Proceedings of the National Academy of Sciences, 116(39), 19251–19257.

    Article  CAS  Google Scholar 

  • de Vreede, T., Andel, S., de Vreede, G. J., Spector, P., Singh, V., & Padmanabhan, B. (2019). What is engagement and how do we measure it? Toward a domain independent definition and scale. In Proceedings of the 52nd Hawaii international conference on system sciences.

    Google Scholar 

  • D’Mello, S., Dieterle, E., & Duckworth, A. (2017). Advanced, analytic, automated (AAA) measurement of engagement during learning. Educational Psychologist, 52(2), 104–123.

    Article  PubMed  PubMed Central  Google Scholar 

  • Dobson, J. L. (2011). Effect of selected “desirable difficulty” learning strategies on the retention of physiology information. Advances in Physiology Education, 35, 378–383.

    Article  PubMed  Google Scholar 

  • Dobson, J. L. (2013). Retrieval practice is an efficient method of enhancing the retention of anatomy and physiology information. Advances in Physiology Education, 37, 184–191.

    Article  PubMed  Google Scholar 

  • Dover, M. A., (2013). Human needs: Overview. In Encyclopedia of social work. Oxford University Press. https://doi.org/10.1093/acrefore/9780199975839.013.554. https://philarchive.org/archive/DOVHNO

  • Dowd, A. C., Sawatzky, M., & Korn, R. (2011). Theoretical foundations and a research agenda to validate measures of intercultural effort. The Review of Higher Education, 35(1), 17–44.

    Article  Google Scholar 

  • 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.

    Article  PubMed  Google Scholar 

  • Ebbinghaus, H. (1885). Memory: A contribution to experimental psychology (H. A. Ruger & C. E. Bussenius, Trans. (1913)). https://doi.org/10.1037/10011-000. https://web.archive.org/web/20050504104838/, http://psy.ed.asu.edu/~classics/Ebbinghaus/index.htm

  • Ebert-May, D., Brewer, C., & Allred, S. (1997). Innovation in large lectures: Teaching for active learning. Bioscience, 47(9), 601–607.

    Article  Google Scholar 

  • Eccles, J. (2016). Engagement: Where to next? Learning and Instruction, 43, 71–75. https://doi.org/10.1016/j.learninstruc.2016.02.003

    Article  Google Scholar 

  • Edlund, J. E. (2020). Exam wrappers in psychology. Teaching of Psychology, 47(2), 156–161.

    Article  Google Scholar 

  • Eibl-Eibesfeldt, I. (1979). Human ethology: Concepts and implications for the sciences of man. Behavioral and Brain Sciences, 2(1), 1–57.

    Article  Google Scholar 

  • Ellis, R., & Hogard, E. (2016). Programmatic assessment: A paradigm shift in medical education. All Ireland. Journal of Higher Education, 8(3), article 2951.

    Google Scholar 

  • Engle, R. A., & Conant, F. R. (2002). Guiding principles for fostering productive disciplinary engagement: Explaining an emergent argument in a community of learners classroom. Cognition and Instruction, 20(4), 399–483.

    Article  Google Scholar 

  • Entwistle, N. (2000). Promoting deep learning through teaching and assessment: Conceptual frameworks and educational contexts. In Teaching and learning research programme conference. ESRC. https://www.arasite.org/RMdatabase/entwistle2000.pdf

  • Evans, D. J., Zeun, P., & Stanier, R. A. (2014). Motivating student learning using a formative assessment journey. Journal of Anatomy, 224(3), 296–303.

    Article  PubMed  Google Scholar 

  • Faust, J. L., & Paulson, D. R. (1998). Active learning in the college classroom. Journal on Excellence in College Teaching, 9(2), 3–24.

    Google Scholar 

  • Felder, R. M., & Brent, R. (1996). Navigating the bumpy road to student-centered instruction. College Teaching, 44, 43–47.

    Article  Google Scholar 

  • Finn, J. D. (1989). Withdrawing from school. Review of Educational Research, 59, 117–142.

    Article  Google Scholar 

  • Fisch, S. M., Truglio, R. T., & Cole, C. F. (1999). The impact of Sesame Street on preschool children: A review and synthesis of 30 years’ research. Media Psychology, 1(2), 165–190.

    Article  Google Scholar 

  • Fonseca, M., Oliveira, B., Carreiro-Martins, P., Neuparth, N., & Rendas, A. (2020). Revisiting the role of concept mapping in teaching and learning pathophysiology for medical students. Advances in Physiology Education, 44(3), 475–481.

    Article  PubMed  Google Scholar 

  • Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59–109.

    Article  Google Scholar 

  • Fredricks, J. A., Filsecker, M., & Lawson, M. A. (2016). Student engagement, context, and adjustment: Addressing definitional, measurement, and methodological issues. Learning and Instruction, 43, 1–4.

    Article  Google Scholar 

  • Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences of the United States of America, 111(23), 8410. https://doi.org/10.1073/pnas.1319030111

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Freeman, S., O’Connor, E., Parks, J. W., Cunningham, M., Hurley, D., Haak, D., Dirks, C., & Wenderoth, M. P. (2007). Prescribed active learning increases performance in introductory biology. CBE—Life Sciences Education, 6(2), 132–139.

    Article  PubMed  PubMed Central  Google Scholar 

  • Furrer, C., & Skinner, E. (2003). Sense of relatedness as a factor in children’s academic engagement and performance. Journal of Educational Psychology, 95(1), 148–162.

    Article  Google Scholar 

  • Gamba, G. (2003). Analogy for explaining intermediate metabolism. Advances in Physiology Education, 27(3), 156–157. https://doi.org/10.1152/advan.00015.2003

    Article  PubMed  Google Scholar 

  • Garrison, D. R., Anderson, T., & Archer, W. (2010). The first decade of the community of inquiry framework: A retrospective. The Internet and Higher Education, 13(1-2), 5–9.

    Article  Google Scholar 

  • Garrison, R. (2000). Theoretical challenges for distance education in the 21st century: A shift from structural to transactional issues. International Review of Research in Open and Distributed Learning, 1(1), 1–17.

    Article  Google Scholar 

  • Gauci, S. A., Dantas, A. M., Williams, D. A., & Kemm, R. E. (2009). Promoting student-centered active learning in lectures with a personal response system. Advances Physiology Education, 33, 60–71.

    Article  Google Scholar 

  • Gentry, S. V., Gauthier, A., Ehrstrom, B. L. E., Wortley, D., Lilienthal, A., Car, L. T., Dauwels-Okutsu, S., Nikolaou, C. K., Zary, N., Campbell, J., & Car, J. (2019). Serious gaming and gamification education in health professions: Systematic review. Journal of Medical Internet Research, 21(3), e12994.

    Article  PubMed  PubMed Central  Google Scholar 

  • Gitinabard, N., Xu, Y., Heckman, S., Barnes, T., & Lynch, C. F. (2019). How widely can prediction models be generalized? Performance prediction in blended courses. IEEE Transactions on Learning Technologies, 12(2), 184–197.

    Article  Google Scholar 

  • Gleason, B. L., Peeters, M. J., Resman-Targoff, B. H., Karr, S., McBane, S., Kelley, K., Thomas, T., & Denetclaw, T. H. (2011). An active-learning strategies primer for achieving ability-based educational outcomes. American Journal of Pharmaceutical Education, 75(9), article 186.

    Article  PubMed  Google Scholar 

  • Gooding, H. C., Mann, K., & Armstrong, E. (2017). Twelve tips for applying the science of learning to health professions education. Medical Teacher, 39, 26–31.

    Article  CAS  PubMed  Google Scholar 

  • Gordon, C. J., & Hughes, V. K. (2013). Creating relevance and credibility: New approaches for bioscience education in pre-registration nursing curriculum. International Journal of Innovation in Science and Mathematics Education, 21(2), 53–65.

    Google Scholar 

  • Green, R. A., Farchione, D., Hughes, D. L., & Chan, S.-P. (2014). Participation in asynchronous online discussion forums does improve student learning of gross anatomy. Anatomical Sciences Education, 7, 71–76.

    Article  PubMed  Google Scholar 

  • Haagsman, M. E., Scager, K., Boonstra, J., & Koster, M. C. (2020). Pop-up questions within educational videos: Effects on students’ learning. Journal of Science Education and Technology, 29, 713–724.

    Article  Google Scholar 

  • Hamilton, R. J. (1997). Effects of three types of elaboration on learning concepts from text. Contemporary Educational Psychology, 22(3), 299–318.

    Article  CAS  PubMed  Google Scholar 

  • Handelsman, M. M., Briggs, W. L., Sullivan, N., & Towler, A. (2005). A measure of college student course engagement. The Journal of Educational Research, 98, 184–193.

    Article  Google Scholar 

  • Hanus, M. D., & Fox, J. (2015). Assessing the effects of gamification in the classroom: A longitudinal study on intrinsic motivation, social comparison, satisfaction, effort, and academic performance. Computers & Education, 80, 152–161.

    Article  Google Scholar 

  • Harlen, W., Crick, R. D., Broadfoot, P., Daugherty, R., Gardner, J., James, M., & Stobart, G. (2002). A systematic review of the impact of summative assessment and tests on students’ motivation for learning. (EPPI-Centre Review, version 1.1*). In: Research evidence in education library. Issue 1. EPPI-Centre, Social Science Research Unit, Institute of Education.

    Google Scholar 

  • Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112.

    Article  Google Scholar 

  • Hausmann, L. R., Ye, F., Schofield, J. W., & Woods, R. L. (2009). Sense of belonging and persistence in White and African American first-year students. Research in Higher Education, 50(7), 649–669.

    Article  Google Scholar 

  • Heddy, B. C., & Sinatra, G. M. (2013). Transforming misconceptions: Using transformative experience to promote positive affect and conceptual change in students learning about biological evolution. Science Education, 97(5), 723–744.

    Article  Google Scholar 

  • Heist, P. (Ed.). (1968). The creative college student: An unmet challenge. Jossey-Bass.

    Google Scholar 

  • Henderson, M., Phillips, M., Ryan, T., Boud, D., Dawson, P., Molloy, E., & Mahoney, P. (2019). Conditions that enable effective feedback. Higher Education Research & Development, 38(7), 1401–1416.

    Article  Google Scholar 

  • Herrmann, L., Beitz-Radzio, C., Bernigau, D., Birk, S., Ehlers, J. P., Pfeiffer-Morhenn, B., Preusche, I., Tipold, A., & Schaper, E. (2020). Status quo of progress testing in veterinary medical education and lessons learned. Frontiers in Veterinary Science, 7, article 559. https://doi.org/10.3389/fvets.2020.00559

    Article  PubMed  Google Scholar 

  • Hilbert, T. S., & Renkl, A. (2008). Concept mapping as a follow-up strategy to learning from texts: What characterizes good and poor mappers? Instructional Science, 36(1), 53–73.

    Article  Google Scholar 

  • Hilgard, E. R. (1969). The psychological heuristics of learning. Proceedings of the National Academy of Sciences of the United States of America, 63(3), 580–587.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Hirshman, E. (2001). Elaboration in memory. In N. J. Smelser & P. B. Baltes (Eds.), International encyclopedia of the social & behavioral sciences (pp. 4369–4374). Pergamon.

    Chapter  Google Scholar 

  • Hodges, L. C. (2020). Student engagement in active learning classes. In J. J. Mintzes & E. Walter (Eds.), Active learning in college science (pp. 27–41). Springer.

    Chapter  Google Scholar 

  • Hogan, M. P. (1985). Writing as punishment. The English Journal, 74(5), 40–42.

    Article  Google Scholar 

  • Horton, A. (2005). The academic achievement gap between blacks and whites: The latest version of blaming the victim? Journal of Human Behavior in the Social Environment, 10(2), 57–70.

    Article  Google Scholar 

  • Hurtado, S., & Carter, D. F. (1997). Effects of college transition and perceptions of the campus racial climate on Latino college students’ sense of belonging. Sociology of Education, 70(4), 324–345.

    Article  Google Scholar 

  • Hurtado, S., & Ruiz Alvarado, A. (2015). Discrimination and bias, underrepresentation, and sense of belonging on campus. Higher Education Research Institute.

    Google Scholar 

  • Idsardi, R. (2020). Evidence-based practices for the active learning classroom. In J. J. Mintzes & E. Walter (Eds.), Active learning in college science (pp. 13–25). Springer.

    Chapter  Google Scholar 

  • IES WWC. (2021). What works clearinghouse. Department of Education. https://ies.ed.gov/ncee/wwc/

    Google Scholar 

  • Ishitani, T. T. (2006). Studying attrition and degree completion behavior among first-generation college students in the United States. The Journal of Higher Education, 77(5), 861–885.

    Article  Google Scholar 

  • Jeno, L. M., Danielsen, A. G., & Raaheim, A. (2018). A prospective investigation of students’ academic achievement and dropout in higher education: A Self-Determination Theory approach. Educational Psychology, 38(9), 1163–1184.

    Article  Google Scholar 

  • Jham, B. C., Duraes, G. V., Strassler, H. E., & Sensi, L. G. (2008). Joining the podcast revolution. Journal of Dental Education, 72(3), 278–281.

    Article  PubMed  Google Scholar 

  • Jovanović, J., Mirriahi, N., Gašević, D., Dawson, S., & Pardo, A. (2019). Predictive power of regularity of pre-class activities in a flipped classroom. Computers & Education, 134, 156–168.

    Article  Google Scholar 

  • Jovanović, J., Saqr, M., Joksimović, S., & Gašević, D. (2021). Students matter the most in learning analytics: The effects of internal and instructional conditions in predicting academic success. Computers & Education. https://doi.org/10.1016/j.compedu.2021.104251

  • Juvonen, J., Espinoza, G., & Knifsend, C. (2012). The role of peer relationships in student academic and extracurricular engagement. In S. L. Christenson, A. L. Reschly, & C. Wylie (Eds.), Handbook of research on student engagement (pp. 387–401). Springer.

    Chapter  Google Scholar 

  • Kahn, W. A. (1990). Psychological conditions of personal engagement and disengagement at work. Academy of Management Journal, 33(4), 692–724.

    Article  Google Scholar 

  • Kahu, E. R. (2013). Framing student engagement in higher education. Studies in Higher Education, 38(5), 758–773.

    Article  Google Scholar 

  • Karpicke, J. D., & Roediger, H. L., 3rd. (2007). Expanding retrieval practice promotes short-term retention, but equally spaced retrieval enhances long-term retention. Journal of Experimental Psychology Learning Memory Cognition, 33(4), 704–719. https://doi.org/10.1037/0278-7393.33.4.704

    Article  PubMed  Google Scholar 

  • Kauffman, C. A., Derazin, M., Asmar, A., & Kibble, J. D. (2018). Relationship between classroom attendance and examination performance in a second-year medical pathophysiology class. Advances in Physiology Education, 42(4), 593–598.

    Article  PubMed  Google Scholar 

  • Kelley, P., & Whatson, T. (2013). Making long-term memories in minutes: A spaced learning pattern from memory research in education. Frontiers in Human Neuroscience, 7, article 589.

    Article  PubMed  Google Scholar 

  • Kerr, C. (2001). The uses of the university (5th ed.). Harvard University Press.

    Google Scholar 

  • Kift, S., Nelson, K., & Clarke, J. (2010). Transition pedagogy: A third generation approach to FYE-A case study of policy and practice for the higher education sector. International Journal of the First Year in higher Education, 1(1), 1–20.

    Article  Google Scholar 

  • Kim, T. W., & Werbach, K. (2016). More than just a game: Ethical issues in gamification. Ethics and Information Technology, 18(2), 157–173.

    Article  Google Scholar 

  • Klein, R., Kelly, K., Sinnayah, P., & Winchester, M. (2019). The VU way: The Block Model intensive learning at University favours low achieving students. International Journal of Innovation in Science and Mathematics Education, 27(9), 47–59.

    Google Scholar 

  • Kluger, A. N., & DeNisi, A. (1996). The effects of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory. Psychological Bulletin, 119(2), 254–284.

    Article  Google Scholar 

  • Komarraju, M., Karau, S. J., & Schmeck, R. R. (2009). Role of the Big Five personality traits in predicting college students’ academic motivation and achievement. Learning and Individual Differences, 19(1), 47–52.

    Article  Google Scholar 

  • Krieger, P. A. (2017). A visual analogy guide to human anatomy & physiology. Morton.

    Google Scholar 

  • Kuh, G. D. (1993). In their own words: What students learn outside the classroom. American Educational Research Journal, 30(2), 277–304.

    Article  Google Scholar 

  • Kuh, G. D. (2001). The national survey of student engagement: Conceptual framework and overview of psychometric properties. Indiana University Center for Postsecondary Research and Planning. https://scholarworks.iu.edu/dspace/bitstream/handle/2022/24268/The%20National%20Survey%20of%20Student%20Engagement-%20Conceptual%20framework%20and%20overview%20of%20psychometric%20properties.pdf?sequence=1

  • Kuh, G. D. (2009a). The national survey of student engagement: Conceptual and empirical foundations. New Directions for Institutional Research, 141, 5–20.

    Article  Google Scholar 

  • Kuh, G. D. (2009b). What student affairs professionals need to know about student engagement. Journal of College Student Development, 50, 683–706.

    Article  Google Scholar 

  • Kuh, G. D., Cruce, T., Shoup, R., Kinzie, J., & Gonyea, R. M. (2008). Unmasking the effects of student engagement on college grades and persistence. Journal of Higher Education, 79(5), 540–563.

    Article  Google Scholar 

  • Kuh, G. D., Kinzie, J., Buckley, J. A., Bridges, B. K., & Hayek, J. C. (2011). Piecing together the student success puzzle: Research, propositions, and recommendations: ASHE higher education report 32(5). Wiley

    Google Scholar 

  • Kuh, G. D., O’Donnell, K., & Reed, S. D. (2013). Ensuring quality & taking high-impact practices to scale. Association of American Colleges and Universities.

    Google Scholar 

  • Kuh, G. D., & Umbach, P. (2004). College and character: Insights from the national survey of student engagement. New Directions for Institutional Research, 122, 37–54.

    Article  Google Scholar 

  • Kuiper, E., & de Pater-Sneep, M. (2014). Student perceptions of drill-and-practice mathematics software in primary education. Mathematics Education Research Journal, 26(2), 215–236.

    Google Scholar 

  • Kurbel, S. (2014). A vector-free ECG interpretation with P, QRS & T waves as unbalanced transitions between stable configurations of the heart electric field during P-R, S-T & T-P segments. Theoretical Biology and Medical Modelling, 11(1), 10. https://doi.org/10.1186/1742-4682-11-10

    Article  PubMed  PubMed Central  Google Scholar 

  • Larsen, D. P., Butler, A. C., & Roediger, H. L., 3rd. (2008). Test-enhanced learning in medical education. Medical Education, 42(10), 959–966. https://doi.org/10.1111/j.1365-2923.2008.03124.x

    Article  PubMed  Google Scholar 

  • Latessa, R., & Mouw, D. (2005). Use of an audience response system to augment interactive learning. Family Medicine, 37, 12–14.

    PubMed  Google Scholar 

  • Lazowski, R. A., & Hulleman, C. S. (2016). Motivation interventions in education: A meta-analytic review. Review of Educational Research, 86(2), 602–640.

    Article  Google Scholar 

  • Levine, R. E. (2008). Peer evaluation in team-based learning. Chapter 9. In L. Michaelsen, D. Parmelee, K. K. McMahon, & R. E. Levine (Eds.), Team-based learning for health professions education: A guide to using small groups to improve learning (pp. 103–116). Stylus.

    Google Scholar 

  • Li, Y., & Lerner, R. M. (2011). Trajectories of school engagement during adolescence: Implications for grades, depression, delinquency, and substance use. Developmental Psychology, 47(1), 233–347.

    Article  PubMed  Google Scholar 

  • Linderholm, T., Dobson, J., & Yarbrough, M. B. (2016). The benefit of self-testing and interleaving for synthesizing concepts across multiple physiology texts. Advances in Physiology Education, 40(3), 329–334.

    Article  PubMed  Google Scholar 

  • Loganathan, P., Talib, C., Thoe, N., Aliyu, F., & Zawadski, R. (2019). Implementing technology infused gamification in science classroom: A systematic review and suggestions for future research. Learning Science and Mathematics, 14, 60–73.

    Google Scholar 

  • Lovett, M. C. (2013). Make exams worth more than the grade: Using exam wrappers to promote metacognition. In M. Kaplan, N. Silver, D. LaVague-Manty, & D. Meizlish (Eds.), Using reflection and metacognition to improve student learning: Across the disciplines, across the academy (pp. 18–52). Stylus.

    Google Scholar 

  • Majuri, J., Koivisto, J., & Hamari, J. (2018). Gamification of education and learning: A review of empirical literature. In Proceedings of the 2nd international GamiFIN conference, GamiFIN 2018. CEUR-WS.

    Google Scholar 

  • Marchant, G. J. (2002). Student reading of assigned articles: Will this be on the test? Teaching of Psychology., 29(1), 49–51.

    Google Scholar 

  • Mares, M. L., & Pan, Z. (2013). Effects of Sesame Street: A meta-analysis of children’s learning in 15 countries. Journal of Applied Developmental Psychology, 34(3), 140–151.

    Article  Google Scholar 

  • Martin, A. J., Anderson, J., Bobis, J., Way, J., & Vellar, R. (2012). Switching on and switching off in mathematics: An ecological study of future intent and disengagement among middle school students. Journal of Educational Psychology, 104(1), 1–18.

    Article  Google Scholar 

  • Martinez, M. E., & Lipson, J. I. (1989). Assessment for learning. Educational Leadership, 46(7), 73–75.

    Google Scholar 

  • Marton, F., & Säljö, R. (1976). On qualitative differences in learning: I—Outcome and process. British Journal of Educational Psychology, 46(1), 4–11.

    Article  Google Scholar 

  • Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50(4), 370.

    Article  Google Scholar 

  • Mayer, R. E., & Gallini, J. K. (1990). When is an illustration worth ten thousand words? Journal of Educational Psychology, 82, 715–726.

    Article  Google Scholar 

  • Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43–52.

    Article  Google Scholar 

  • McDaniel, M. A., & Donnelly, C. M. (1996). Learning with analogy and elaborative interrogation. Journal of Educational Psychology, 88(3), 508–519.

    Article  Google Scholar 

  • McGregor, D. (1960). The human side of enterprise. McGraw-Hill Higher Education.

    Google Scholar 

  • McKeachie, W. J., Pintrich, P. R., Lin, Y. G., & Smith, D. A. (1987). Teaching and learning in the college classroom: A review of the literature. National Center for Research to improve secondary teaching and learning. University of Michigan Press.

    Google Scholar 

  • Melton, A. W. (1970). The situation with respect to the spacing of repetitions and memory. Journal of Verbal Learning and Verbal Behavior, 9, 596–606.

    Article  Google Scholar 

  • Michael, J. (2006). Where’s the evidence that active learning works. Advances in Physiology Education, 30(4), 159–167.

    Article  PubMed  Google Scholar 

  • Michaelsen, L. K., Parmelee, D. X., McMahan, K. K., & Levine, R. E. (2008). Team-based learning for health professions education (1st ed.). Stylus.

    Google Scholar 

  • Miller, R. G., Ashar, B. H., & Getz, K. J. (2003). Evaluation of an audience response system for the continuing education of health professionals. Journal of Continuing Education in the Health Professions, 23, 109–115.

    Article  PubMed  Google Scholar 

  • Mintzes, J. J. (2020). From constructivism to active learning in college science. In J. J. Mintzes & E. Walter (Eds.), Active learning in college science (pp. 3–12). Springer.

    Chapter  Google Scholar 

  • Morisano, D., Hirsh, J. B., Peterson, J. B., Pihl, R. O., & Shore, B. M. (2010). Setting, elaborating, and reflecting on personal goals improves academic performance. Journal of Applied Psychology, 95(2), 255–264.

    Article  PubMed  Google Scholar 

  • Mowrer, O. H. (1939). A stimulus-response analysis of anxiety and its role as a reinforcing agent. Psychological Review, 46(6), 553–565.

    Article  Google Scholar 

  • Munday, P. (2016). The case for using DUOLINGO as part of the language classroom experience. RIED: Revista Iberoamericana de Educación a Distancia, 19(1), 83–101.

    Google Scholar 

  • Murre, J. M., & Dros, J. (2015). Replication and analysis of Ebbinghaus’ forgetting curve. PLoS One, 10(7), e0120644.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • National Research Council. (2000). How people learn: Brain, mind, experience, and school: Expanded edition. National Academies Press.

    Google Scholar 

  • Newby, T. J., & Stepich, D. A. (1987). Learning abstract concepts: The use of analogies as a mediational strategy. Journal of Instructional Development, 10(2), 20–26. Retrieved from http://www.jstor.org/stable/30220840

    Article  Google Scholar 

  • Nicol, D. J., & Macfarlane-Dick, D. (2006). Formative assessment and self-regulated learning: A model and seven principles of good feedback practice. Studies in Higher Education, 31(2), 199–218.

    Article  Google Scholar 

  • Nicoll, R. A. (2017). A brief history of long-term potentiation. Neuron, 93, 281–290.

    Article  CAS  PubMed  Google Scholar 

  • Norman, G. R. (1987). Current issues in the assessment of clinical competence. In I. R. Hart & H. J. Walton (Eds.), Further developments in assessing clinical competence. Canadian Health Publications.

    Google Scholar 

  • Nouns, Z. M., & Georg, W. (2010). Progress testing in German speaking countries. Medical Teacher, 32(6), 467–470.

    Article  PubMed  Google Scholar 

  • Ogbu, J. U. (2003). Black American students in an affluent suburb: A study of academic disengagement. Routledge.

    Book  Google Scholar 

  • Olimpo, J. T., & Esparza, D. (2020). Active learning and conceptual understanding in biology. In J. J. Mintzes & E. Walter (Eds.), Active learning in college science (pp. 43–57). Springer.

    Chapter  Google Scholar 

  • Olivas, M. A. (2011). If you build it, they will assess it (or, an open letter to George Kuh, with love and respect). The Review of Higher Education, 35(1), 1–15.

    Article  Google Scholar 

  • Owens, D. C., Sadler, T. D., Barlow, A. T., & Smith-Walters, C. (2020). Student motivation from and resistance to active learning rooted in essential science practices. Research in Science Education, 50(1), 253–277.

    Article  Google Scholar 

  • Page, J., Meehan-Andrews, T., Weerakkody, N., Hughes, D. L., & Rathner, J. A. (2017). Student perceptions and learning outcomes of blended learning in a massive first-year core physiology for allied health subjects. Advances in Physiology Education, 41, 44–55.

    Article  PubMed  Google Scholar 

  • Paivio, A., & Csapo, K. (1973). Picture superiority in free recall: Imagery or dual coding? Cognitive Psychology, 5, 176–206.

    Article  Google Scholar 

  • Pani, J. R., Chariker, J. H., & Naaz, F. (2013). Computer-based learning: Interleaving whole and sectional representation of neuroanatomy. Anatomical Sciences Education, 6(1), 11–18.

    Article  PubMed  Google Scholar 

  • Pardales, M. J., & Girod, M. (2006). Community of inquiry: Its past and present future. Educational Philosophy and Theory, 38(3), 299–309.

    Article  Google Scholar 

  • Pascarella, E. T., & Terenzini, P. T. (1980). Predicting freshman persistence and voluntary dropout decisions from a theoretical model. The Journal of Higher Education, 51(1), 60–75.

    Article  Google Scholar 

  • Paul, R., & Elder, L. (2007). Critical thinking: The art of Socratic questioning. Journal of Developmental Education, 31(1), 36–37.

    Google Scholar 

  • Pechenkina, E., Laurence, D., Oates, G., Eldridge, D., & Hunter, D. (2017). Using a gamified mobile app to increase student engagement, retention and academic achievement. International Journal of Educational Technology in Higher Education, 14, 1–12.

    Article  Google Scholar 

  • Pedaste, M., Mäeots, M., Siiman, L. A., De Jong, T., Van Riesen, S. A., Kamp, E. T., Manoli, C. C., Zacharia, Z. C., & Tsourlidaki, E. (2015). Phases of inquiry-based learning: Definitions and the inquiry cycle. Educational Research Review, 14, 47–61.

    Article  Google Scholar 

  • Peters, H., Zdravkovic, M., João Costa, M., Celenza, A., Ghias, K., Klamen, D., Mossop, L., Rieder, M., Nadarajah, V. D., Wangsaturaka, D., Wohlin, M., & Weggemans, M. (2018). Twelve tips for enhancing student engagement. Medical Teacher, 41(6), 632–637.

    Article  PubMed  Google Scholar 

  • Philpott, J. (2009). Revision (Chapter 5). In Captivating your class: Effective teaching skills. Bloomsbury.

    Google Scholar 

  • Pieterse, V., & Thompson, L. (2010). Academic alignment to reduce the presence of ‘social loafers’ and ‘diligent isolates’ in student teams. Teaching in Higher Education, 15(4), 355–367.

    Article  Google Scholar 

  • Pike, G. R., Kuh, G. D., & Massa-McKinley, R. C. (2008). First-year students’ employment, engagement, and academic achievement: Untangling the relationship between work and grades. NASPA Journal, 45(4), 560–582.

    Article  Google Scholar 

  • Prahl, K. (2017). Best practices for the think-pair-share active-learning technique. The American Biology Teacher, 79(1), 3–8.

    Article  Google Scholar 

  • Pugh, K. J., Bergstrom, C. M., Heddy, B. C., & Krob, K. E. (2017). Supporting deep engagement: The teaching for transformative experiences in science (TTES) model. The Journal of Experimental Education, 85(4), 629–657.

    Article  Google Scholar 

  • Putnam, A. L., Sungkhasettee, V. W., & Roediger, H. L. (2016). Optimizing learning in college: Tips from cognitive psychology. Perspectives on Psychological Science, 11, 652–660.

    Article  PubMed  Google Scholar 

  • Rathner, J. A., Hughes, D. L., & Schuijers, J. A. (2013). Redesigning a core first year physiology subject in allied health to achieve better learning outcomes. International Journal of Innovation in Science and Mathematics Education, 21(2), 37–52.

    Google Scholar 

  • Rathner, J. A., & Schier, M. A. (2020). The impact of flipped classroom andragogy on student assessment performance and perception of learning experience in two advanced physiology subjects. Advances in Physiology Education, 44(1), 80–92.

    Article  PubMed  Google Scholar 

  • Reeve, J., Jang, H., Carrell, D., Jeon, S., & Barch, J. (2004). Enhancing students’ engagement by increasing teachers’ autonomy support. Motivation and Emotion, 28, 147–169. https://doi.org/10.1023/B:MOEM.0000032312.95499.6f

    Article  Google Scholar 

  • Reschly, A. L., & Christenson, S. L. (2012). Jingle, jangle, and conceptual haziness: Evolution and future directions of the engagement construct. In Handbook of research on student engagement (pp. 3–19). Springer.

    Chapter  Google Scholar 

  • Rodriguez, F., Kataoka, S., Janet Rivas, M., Kadandale, P., Nili, A., & Warschauer, M. (2021). Do spacing and self-testing predict learning outcomes? Active Learning in Higher Education, 22, 77–91.

    Article  Google Scholar 

  • Roediger, H. L., Agarwal, P. K., McDaniel, M. A., & McDermott, K. B. (2011). Test-enhanced learning in the classroom: Long-term improvements from quizzing. Journal of Experimental Psychology: Applied, 17(4), 382–395.

    PubMed  Google Scholar 

  • Roediger, H. L., & Butler, A. C. (2011). The critical role of retrieval practice in long-term retention. Trends in Cognitive Sciences, 15(1), 20–27.

    Article  PubMed  Google Scholar 

  • Roediger, H. L., & Karpicke, J. D. (2006a). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science, 17(3), 249–255. https://doi.org/10.1111/j.1467-9280.2006.01693.x

    Article  PubMed  Google Scholar 

  • Roediger, H. L., & Karpicke, J. D. (2006b). The power of testing memory: Basic research and implications for educational practice. Perspectives on Psychological Science, 1(3), 181–210. https://doi.org/10.1111/j.1745-6916.2006.00012.x

    Article  PubMed  Google Scholar 

  • Roediger, H. L., Putnam, A. L., & Smith, M. A. (2011). Chapter one—Ten benefits of testing and their applications to educational practice. In J. P. Mestre & B. H. Ross (Eds.), Psychology of learning and motivation (pp. 1–36). Academic Press.

    Google Scholar 

  • Roediger, H. L., & Pyc, M. A. (2012). Inexpensive techniques to improve education: Applying cognitive psychology to enhance educational practice. Journal of Applied Research in Memory and Cognition, 1(4), 242–248.

    Article  Google Scholar 

  • Rosen, L. D., Lim, A. F., Carrier, L. M., & Cheever, N. A. (2011). An empirical examination of the educational impact of text message-induced task switching in the classroom: Educational implications and strategies to enhance learning. Educational Psychology, 17(2), 163–177.

    Google Scholar 

  • Rotgans, J. I., & Schmidt, H. G. (2011). Situational interest and academic achievement in the active-learning classroom. Learning and Instruction, 21(1), 58–67.

    Article  Google Scholar 

  • Rourke, L., & Kanuka, H. (2009). Learning in communities of inquiry: A review of the literature. International Journal of E-Learning & Distance Education/Revue internationale du e-learning et la formation à distance, 23(1), 19–48.

    Google Scholar 

  • Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55, 68–78.

    Article  CAS  PubMed  Google Scholar 

  • Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemporary Educational Psychology, 61, 101860.

    Article  Google Scholar 

  • Ryan, R. M., & Stiller, J. (1991). The social contexts of internalization: Parent and teacher influences on autonomy, motivation, and learning. In P. R. Pintrich & M. L. Maehr (Eds.), Advances in motivation and achievement (Vol. 7, pp. 115–149). JAI Press.

    Google Scholar 

  • Schmidmaier, R., Ebersbach, R., Schiller, M., Hege, I., Holzer, M., & Fischer, M. R. (2011). Using electronic flashcards to promote learning in medical students: Retesting versus restudying. Medical Education, 45(11), 1101–1110.

    Article  PubMed  Google Scholar 

  • Schmidt, J. A., Rosenberg, J. M., & Beymer, P. N. (2018). A person-in-context approach to student engagement in science: Examining learning activities and choice. Journal of Research in Science Teaching, 55(1), 19–43.

    Article  Google Scholar 

  • Schofer, E., & Meyer, J. W. (2005). The worldwide expansion of higher education in the twentieth century. American Sociological Review, 70(6), 898–920.

    Article  Google Scholar 

  • Schut, S., Heeneman, S., Bierer, B., Driessen, E., van Tartwijk, J., & van Der Vleuten, C. (2020). Between trust and control: Teachers’ assessment conceptualisations within programmatic assessment. Medical Education, 54(6), 528–537.

    Article  PubMed  Google Scholar 

  • Schuwirth, L., van der Vleuten, C., & Durning, S. J. (2017). What programmatic assessment in medical education can learn from healthcare. Perspectives on Medical Education, 6(4), 211–215. https://doi.org/10.1007/s40037-017-0345-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Schuwirth, L. W. T., & van der Vleuten, C. P. M. (2012). The use of progress testing. Perspectives on Medical Education, 1(1), 24–30. https://doi.org/10.1007/s40037-012-0007-2

    Article  PubMed  PubMed Central  Google Scholar 

  • Schwartz, D. L., & Bransford, J. D. (1998). A time for telling. Cognition and Instruction, 16(4), 475–5223.

    Article  Google Scholar 

  • Seibert Hanson, A. E., & Brown, C. M. (2020). Enhancing L2 learning through a mobile assisted spaced-repetition tool: An effective but bitter pill? Computer Assisted Language Learning, 33, 133–155.

    Article  Google Scholar 

  • Seidel, S. B., & Tanner, K. D. (2013). What if students revolt?—Considering student resistance: Origins, options, and opportunities for investigation. CBE Life Sciences Education, 12, 586–595.

    Article  PubMed  PubMed Central  Google Scholar 

  • Shekhar, P., Demonbrun, M., Borrego, M., Finelli, C., Prince, M., Henderson, C., & Waters, C. (2015). Development of an observation protocol to study undergraduate engineering student resistance to active learning. International Journal of Engineering Education, 31(2), 597–609.

    Google Scholar 

  • Shernoff, D. J., & Hoogstra, L. (2001). Continuing motivation beyond the high school classroom. New Directions for Child and Adolescent Development, 93, 73–87.

    Article  Google Scholar 

  • Silverthorn, D. U. (2020). When active learning fails… and what to do about it. In J. J. Mintzes & E. Walter (Eds.), Active learning in college science (pp. 985–1001). Springer.

    Chapter  Google Scholar 

  • Silverthorn, D. U., Thorn, P. M., & Svinicki, M. D. (2006). It’s difficult to change the way we teach: Lessons from the integrative themes in physiology curriculum module project. Advances in Physiology Education, 30, 204–214.

    Article  PubMed  Google Scholar 

  • Sinatra, G. M., Heddy, B. C., & Lombardi, D. (2015). The challenges of defining and measuring student engagement in science. Educational Psychologist, 50(1), 1–13.

    Article  Google Scholar 

  • Sinatra, G. M., & Pintrich, P. R. (2002). The role of intentions in conceptual change learning. In G. M. Sinatra & P. R. Pintrich (Eds.), Intentional conceptual change (pp. 10–26). Routledge.

    Google Scholar 

  • Sinclair, M. F., Christenson, S. L., Lehr, C. A., & Anderson, A. R. (2003). Facilitating student engagement: Lessons learned from Check & Connect longitudinal studies. The California School Psychologist, 8(1), 29–41.

    Article  Google Scholar 

  • Sinnayah, P., Rathner, J. A., Loton, D., Klein, R., & Hartley, P. (2019). A combination of active learning strategies improves student academic outcomes in first-year paramedic bioscience. Advances in Physiology Education, 43(2), 233–240. https://doi.org/10.1152/advan.00199.2018

    Article  PubMed  Google Scholar 

  • Skinner, E., Furrer, C., Marchand, G., & Kindermann, T. (2008). Engagement and disaffection in the classroom: Part of a larger motivational dynamic? Journal of Educational Psychology, 100(4), 765.

    Article  Google Scholar 

  • Smolen, P., Zhang, Y., & Byrne, J. H. (2016). The right time to learn: Mechanisms and optimization of spaced learning. Nature Reviews Neuroscience, 17(2), 77–88.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Snyder, B. R. (1971). The hidden curriculum. MIT Press.

    Google Scholar 

  • Söbke, H. (2018). A case study of deep gamification in higher engineering education. In International conference on games and learning alliance (pp. 375–386). Springer.

    Google Scholar 

  • Soicher, R. N., & Gurung, R. A. (2017). Do exam wrappers increase metacognition and performance? A single course intervention. Psychology Learning & Teaching, 16(1), 64–73.

    Article  Google Scholar 

  • Sommer, W. G. (1990). Procrastination and cramming: How adept students ace the system. Journal of American College Health, 39(1), 5–10.

    Article  CAS  PubMed  Google Scholar 

  • Stead, D. R. (2005). A review of the one-minute paper. Active Learning in Higher Education, 6(2), 118–131.

    Article  Google Scholar 

  • Stephenson, B., Craig, M., Zingaro, D., Horton, D., Heap, D., & Huynh, E. (2017). Exam wrappers: Not a silver bullet. In Proceedings of the 2017 ACM SIGCSE technical symposium on computer science education (pp. 573–578).

    Google Scholar 

  • Sterling, L., Pedell, S., & Oates, G. (2020). Using motivational modelling with an app designed to increase student performance and retention. In Early warning systems and targeted interventions for student success in online courses (pp. 161–176). IGI Global.

    Google Scholar 

  • Stiggins, R. J. (2005). Student-involved assessment for learning. Pearson Prentice Hall.

    Google Scholar 

  • Sundrud, R. B., & Hueftle, K. (2009). Essential analogies in human anatomy & physiology. The American Biology Teacher, 71(9), 554–557.

    Article  Google Scholar 

  • Szpunar, K. K., Khan, N. Y., & Schacter, D. L. (2013). Interpolated memory tests reduce mind wandering and improve learning of online lectures. Proceedings of the National Academy of Sciences of the United States of America, 110(16), 6313–6317.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Tabibian, B., Upadhyay, U., De, A., Zarezade, A., Schölkopf, B., & Gomez-Rodriguez, M. (2019). Enhancing human learning via spaced repetition optimization. Proceedings of the National Academy of Sciences of the United States of America, 116, 3988–3993.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Talbert, R. (2017). Flipped learning: A guide for higher education faculty. Stylus.

    Google Scholar 

  • Taylor, S. A., Goodwin, S. A., Melton, H., & Hunter, G. (2011). An analysis of the Student Course Engagement Questionnaire (SCEQ) in large-section marketing principles classes. Journal on Excellence in College Teaching, 22(1), 29–57.

    Google Scholar 

  • Team Based Learning Collaborative. (2013). What is team based Learning: Overview. http://www.teambasedlearning.org/definition/. Accessed 28 Apr 2021.

  • Theobald, E. J., Hill, M. J., Tran, E., Agrawal, S., Arroyo, E. N., Behling, S., Chambwe, N., Cintrón, D. L., Cooper, J. D., Dunster, G., Grummer, J. A., Hennessey, K., Hsiao, J., Iranon, N., Jones, L., 2nd, Jordt, H., Keller, M., Lacey, M. E., Littlefield, C. E., … Freeman, S. (2020). Active learning narrows achievement gaps for underrepresented students in undergraduate science, technology, engineering, and math. Proceedings of the National Academy of Sciences of the United States of America, 117(12), 6476–6483.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Thomas, L., & Jones, R. (2017). Student engagement in the context of commuter students. The Student Engagement Partnership & Liz Thomas Associates. https://lizthomasassociates.co.uk/projects/2018/Commuter%20student%20engagement.pdf

    Google Scholar 

  • Tinto, V. (1975). Dropout from higher education: A theoretical synthesis of recent research. Review of Educational Research, 45(1), 89–125.

    Article  Google Scholar 

  • Tinto, V. (2003). Learning better together: The impact of learning communities on student success. Higher Education Monograph Series, 1(8), 1–8.

    Google Scholar 

  • Tolman, E. C. (1938). The determiners of behavior at a choice point. Psychological Review, 45(1), 1.

    Article  Google Scholar 

  • Tomé Klock, A. C., Gasparini, I., Soares Pimenta, M., & Hamari, J. (2020). Tailored gamification: A review of literature. International Journal of Human-Computer Studies, 144, 102495.

    Article  Google Scholar 

  • Van Hoof, T. J., & Doyle, T. J. (2018). Learning science as a potential new source of understanding and improvement for continuing education and continuing professional development. Medical Teacher, 40(9), 880–885.

    Article  PubMed  Google Scholar 

  • Voelkel, S. (2013). Combining the formative with the summative: The development of a two-stage online test to encourage engagement and provide personal feedback in large classes. Research in Learning Technology, 21(1), 1–18.

    Google Scholar 

  • Voelkl, K. E. (2012). School identification. In S. L. Christenson, A. L. Reschly, & C. Wylie (Eds.), Handbook of research on student engagement (pp. 193–218). Springer.

    Chapter  Google Scholar 

  • Wahba, M. A., & Bridwell, L. G. (1976). Maslow reconsidered: A review of research on the need hierarchy theory. Organizational Behavior and Human Performance, 15(2), 212–240.

    Article  Google Scholar 

  • Waluyo, B., & Bucol, J. L. (2021). The impact of gamified vocabulary learning using quizlet on low-proficiency students. Computer-Assisted Language Learning, 22(1), 158–179.

    Google Scholar 

  • Wang, M. T., & Degol, J. (2014). Staying engaged: Knowledge and research needs in student engagement. Child Development Perspectives, 8(3), 137–143.

    Article  PubMed  PubMed Central  Google Scholar 

  • Wang, M. T., & Fredricks, J. A. (2014). The reciprocal links between school engagement and youth problem behavior during adolescence. Child Development, 85, 722e737.

    Article  Google Scholar 

  • Weinstein, Y., Madan, C. R., & Sumeracki, M. A. (2018). Teaching the science of learning. Cognitive Research: Principles and Implications, 3, 2. https://doi.org/10.1186/s41235-017-0087-y

    Article  Google Scholar 

  • Wenger, E. (1999). Communities of practice: Learning, meaning, and identity. Cambridge University Press.

    Google Scholar 

  • Wheeler, M. A., & Roediger, H. L. (1992). Disparate Effects of repeated testing: Reconciling Ballard’s (1913) and Bartlett’s (1932) results. Psychological Science, 3(4), 240–246. https://doi.org/10.1111/j.1467-9280.1992.tb00036.x

    Article  Google Scholar 

  • White, C., Bradley, E., Martindale, J., Roy, P., Patel, K., Yoon, M., & Worden, M. K. (2014). Why are medical students ‘checking out’ of active learning in a new curriculum? Medical Education, 48(3), 315–324.

    Article  PubMed  Google Scholar 

  • Wilkinson, T. J., & Tweed, M. J. (2018). Deconstructing programmatic assessment. Advances in Medical Education and Practice, 9, 191–197. https://doi.org/10.2147/AMEP.S144449

    Article  PubMed  PubMed Central  Google Scholar 

  • Wilson, A., Howitt, S., & Higgins, D. (2016). Assessing the unassessable: Making learning visible in undergraduates’ experiences of scientific research. Assessment & Evaluation in Higher Education, 41(6), 901–916.

    Article  Google Scholar 

  • Wiltbank, L. B., Williams, K. R., Marciniak, L., & Momsen, J. L. (2019). Student perceptions and use of feedback during active learning: A new model from repeated stimulated recall interviews. Assessment & Evaluation in Higher Education, 44(3), 431–448.

    Article  Google Scholar 

  • Winne, P. H. (1996). A metacognitive view of individual differences in self-regulated learning. Learning and Individual Differences, 8(4), 327–353.

    Article  Google Scholar 

  • Wissman, K. T., Rawson, K. A., & Pyc, M. A. (2012). How and when do students use flashcards? Memory, 20(6), 568–579.

    Article  PubMed  Google Scholar 

  • Witchel, H., Westling, C., Tee, J., Healy, A., Needham, R., & Chockalingam, N. (2014). What does not happen: Quantifying embodied engagement using NIMI and self-adaptors. Participations: Journal of Audience and Reception Studies, 11(1), 304–331.

    Google Scholar 

  • Witchel, H. J. (2013). Engagement: The inputs and the output. In Proceedings of the 2013 inputs-outputs conference: An interdisciplinary conference on engagement in HCI and performance (pp. 1–4).

    Google Scholar 

  • Wittrock, M. C. (1978). The cognitive movement in instruction. Educational Psychologist, 13(1), 15–29.

    Article  Google Scholar 

  • Won, S., Wolters, C. A., & Mueller, S. A. (2018). Sense of belonging and self-regulated learning: Testing achievement goals as mediators. The Journal of Experimental Education, 86(3), 402–418.

    Article  Google Scholar 

  • Wong, M. M. (2008). Perceptions of parental involvement and autonomy support: Their relations with self-regulation, academic performance, substance use and resilience among adolescents. North American Journal of Psychology, 10(3), 497–518.

    Google Scholar 

  • Wood, D. F. (2003). Problem based learning. British Medical Journal, 326(7384), 328–330.

    Article  PubMed  PubMed Central  Google Scholar 

  • Wormald, B. W., Schoeman, S., Somasunderam, A., & Penn, M. (2009). Assessment drives learning: An unavoidable truth? Anatomical Sciences Education, 2(5), 199–204. https://doi.org/10.1002/ase.102

    Article  PubMed  Google Scholar 

  • Wozniak, P. (2021). SuperMemo Guru. https://supermemo.guru/wiki/SuperMemo_Guru. Accessed 30 Apr 2021.

  • Wyer, K. (2013). Survey: More freshmen than ever say they go to college to get better jobs, make more money. Higher Education Research Institute at UCLA. http://heri.ucla.edu/press-release/TheAmericanFreshman2012-PressRelease.pdf

    Google Scholar 

  • Yeager, D. S., & Dweck, C. S. (2012). Mindsets that promote resilience: When students believe that personal characteristics can be developed. Educational Psychologist, 47(4), 302–314.

    Article  Google Scholar 

  • Zhang, Y., Haddad, E., Torres, B., & Chen, C. (2011). The reciprocal relationships among parents’ expectations, adolescents’ expectations, and adolescents’ achievement: A two-wave longitudinal analysis of the NELS data. Journal of Youth and Adolescence, 40(4), 479–489.

    Article  PubMed  Google Scholar 

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Authors and Affiliations

  1. Department of Neuroscience, Brighton and Sussex Medical School, Brighton, UK

    Harry J. Witchel

  2. First Year College, Victoria University, Melbourne, VIC, Australia

    Rudi Klein & Puspha Sinnayah

  3. Institute for Health and Sport, Victoria University, Melbourne, VIC, Australia

    Puspha Sinnayah

  4. University of Melbourne, Melbourne, VIC, Australia

    Joseph Rathner

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Correspondence to Harry J. Witchel .

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  1. Department of Neuroscience, Brighton and Sussex Medical School, Brighton, UK

    Harry J. Witchel

  2. Department of Medical Education, Geisel School of Medicine, Dartmouth College, Hanover, NH, USA

    Michael W. Lee

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Witchel, H.J., Klein, R., Sinnayah, P., Rathner, J. (2022). From Psychology Laboratory to Student Development: Untangling Momentary Engagement from Longer-Term Engagement in Bioscience Education. 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_4

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