Leveraging student-centred teaching practices by authentic simulations environment and self-regulated learning

References

• Allan, C. (2019). Actors in nursing simulations: A Balanced interdisciplinary approach. The Midwest Quarterly, 60(3), 290–298. link.gale.com/apps/doc/A583693213/AONE?u=anon~e91424f0&sid=googleScholar&xid=31ff5256
   Web of Science ®Google Scholar
• Azevedo, R., Behnagh, R., Duffy, M., Harley, J., & Trevors, G. (2012). Metacognition and self-regulated learning in student-centered learning environments. Theoretical Foundations of Student-Centered Learning Environments, 22, 171–197.
   Google Scholar
• Bland, A. J., Topping, A., & Wood, B. (2011). A concept analysis of simulation as a learning strategy in the education of undergraduate nursing students. Nurse Education Today, 31(7), 664–670. https://doi.org/10.1016/j.nedt.2010.10.013
   PubMed Web of Science ®Google Scholar
• Bradley, E. G., & Kendall, B. (2014). A review of computer simulations in teacher education. Journal of Educational Technology Systems, 43(1), 3–12. https://doi.org/10.2190/ET.43.1.b
   Google Scholar
• Broadbent, J. (2017). Comparing online and blended learner’s self-regulated learning strategies and academic performance. The Internet and Higher Education, 33, 24–32. https://doi.org/10.1016/j.iheduc.2017.01.004
   Web of Science ®Google Scholar
• De Corte, E., Verschaffel, L., & Masui, C. (2004). The CLIA-model: A framework for designing powerful learning environments for thinking and problem solving. European Journal of Psychology of Education, 19(4), 365–384. https://doi.org/10.1007/BF03173216
   Web of Science ®Google Scholar
• Dieker, L. A., Rodriguez, J. A., Lignugaris, B., Hynes, M. C., & Hughes, C. E. (2014). The potential of simulated environments in teacher education: Current and future possibilities. Teacher Education and Special Education: The Journal of the Teacher Education Division of the Council for Exceptional Children, 37(1), 21–33. https://doi.org/10.1177/0888406413512683
   Google Scholar
• Duffy, M. C., Azevedo, R., Sun, N. Z., Griscom, S. E., Stead, V., Crelinsten, L., Wiseman, J., Maniatis, T., & Lachapelle, K. (2015). Team regulation in a simulated medical emergency: An in-depth analysis of cognitive, metacognitive, and affective processes. Instructional Science, 43(3), 401–426. https://doi.org/10.1007/s11251-014-9333-6
   Web of Science ®Google Scholar
• Fanning, R. M., & Gaba, D. M. (2007). The role of debriefing in simulation-based learning. Simulation in Healthcare: The Journal of the Society for Simulation in Healthcare, 2(2), 115–125. https://doi.org/10.1097/SIH.0b013e3180315539
   Google Scholar
• Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive developmental inquiry. American Psychologist, 34(10), 906–911. https://doi.org/10.1037/0003-066X.34.10.906
   Web of Science ®Google Scholar
• Gosen, J., & Washbush, J. (2004). A review of scholarship on assessing experiential learning effectiveness. Simulation & Gaming, 35(2), 270–293. https://doi.org/10.1177/1046878104263544
   Google Scholar
• Hadwin, A., Järvelä, S., & Miller, M. (2018). Self-regulation, co-regulation, and shared regulation in collaborative learning environments. In D. H. Schunk & J. A. Greene (Eds.), Handbook of self-regulation of learning and performance (pp. 83–106). Routledge.
   Google Scholar
• Ingram, J., & Elliott, V. (2016). A critical analysis of the role of wait time in classroom interactions and the effects on student and teacher interactional behaviours. Cambridge Journal of Education, 46(1), 37–53. https://doi.org/10.1080/0305764X.2015.1009365
   Web of Science ®Google Scholar
• Järvelä, S., Kirschner, P. A., Panadero, E., Malmberg, J., Phielix, C., Jaspers, J., Koivuniemi, M., & Järvenoja, H. (2015). Enhancing socially shared regulation in collaborative learning groups: Designing for CSCL regulation tools. Educational Technology Research and Development, 63(1), 125–142. https://doi.org/10.1007/s11423-014-9358-1
   Web of Science ®Google Scholar
• Kaiser, G., Busse, A., Hoth, J., König, J., & Blömeke, S. (2015). About the complexities of video-based assessments: Theoretical and methodological approaches to overcoming shortcomings of research on teachers’ competence. International Journal of Science and Mathematics Education, 13(2), 369–387. https://doi.org/10.1007/s10763-015-9616-7
   Web of Science ®Google Scholar
• Kaufman, D., & Ireland, A. (2019). Simulation as a strategy in teacher education. Oxford Research Encyclopedia of Education. https://doi.org/10.1093/acrefore/9780190264093.013.478
   Google Scholar
• Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75–86. https://doi.org/10.1207/s15326985ep4102_1
   Web of Science ®Google Scholar
• Kohen, Z., & Kramarski, B. (2018). Promoting mathematics teachers’ pedagogical metacognition: A theoretical-practical model and case study. In Y. Dori, Z. Mevarech, & D. Baker (Eds.), Cognition, metacognition, and culture in STEM education (pp. 279–305). Springer.
   Google Scholar
• Kramarski, B. (2008). Promoting teachers’ algebraic reasoning and self-regulation with metacognitive guidance. Metacognition and Learning, 3(2), 83–99. https://doi.org/10.1007/s11409-008-9020-6
   Web of Science ®Google Scholar
• Kramarski, B. (2018). Teachers as agents in promoting students’ SRL and performance: Applications for teachers’ dual-role training program. In D. H. Schunk & J. A. Greene (Eds.), Handbook of self-regulation of learning and performance (pp. 223–239). Springer Publisher.
   Google Scholar
• Kramarski, B., & Kohen, Z. (2017). Promoting preservice teachers’ dual self-regulation roles as learners and as teachers: Effects of generic vs. specific prompts. Metacognition & Learning, 12(2), 157–191. https://doi.org/10.1007/s11409-016-9164-8
   Web of Science ®Google Scholar
• Kramarski, B., & Michalsky, T. (2009). Investigating pre-service teachers’ professional growth in self-regulated learning environments. Journal of Educational Psychology, 101(1), 161–175. https://doi.org/10.1037/a0013101
   Web of Science ®Google Scholar
• Kramarski, B., & Michalsky, T. (2010). Preparing preservice teachers for self-regulated learning in the context of technological pedagogical content knowledge. Learning and Instruction, 20(5), 434–447. https://doi.org/10.1016/j.learninstruc.2009.05.003
   Web of Science ®Google Scholar
• Kramarski, B., & Michalsky, T. (2015). Effect of a TPCK-SRL model on teachers’ pedagogical beliefs, self-efficacy, and technology-based lesson design. In C. Angeli & N. Valanides (Eds.), Technological pedagogical content knowledge (pp. 89–112). Springer.
   Google Scholar
• Maghfiroh, L., Subchan, W., & Iqbal, M. (2017). Problem based learning trough moodle for increasing self regulated learning students (Goal setting and Planing). The International Journal of Social Sciences and Humanities Invention, 4(8), 3880–3887. https://doi.org/10.18535/ijsshi/v4i8.32
   Google Scholar
• Mevarech, Z. R., & Kramarski, B. (2014). Critical maths for innovative societies: The role of metacognitive pedagogies (pp. 23–33). OECD Publisher. https://doi.org/10.1787/9789264223561-en
   Google Scholar
• Niemi, H., & Nevgi, A. (2014). Research studies and active learning promoting professional competences in Finnish teacher education. Teaching and Teacher Education, 43, 131–142. https://doi.org/10.1016/j.tate.2014.07.006
   Web of Science ®Google Scholar
• Organisation for Economic Co-operation and Development. (2013). Pisa 2012 assessment and analytical framework: Mathematics, reading, science and problem solving and financial literacy (pp. 13–21). https://doi.org/10.1787/9789264190511-en.
   Google Scholar
• Peeters, J., De Backer, F., Reina, V. R., Kindekens, A., Buffel, T., & Lombaerts, K. (2014). The role of teachers’ self-regulatory capacities in the implementation of self-regulated learning practices. Procedia - Social and Behavioral Sciences, 116, 1963–1970. https://doi.org/10.1016/j.sbspro.2014.01.504
   Google Scholar
• Pintrich, P. R. (2000). The role of goal orientation in self-regulated learning. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation: Research and application (pp. 451–502). Academic.
   Google Scholar
• Pundir, R., & Surana, A. (2016). Constructivism learning: A way to make knowledge construction. The International Journal of Indian Psychology, 3(10), 345–359.
   Google Scholar
• Raedts, M., Rijlaarsdam, G., Van Waes, L., & Daems, F. (2007). Observational learning through video-based models: Impact on students’ accuracy of self-efficacy beliefs, task knowledge and writing performances. In G. Rijlaarsdam, E. Series, P. Boscolo, & S. Hidi (Eds.), Studies in Writing. Vol. 19. Writing and Motivation (pp. 219–238). Elsevier.
   Google Scholar
• Raedts, M., Rijlaarsdam, G., Van Waes, L., & Daems, F.(2007). Observational learning through video-based models: Impact on student’s accuracy of self-efficacy beliefs, task knowledge, and writing performances. In G. Rijlaarsdam (Series Ed.) and P. Boscolo & S. Hidi (Volume Eds.), Studies in Writing,Volume 19, Writing and Motivation (pp. 219–238). Elsevier.
   Google Scholar
• Rudd, C. J., & Churchouse, C. (2007, June). Scripting, acting, performing = learning: Developing a toolbox for facilitators to use actors in mental health scenario based learning. Paper presented at the SimTec Healthcare Conference Proceedings, Brisbane.
   Google Scholar
• Schraw, G. (1998). Promoting general metacognitive awareness. Instructional Science, 26(1), 113–125.
   Web of Science ®Google Scholar
• Seidel, T., Schnitzler, K., Kosel, C., Stürmer, K., & Holzberger, D. (2021). Student characteristics in the eyes of teachers: Differences between novice and expert teachers in judgment accuracy, observed behavioral cues, and gaze. Educational Psychology Review, 33, 69–89. https://doi.org/10.1007/s10648-020-09532-2
   Web of Science ®Google Scholar
• Shapira-Lishchinsky, O. (2013). Team-based simulations: Learning ethical conduct in teacher trainee programs. Teaching and Teacher Education, 33, 1–12. https://doi.org/10.1016/j.tate.2013.02.001
   Web of Science ®Google Scholar
• Shilo, A., & Kramarski, B. (2019). Mathematical-metacognitive discourse: How can it be developed among teachers and their students? Empirical evidence from a videotaped lesson and two case studies. ZDM, 51(4), 625–640. https://doi.org/10.1007/s11858-018-01016-6
   Google Scholar
• Slepkov, H. (2008). Teacher professional growth in an authentic learning environment. Journal of Research on Technology in Education, 41(1), 85–111. https://doi.org/10.1080/15391523.2008.10782524
   Google Scholar
• Spruce, R., & Bol, L. (2015). Teacher beliefs, knowledge, and practice of self-regulated learning. Journal of Metacognition Learning, 10(2), 245–277. https://doi.org/10.1007/s11409-014-9124-0
   Web of Science ®Google Scholar
• Stahl, R. J. (1994). Using “think-time” and “wait-time” skilfully in the classroom. ERIC Digest.
   Google Scholar
• Sturmer, K., Konings, K. D., & Seidel, T. (2013). Declarative knowledge and professional vision in teacher education: Effect of courses in teaching and learning. British Journal of Educational Psychology, 83(3), 467–483. https://doi.org/10.1111/j.2044-8279.2012.02075.x
   PubMed Web of Science ®Google Scholar
• Swanson, E. A., Nicholson, A. C., Boese, T. A., Cram, E., Stineman, A. M., & Tew, K. (2011). Comparison of selected teaching strategies incorporating simulation and student outcomes. Clinical Simulation in Nursing, 7(3), e81–e90. https://doi.org/10.1016/j.ecns.2009.12.011
   Google Scholar
• Toklu, H. Z., & Hussain, A. (2013). The changing face of pharmacy practice and the need for a new model of pharmacy education. Journal of Young Pharmacists, 5(2), 38–40. https://doi.org/10.1016/j.jyp.2012.09.001
   PubMedGoogle Scholar
• Vermunt, J. D. (2016, June). Promoting student learning and teacher learning through diversity. Invited keynote given at the Conference of the EARLI-SIG Teaching and Teacher Education, Zürich, Switzerland. https://doi.org/10.1192/apt.8.5.342
   Google Scholar
• Xu, Y., & Yang, Y. (2010). Student learning in business simulation: An empirical investigation. Journal of Education for Business, 85(4), 223. https://doi.org/10.1080/08832320903449469
   Google Scholar
• Yang, Y., van Aalst, J., Chan, C. K. K., & Tian, W. (2016). Reflective assessment in knowledge building by students with low academic achievement. International Journal of Computer-Supported Collaborative Learning, 11(3), 281–311. https://doi.org/10.1007/s11412-016-9239-1
   Web of Science ®Google Scholar
• Zimmerman, B. J. (2013). Theories of self-regulated learning and academic achievement: An overview and analysis. In B. J. Zimmerman & D. H. Schunk (Eds.),Self-regulated learning and academic achievement (pp. 10–45). Routledge.
   Google Scholar