This meta-analysis aims to assess the impact of Simulation-Based Learning (SBL) on complex cognitive skills in higher learning institutions with data from 145 studies involving 10,532 students and published between December 1903 and March 2024. This rationale is based on research evidence collected using a problem-solving learning approach and simulation to mimic real life situations. We quantify the extent of SBL’s effectiveness in developing skills across different areas of practice and to determine the moderating variables, which include the type of simulation, simulation length, instructional support, and learner attributes. The findings from the meta-study using a random-impacts model showed a positive Effect Size (ES) for overall SBL, but with significant heterogeneity. The most represented field was medical education with 126 articles, which positively influenced technical skills, overall problem-solving abilities, and diagnostic competencies. As for the interpersonal skills, there were only moderate gains in communication and teamwork skills. Instructional supports, such as knowledge conveyance and scaffolding, significantly enhanced learning outcomes, particularly when combined (e.g., knowledge conveyance with samples identified in 82 articles). We provided assurance that there was no publication bias, thus affirming the credibility of the findings. However, future research should investigate the effects of SBL over an extended period, include new technologies, and focus on the areas that are not well-represented to enhance SBL’s effectiveness and achieve the greatest gains in education.
C. Koh et al., “Investigating the Effect of 3D Simulation Based Learning on the Motivation and Performance of Engineering Students,” Journal of Engineering Education, vol. 99, no. 3, pp. 237–251, Jul. 2010, doi: 10.1002/j.2168-9830.2010.tb01059.x.
E. Winsberg, “Simulated Experiments: Methodology for a Virtual World,” Philosophy of Science, vol. 70, no. 1, pp. 105–125, Jan. 2003, doi: 10.1086/367872.
M. M. Asad, A. Naz, P. Churi, and M. M. Tahanzadeh, “Virtual Reality as Pedagogical Tool to Enhance Experiential Learning: A Systematic Literature Review,” Education Research International, vol. 2021, pp. 1–17, Nov. 2021, doi: 10.1155/2021/7061623.
W. C. McGaghie, S. B. Issenberg, E. R. Petrusa, and R. J. Scalese, “Revisiting ‘A critical review of simulation-based medical education research: 2003-2009,’” Medical Education, vol. 50, no. 10, pp. 986–991, Sep. 2016, doi: 10.1111/medu.12795.
M. El Hussein, G. Harvey, and L. Kilfoil, “Pre-Brief in Simulation-Based Experiences: A Scoping Review of the Literature,” Clinical Simulation in Nursing, vol. 61, pp. 86–95, Dec. 2021, doi: 10.1016/j.ecns.2021.08.003.
C. Hoyles, R. Noss, and R. Adamson, “Rethinking the Microworld Idea,” Journal of Educational Computing Research, vol. 27, no. 1, pp. 29–53, Jul. 2002, doi: 10.2190/u6x9-0m6h-mu1q-v36x.
H. M. Hodgetts, S. Packwood, F. Vachon, and S. Tremblay, “A microworld simulation of dynamic cognition as a test of executive function,” Journal of Clinical and Experimental Neuropsychology, vol. 45, no. 2, pp. 165–181, Feb. 2023, doi: 10.1080/13803395.2023.2214297.
J. J. G. van Merriënboer and J. Sweller, “Cognitive Load Theory and Complex Learning: Recent Developments and Future Directions,” Educational Psychology Review, vol. 17, no. 2, pp. 147–177, Jun. 2005, doi: 10.1007/s10648-005-3951-0.
N. Cowan, “Working Memory Underpins Cognitive Development, Learning, and Education,” Educational Psychology Review, vol. 26, no. 2, pp. 197–223, Dec. 2013, doi: 10.1007/s10648-013-9246-y.
N. Rutten, W. R. van Joolingen, and J. T. van der Veen, “The learning effects of computer simulations in science education,” Computers & Education, vol. 58, no. 1, pp. 136–153, Jan. 2012, doi: 10.1016/j.compedu.2011.07.017.
P. Hallinger and R. Wang, “The Evolution of Simulation-Based Learning Across the Disciplines, 1965–2018: A Science Map of the Literature,” Simulation & Gaming, vol. 51, no. 1, pp. 9–32, Dec. 2019, doi: 10.1177/1046878119888246.
S. E. Husebø, M. Silvennoinen, E. Rosqvist, and I. Masiello, “Status of Nordic research on simulation-based learning in healthcare: an integrative review,” Advances in Simulation, vol. 3, no. 1, Jul. 2018, doi: 10.1186/s41077-018-0071-8.
H. J. WALTON and M. B. MATTHEWS, “Essentials of problem-based learning,” Medical Education, vol. 23, no. 6, pp. 542–558, Nov. 1989, doi: 10.1111/j.1365-2923.1989.tb01581.x.
V. Rajaguru and J. Park, “Contemporary Integrative Review in Simulation-Based Learning in Nursing,” International Journal of Environmental Research and Public Health, vol. 18, no. 2, p. 726, Jan. 2021, doi: 10.3390/ijerph18020726.
Kinshuk, N.-S. Chen, I.-L. Cheng, and S. W. Chew, “Evolution Is not enough: Revolutionizing Current Learning Environments to Smart Learning Environments,” International Journal of Artificial Intelligence in Education, vol. 26, no. 2, pp. 561–581, Feb. 2016, doi: 10.1007/s40593-016-0108-x.
H. Rodrigues, F. Almeida, V. Figueiredo, and S. L. Lopes, “Tracking e-learning through published papers: A systematic review,” Computers & Education, vol. 136, pp. 87–98, Jul. 2019, doi: 10.1016/j.compedu.2019.03.007.
Z.-T. Zhu, M.-H. Yu, and P. Riezebos, “A research framework of smart education,” Smart Learning Environments, vol. 3, no. 1, Mar. 2016, doi: 10.1186/s40561-016-0026-2.
A. Holzinger, M. D. Kickmeier-Rust, S. Wassertheurer, and M. Hessinger, “Learning performance with interactive simulations in medical education: Lessons learned from results of learning complex physiological models with the HAEMOdynamics SIMulator,” Computers & Education, vol. 52, no. 2, pp. 292–301, Feb. 2009, doi: 10.1016/j.compedu.2008.08.008.
G. Alinier and D. Oriot, “Simulation-based education: deceiving learners with good intent,” Advances in Simulation, vol. 7, no. 1, Mar. 2022, doi: 10.1186/s41077-022-00206-3.
R. L. Lamb, L. Annetta, J. Firestone, and E. Etopio, “A meta-analysis with examination of moderators of student cognition, affect, and learning outcomes while using serious educational games, serious games, and simulations,” Computers in Human Behavior, vol. 80, pp. 158–167, Mar. 2018, doi: 10.1016/j.chb.2017.10.040.
M. Dunleavy, C. Dede, and R. Mitchell, “Affordances and Limitations of Immersive Participatory Augmented Reality Simulations for Teaching and Learning,” Journal of Science Education and Technology, vol. 18, no. 1, pp. 7–22, Sep. 2008, doi: 10.1007/s10956-008-9119-1.
E. A. Nadaraya, “On Estimating Regression,” Theory of Probability & Its Applications, vol. 9, no. 1, pp. 141–142, Jan. 1964, doi: 10.1137/1109020.
R. Brooks et al., “CHARMM: The biomolecular simulation program,” Journal of Computational Chemistry, vol. 30, no. 10, pp. 1545–1614, May 2009, doi: 10.1002/jcc.21287.
R. B. Cooper and R. W. Zmud, “Information Technology Implementation Research: A Technological Diffusion Approach,” Management Science, vol. 36, no. 2, pp. 123–139, Feb. 1990, doi: 10.1287/mnsc.36.2.123.
D. Vlachopoulos and A. Makri, “The effect of games and simulations on higher education: a systematic literature review,” International Journal of Educational Technology in Higher Education, vol. 14, no. 1, Jul. 2017, doi: 10.1186/s41239-017-0062-1.
H.-M. Huang, U. Rauch, and S.-S. Liaw, “Investigating learners’ attitudes toward virtual reality learning environments: Based on a constructivist approach,” Computers & Education, vol. 55, no. 3, pp. 1171–1182, Nov. 2010, doi: 10.1016/j.compedu.2010.05.014.
G. F. Dillon and B. E. Clauser, “Computer-Delivered Patient Simulations in the United States Medical Licensing Examination (USMLE),” Simulation in Healthcare: The Journal of the Society for Simulation in Healthcare, vol. 4, no. 1, pp. 30–34, 2009, doi: 10.1097/sih.0b013e3181880484.
M. T. KANE, “Validating Interpretive Arguments for Licensure and Certification Examinations,” Evaluation & the Health Professions, vol. 17, no. 2, pp. 133–159, Jun. 1994, doi: 10.1177/016327879401700202.
Y. Okuda et al., “The Utility of Simulation in Medical Education: What Is the Evidence?,” Mount Sinai Journal of Medicine: A Journal of Translational and Personalized Medicine, vol. 76, no. 4, pp. 330–343, Jul. 2009, doi: 10.1002/msj.20127.
V. Terzis and A. A. Economides, “The acceptance and use of computer based assessment,” Computers & Education, vol. 56, no. 4, pp. 1032–1044, May 2011, doi: 10.1016/j.compedu.2010.11.017.
N. A. Morris, B. M. Czeisler, and A. Sarwal, “Simulation in Neurocritical Care: Past, Present, and Future,” Neurocritical Care, vol. 30, no. 3, pp. 522–533, Oct. 2018, doi: 10.1007/s12028-018-0629-2.
R. J. Mislevy, “Evidence-Centered Design for Simulation-Based Assessment,” Military Medicine, vol. 178, no. 10S, pp. 107–114, Oct. 2013, doi: 10.7205/milmed-d-13-00213.
D. A. Cook and R. Hatala, “Validation of educational assessments: a primer for simulation and beyond,” Advances in Simulation, vol. 1, no. 1, Jan. 2016, doi: 10.1186/s41077-016-0033-y.
A. Gegenfurtner, C. Quesada‐Pallarès, and M. Knogler, “Digital simulation‐based training: A meta‐analysis,” British Journal of Educational Technology, vol. 45, no. 6, pp. 1097–1114, Jul. 2014, doi: 10.1111/bjet.12188.
M. J. Zieky, “An introduction to the use of evidence-centered design in test development,” Psicología Educativa, vol. 20, no. 2, pp. 79–87, Dec. 2014, doi: 10.1016/j.pse.2014.11.003.
M. Arieli-Attali, S. Ward, J. Thomas, B. Deonovic, and A. A. von Davier, “The Expanded Evidence-Centered Design (e-ECD) for Learning and Assessment Systems: A Framework for Incorporating Learning Goals and Processes Within Assessment Design,” Frontiers in Psychology, vol. 10, Apr. 2019, doi: 10.3389/fpsyg.2019.00853.
Y. J. Kim, R. G. Almond, and V. J. Shute, “Applying Evidence-Centered Design for the Development of Game-Based Assessments in Physics Playground,” International Journal of Testing, vol. 16, no. 2, pp. 142–163, Dec. 2015, doi: 10.1080/15305058.2015.1108322.
C. A. Chapelle et al., “Designing a Prototype Tablet‐Based Learning‐Oriented Assessment for Middle School English Learners: An Evidence‐Centered Design Approach,” ETS Research Report Series, vol. 2018, no. 1, pp. 1–55, Dec. 2018, doi: 10.1002/ets2.12232.
J. Clarke-Midura, D. Silvis, J. F. Shumway, V. R. Lee, and J. S. Kozlowski, “Developing a kindergarten computational thinking assessment using evidence-centered design: the case of algorithmic thinking,” Computer Science Education, vol. 31, no. 2, pp. 117–140, Feb. 2021, doi: 10.1080/08993408.2021.1877988.
S. Bechard, A. Clark, R. Swinburne Romine, M. Karvonen, N. Kingston, and K. Erickson, “Use of Evidence-Centered Design to Develop Learning Maps-Based Assessments,” International Journal of Testing, vol. 19, no. 2, pp. 188–205, Apr. 2019, doi: 10.1080/15305058.2018.1543310.
A. Franklin and M. Luctkar-Flude, “2020 to 2023 Research Priorities Advance INACSL Core Values,” Clinical Simulation in Nursing, vol. 47, pp. 82–83, Oct. 2020, doi: 10.1016/j.ecns.2020.09.001.
A. Mohd Khalil, K. L. Lee, Z. A. Kamaruzzaman, and C. A. Ong, “Effectiveness of simulation-based learning in Malaysian higher education: a case study of MonsoonSIM,” Asian Education and Development Studies, vol. 13, no. 1, pp. 64–77, Jan. 2024, doi: 10.1108/aeds-09-2023-0125.
M. Shahin, M. Ali Babar, and L. Zhu, “Continuous Integration, Delivery and Deployment: A Systematic Review on Approaches, Tools, Challenges and Practices,” IEEE Access, vol. 5, pp. 3909–3943, 2017, doi: 10.1109/access.2017.2685629.
J. Wrammert, S. Sapkota, K. Baral, A. KC, M. Målqvist, and M. Larsson, “Teamwork among midwives during neonatal resuscitation at a maternity hospital in Nepal,” Women and Birth, vol. 30, no. 3, pp. 262–269, Jun. 2017, doi: 10.1016/j.wombi.2017.02.002.
A. Baldwin, C. Harvey, E. Willis, B. Ferguson, and T. Capper, “Transitioning across professional boundaries in midwifery models of care: A literature review,” Women and Birth, vol. 32, no. 3, pp. 195–203, Jun. 2019, doi: 10.1016/j.wombi.2018.08.003.
M. M. Butler, D. M. Fraser, and R. J. L. Murphy, “What are the essential competencies required of a midwife at the point of registration?,” Midwifery, vol. 24, no. 3, pp. 260–269, Sep. 2008, doi: 10.1016/j.midw.2006.10.010.
H. Donovan and E. Forster, “Communication Adaption in Challenging Simulations for Student Nurse Midwives,” Clinical Simulation in Nursing, vol. 11, no. 10, pp. 450–457, Oct. 2015, doi: 10.1016/j.ecns.2015.08.004.
P. B. Angood et al., “Blueprint for Action,” Women’s Health Issues, vol. 20, no. 1, pp. S18–S49, Jan. 2010, doi: 10.1016/j.whi.2009.11.007.
S. Stapleton, “Team-Building Making Collaborative Practice Work,” Journal of Nurse-Midwifery, vol. 43, no. 1, pp. 12–18, Feb. 1998, doi: 10.1016/s0091-2182(97)00119-5.
A. Alspaugh, J. Barroso, M. Reibel, and S. Phillips, “Women’s Contraceptive Perceptions, Beliefs, and Attitudes: An Integrative Review of Qualitative Research,” Journal of Midwifery & Women’s Health, vol. 65, no. 1, pp. 64–84, May 2019, doi: 10.1111/jmwh.12992.
B. Binder, T. Morehead Dworkin, N. Nae, C. Schipani, and I. Averianova, “The Plight of Women in Positions of Corporate Leadership in the United States, the European Union, and Japan: Differing Laws and Cultures, Similar Issues,” Michigan Journal of Gender & Law, no. 26.2, p. 279, 2020, doi: 10.36641/mjgl.26.2.plight.
International Monetary Fund, “Burkina Faso: Poverty Reduction Strategy Paper Annual Progress Report,” IMF Staff Country Reports, vol. 07, no. 320, p. i, 2007, doi: 10.5089/9781451803921.002.
Chodzaza, “Quality of care rendered to women with major obstetric complications in Mwanza district, Southern Malawi,” 2008. [Online]. Available: https://www.duo.uio.no/bitstream/10852/30009/2/ChodzazaxElisabeth.pdf.
P. N. Horns, L. P. Ratcliffe, J. C. Leggett, and M. S. Swanson, “Pregnancy Outcomes Among Active and Sedentary Primiparous Women,” Journal of Obstetric, Gynecologic & Neonatal Nursing, vol. 25, no. 1, pp. 49–54, Jan. 1996, doi: 10.1111/j.1552-6909.1996.tb02512.x.
O. Chernikova, N. Heitzmann, M. Stadler, D. Holzberger, T. Seidel, and F. Fischer, “Simulation-Based Learning in Higher Education: A Meta-Analysis,” Review of Educational Research, vol. 90, no. 4, pp. 499–541, Jun. 2020, doi: 10.3102/0034654320933544.
A. Topping et al., “Towards identifying nurse educator competencies required for simulation-based learning: A systemised rapid review and synthesis,” Nurse Education Today, vol. 35, no. 11, pp. 1108–1113, Nov. 2015, doi: 10.1016/j.nedt.2015.06.003.
B.-O. Lee, H.-F. Liang, T.-P. Chu, and C.-C. Hung, “Effects of simulation-based learning on nursing student competences and clinical performance,” Nurse Education in Practice, vol. 41, p. 102646, Nov. 2019, doi: 10.1016/j.nepr.2019.102646.
G. Ford, A. L. Seybert, P. L. Smithburger, L. R. Kobulinsky, J. T. Samosky, and S. L. Kane-Gill, “Impact of simulation-based learning on medication error rates in critically ill patients,” Intensive Care Medicine, vol. 36, no. 9, pp. 1526–1531, Mar. 2010, doi: 10.1007/s00134-010-1860-2.
L. Sarfati et al., “Human‐simulation‐based learning to prevent medication error: A systematic review,” Journal of Evaluation in Clinical Practice, vol. 25, no. 1, pp. 11–20, Jan. 2018, doi: 10.1111/jep.12883.
M. M. Jansson, H. P. Syrjälä, P. P. Ohtonen, M. H. Meriläinen, H. A. Kyngäs, and T. I. Ala-Kokko, “Randomized, controlled trial of the effectiveness of simulation education: A 24-month follow-up study in a clinical setting,” American Journal of Infection Control, vol. 44, no. 4, pp. 387–393, Apr. 2016, doi: 10.1016/j.ajic.2015.10.035.
Z. Mohanna, S. Kusljic, and R. Jarden, “Investigation of interventions to reduce nurses’ medication errors in adult intensive care units: A systematic review,” Australian Critical Care, vol. 35, no. 4, pp. 466–479, Jul. 2022, doi: 10.1016/j.aucc.2021.05.012.
Y. Guo, J. Li, C.-I. Li, J. Long, D. C. Samuels, and Y. Shyr, “The effect of strand bias in Illumina short-read sequencing data,” BMC Genomics, vol. 13, no. 1, Nov. 2012, doi: 10.1186/1471-2164-13-666.
Z. S. Aman, N. N. DePhillipo, L. A. Peebles, F. Familiari, R. F. LaPrade, and T. J. Dekker, “Improved Accuracy of Coronal Alignment Can Be Attained Using 3D-Printed Patient-Specific Instrumentation for Knee Osteotomies: A Systematic Review of Level III and IV Studies,” Arthroscopy: The Journal of Arthroscopic & Related Surgery, vol. 38, no. 9, pp. 2741–2758, Sep. 2022, doi: 10.1016/j.arthro.2022.02.023.
S. Y. Kim et al., “Design of association studies with pooled or un‐pooled next‐generation sequencing data,” Genetic Epidemiology, vol. 34, no. 5, pp. 479–491, Jun. 2010, doi: 10.1002/gepi.20501.
J. O’Rawe et al., “Low concordance of multiple variant-calling pipelines: practical implications for exome and genome sequencing,” Genome Medicine, vol. 5, no. 3, Mar. 2013, doi: 10.1186/gm432.
L. McKenna, F. Bogossian, H. Hall, S. Brady, S. Fox-Young, and S. Cooper, “Is simulation a substitute for real life clinical experience in midwifery? A qualitative examination of perceptions of educational leaders,” Nurse Education Today, vol. 31, no. 7, pp. 682–686, Oct. 2011, doi: 10.1016/j.nedt.2011.02.014.
Al-Elq, “Simulation-based medical teaching and learning,” Journal of Family and Community Medicine, vol. 17, no. 1, p. 35, 2010, doi: 10.4103/1319-1683.68787.
D. Kaufman and A. Ireland, “Enhancing Teacher Education with Simulations,” TechTrends, vol. 60, no. 3, pp. 260–267, Mar. 2016, doi: 10.1007/s11528-016-0049-0.
S. A. Azer, A. P. S. Guerrero, and A. Walsh, “Enhancing learning approaches: Practical tips for students and teachers,” Medical Teacher, vol. 35, no. 6, pp. 433–443, Mar. 2013, doi: 10.3109/0142159x.2013.775413.
T. Dwyer, K. Reid Searl, M. McAllister, M. Guerin, and D. Friel, “Advanced life simulation: High-fidelity simulation without the high technology,” Nurse Education in Practice, vol. 15, no. 6, pp. 430–436, Nov. 2015, doi: 10.1016/j.nepr.2015.05.007.
Y. Yamazaki, I. Hiyamizu, K. Joyner, J. Otaki, and Y. Abe, “Assessment of blood pressure measurement skills in second-year medical students after ongoing simulation-based education and practice,” Medical Education Online, vol. 26, no. 1, Nov. 2020, doi: 10.1080/10872981.2020.1841982.
I. Nakamura et al., “Scenario-based simulation health care education for performance of hand hygiene,” American Journal of Infection Control, vol. 47, no. 2, pp. 144–148, Feb. 2019, doi: 10.1016/j.ajic.2018.07.024.
P. Boonmak et al., “Simulation-based medical education in Thailand: a cross-sectional online national survey,” BMC Medical Education, vol. 22, no. 1, Apr. 2022, doi: 10.1186/s12909-022-03369-9.
P. Bhaskar, P. Bhaskar, A. Anthonisamy, P. Dayalan, and A. Joshi, “Inhibiting factors influencing adoption of simulation-based teaching from management teacher’s perspective: prioritisation using analytic hierarchy process,” International Journal of Learning and Change, vol. 15, no. 5, pp. 529–551, 2023, doi: 10.1504/ijlc.2023.133110.
Ke and X. Xu, “Virtual reality simulation‐based learning of teaching with alternative perspectives taking,” British Journal of Educational Technology, vol. 51, no. 6, pp. 2544–2557, Apr. 2020, doi: 10.1111/bjet.12936.
M. G. Jamil and S. O. Isiaq, “Teaching technology with technology: approaches to bridging learning and teaching gaps in simulation-based programming education,” International Journal of Educational Technology in Higher Education, vol. 16, no. 1, Aug. 2019, doi: 10.1186/s41239-019-0159-9.
Y. Kurashima, Y. Watanabe, Y. Ebihara, S. Murakami, T. Shichinohe, and S. Hirano, “Where do we start? The first survey of surgical residency education in Japan,” The American Journal of Surgery, vol. 211, no. 2, pp. 405–410, Feb. 2016, doi: 10.1016/j.amjsurg.2015.09.004.
Q. Wu, Y. Wang, L. Lu, Y. Chen, H. Long, and J. Wang, “Virtual Simulation in Undergraduate Medical Education: A Scoping Review of Recent Practice,” Frontiers in Medicine, vol. 9, Mar. 2022, doi: 10.3389/fmed.2022.855403.
I. Theodoulou, M. Nicolaides, T. Athanasiou, A. Papalois, and M. Sideris, “Simulation-Based Learning Strategies to Teach Undergraduate Students Basic Surgical Skills: A Systematic Review,” Journal of Surgical Education, vol. 75, no. 5, pp. 1374–1388, Sep. 2018, doi: 10.1016/j.jsurg.2018.01.013.
T. Kameda, N. Taniguchi, K. Konno, H. Koibuchi, K. Omoto, and K. Itoh, “Ultrasonography in undergraduate medical education: a comprehensive review and the education program implemented at Jichi Medical University,” Journal of Medical Ultrasonics, vol. 49, no. 2, pp. 217–230, Jan. 2022, doi: 10.1007/s10396-021-01178-z.
Y. K. Dwivedi et al., “Opinion Paper: ‘So what if ChatGPT wrote it?’ Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy,” International Journal of Information Management, vol. 71, p. 102642, Aug. 2023, doi: 10.1016/j.ijinfomgt.2023.102642.
K. F. Hew and T. Brush, “Integrating technology into K-12 teaching and learning: current knowledge gaps and recommendations for future research,” Educational Technology Research and Development, vol. 55, no. 3, pp. 223–252, Dec. 2006, doi: 10.1007/s11423-006-9022-5.
A. Hutchison and D. Reinking, “Teachers’ Perceptions of Integrating Information and Communication Technologies Into Literacy Instruction: A National Survey in the United States,” Reading Research Quarterly, vol. 46, no. 4, pp. 312–333, Oct. 2011, doi: 10.1002/rrq.002.
S. Archana, S. R. Nilakantam, B. Hathur, and M. Dayananda, “The Need and Art of Establishing Skill and Simulation Centers to Strengthen Skill-Based Medical Education,” Annals of African Medicine, vol. 20, no. 4, pp. 247–254, Oct. 2021, doi: 10.4103/aam.aam_53_20.
S. S. Elshama, “How to apply Simulation-Based Learning in Medical Education?,” Iberoamerican Journal of Medicine, vol. 2, no. 2, pp. 79–86, Mar. 2020, doi: 10.53986/ibjm.2020.0016.
R. Datta, K. Upadhyay, and C. Jaideep, “Simulation and its role in medical education,” Medical Journal Armed Forces India, vol. 68, no. 2, pp. 167–172, Apr. 2012, doi: 10.1016/s0377-1237(12)60040-9.
A. Banerjee et al., “A simulation-based curriculum to introduce key teamwork principles to entering medical students,” BMC Medical Education, vol. 16, no. 1, Nov. 2016, doi: 10.1186/s12909-016-0808-9.
F. Lateef, “Simulation-based learning: Just like the real thing,” Journal of Emergencies, Trauma, and Shock, vol. 3, no. 4, p. 348, 2010, doi: 10.4103/0974-2700.70743.
R. P. Cant and S. J. Cooper, “Simulation‐based learning in nurse education: systematic review,” Journal of Advanced Nursing, vol. 66, no. 1, pp. 3–15, Dec. 2009, doi: 10.1111/j.1365-2648.2009.05240.x.
R. M. Fanning and D. M. Gaba, “The Role of Debriefing in Simulation-Based Learning,” Simulation in Healthcare: The Journal of the Society for Simulation in Healthcare, vol. 2, no. 2, pp. 115–125, 2007, doi: 10.1097/sih.0b013e3180315539.
K. W. K. Chung, T. C. Harmon, and E. L. Baker, “The impact of a simulation-based learning design project on student learning,” IEEE Transactions on Education, vol. 44, no. 4, pp. 390–398, 2001, doi: 10.1109/13.965789.
F. Scholtz and S. Hughes, “A systematic review of educator interventions in facilitating simulation based learning,” Journal of Applied Research in Higher Education, vol. 13, no. 5, pp. 1408–1435, Mar. 2019, doi: 10.1108/jarhe-02-2018-0019.
N. Campos, M. Nogal, C. Caliz, and A. A. Juan, “Simulation-based education involving online and on-campus models in different European universities,” International Journal of Educational Technology in Higher Education, vol. 17, no. 1, Mar. 2020, doi: 10.1186/s41239-020-0181-y.
D. Rooney, N. Hopwood, D. Boud, and M. Kelly, “The Role of Simulation in Pedagogies of Higher Education for the Health Professions: Through a Practice-Based Lens,” Vocations and Learning, vol. 8, no. 3, pp. 269–285, Aug. 2015, doi: 10.1007/s12186-015-9138-z.
C. Tamilselvan, S. M. Chua, H. S. J. Chew, and M. K. Devi, “Experiences of simulation-based learning among undergraduate nursing students: A systematic review and meta-synthesis,” Nurse Education Today, vol. 121, p. 105711, Feb. 2023, doi: 10.1016/j.nedt.2023.105711.
Ma et al., “Enhancing Surgical Nursing Student Performance: Comparative Study of Simulation-Based Learning and Problem-Based Learning,” Journal of Multidisciplinary Healthcare, vol. Volume 17, pp. 991–1005, Mar. 2024, doi: 10.2147/jmdh.s440333.
O. Levin and H. Flavian, “Simulation-based learning in the context of peer learning from the perspective of preservice teachers: a case study,” European Journal of Teacher Education, vol. 45, no. 3, pp. 373–394, Oct. 2020, doi: 10.1080/02619768.2020.1827391.
M. Carethers, S. M. Quezada, R. M. Carr, and L. W. Day, “Diversity Within US Gastroenterology Physician Practices: The Pipeline, Cultural Competencies, and Gastroenterology Societies Approaches,” Gastroenterology, vol. 156, no. 4, pp. 829–833, Mar. 2019, doi: 10.1053/j.gastro.2018.10.056.
M. Sideris et al., “In vivo Simulation-Based Learning for Undergraduate Medical Students: Teaching and Assessment,” Advances in Medical Education and Practice, vol. Volume 12, pp. 995–1002, Aug. 2021, doi: 10.2147/amep.s272185.
S. Perera, S. O. Babatunde, J. Pearson, and D. Ekundayo, “Professional competency-based analysis of continuing tensions between education and training in higher education,” Higher Education, Skills and Work-Based Learning, vol. 7, no. 1, pp. 92–111, Feb. 2017, doi: 10.1108/heswbl-04-2016-0022.
I. Gast, K. Schildkamp, and J. T. van der Veen, “Team-Based Professional Development Interventions in Higher Education: A Systematic Review,” Review of Educational Research, vol. 87, no. 4, pp. 736–767, Apr. 2017, doi: 10.3102/0034654317704306.
L. Margalef García and N. Pareja Roblin, “Innovation, research and professional development in higher education: Learning from our own experience,” Teaching and Teacher Education, vol. 24, no. 1, pp. 104–116, Jan. 2008, doi: 10.1016/j.tate.2007.03.007.
P. Bradley, “The history of simulation in medical education and possible future directions,” Medical Education, vol. 40, no. 3, pp. 254–262, Mar. 2006, doi: 10.1111/j.1365-2929.2006.02394.x.
J. Moran, G. Briscoe, and S. Peglow, “Current Technology in Advancing Medical Education: Perspectives for Learning and Providing Care,” Academic Psychiatry, vol. 42, no. 6, pp. 796–799, Jun. 2018, doi: 10.1007/s40596-018-0946-y.
S. Thammasitboon, B. L. Ligon, G. Singhal, G. E. Schutze, and T. L. Turner, “Creating a medical education enterprise: leveling the playing fields of medical education vs. medical science research within core missions,” Medical Education Online, vol. 22, no. 1, p. 1377038, Jan. 2017, doi: 10.1080/10872981.2017.1377038.
H. Barbosa et al., “Human mobility: Models and applications,” Physics Reports, vol. 734, pp. 1–74, Mar. 2018, doi: 10.1016/j.physrep.2018.01.001.
Liu, Y. Wang, B. Li, and S. Ma, “Current research, key performances and future development of search and rescue robots,” Frontiers of Mechanical Engineering in China, vol. 2, no. 4, pp. 404–416, Oct. 2007, doi: 10.1007/s11465-007-0070-2.
S. Aslam, M. P. Michaelides, and H. Herodotou, “Internet of Ships: A Survey on Architectures, Emerging Applications, and Challenges,” IEEE Internet of Things Journal, vol. 7, no. 10, pp. 9714–9727, Oct. 2020, doi: 10.1109/jiot.2020.2993411.
S. Mamakli, M. K. Alimoğlu, and M. Daloğlu, “Scenario-based learning: preliminary evaluation of the method in terms of students’ academic achievement, in-class engagement, and learner/teacher satisfaction,” Advances in Physiology Education, vol. 47, no. 1, pp. 144–157, Mar. 2023, doi: 10.1152/advan.00122.2022.
K. MacKinnon, L. Marcellus, J. Rivers, C. Gordon, M. Ryan, and D. Butcher, “Student and educator experiences of maternal-child simulation-based learning: a systematic review of qualitative evidence protocol,” JBI Database of Systematic Reviews and Implementation Reports, vol. 13, no. 1, pp. 14–26, Jan. 2015, doi: 10.11124/jbisrir-2015-1694.
J. Dewey, “Democracy in Education,” The Elementary School Teacher, vol. 4, no. 4, pp. 193–204, Dec. 1903, doi: 10.1086/453309.
J. B. Labov, “From the National Academies: The Challenges and Opportunities for Improving Undergraduate Science Education through Introductory Courses,” Cell Biology Education, vol. 3, no. 4, pp. 212–214, Dec. 2004, doi: 10.1187/cbe.04-07-0049.
S. Clegg *, “Problematising ourselves: continuing professional development in higher education,” International Journal for Academic Development, vol. 8, no. 1–2, pp. 37–50, May 2003, doi: 10.1080/1360144042000277928.
H. SCHOMBURG, “The Professional Success of Higher Education Graduates,” European Journal of Education, vol. 42, no. 1, pp. 35–57, Feb. 2007, doi: 10.1111/j.1465-3435.2007.00286.x.
A. López-García, P. Miralles-Martínez, and J. Maquilón, “Design, Application and Effectiveness of an Innovative Augmented Reality Teaching Proposal through 3P Model,” Applied Sciences, vol. 9, no. 24, p. 5426, Dec. 2019, doi: 10.3390/app9245426.
W. W. S. Lee and C. K. K. Chan, “Relationships Among Epistemic Beliefs, Perception of Learning Environment, Study Approaches and Academic Performance: A Longitudinal Exploration with 3P Model,” The Asia-Pacific Education Researcher, vol. 27, no. 4, pp. 267–276, May 2018, doi: 10.1007/s40299-018-0384-3.
H. Han, “Closing the Missing Links and Opening the Relationships among the Factors: A Literature Review on the Use of Clicker Technology Using the 3P Model.,” Educational Technology & Society/Journal of Educational Technology & Society, vol. 17, no. 4, pp. 150–168, Oct. 2014, [Online]. Available: http://www.ifets.info/journals/17_4/10.pdf.
G. M. Slavich and P. G. Zimbardo, “Transformational Teaching: Theoretical Underpinnings, Basic Principles, and Core Methods,” Educational Psychology Review, vol. 24, no. 4, pp. 569–608, Jul. 2012, doi: 10.1007/s10648-012-9199-6.
S. Mueller and A. R. Anderson, “Understanding the entrepreneurial learning process and its impact on students’ personal development: A European perspective,” The International Journal of Management Education, vol. 12, no. 3, pp. 500–511, Nov. 2014, doi: 10.1016/j.ijme.2014.05.003.
J. Cope, “Toward a Dynamic Learning Perspective of Entrepreneurship,” Entrepreneurship Theory and Practice, vol. 29, no. 4, pp. 373–397, Jul. 2005, doi: 10.1111/j.1540-6520.2005.00090.x.
P. Smith III, A. A. diSessa, and J. Roschelle, “Misconceptions Reconceived: A Constructivist Analysis of Knowledge in Transition,” Journal of the Learning Sciences, vol. 3, no. 2, pp. 115–163, Apr. 1994, doi: 10.1207/s15327809jls0302_1.
K. Hogan, “Exploring a process view of students’ knowledge about the nature of science,” Science Education, vol. 84, no. 1, pp. 51–70, Jan. 2000, doi: 10.1002/(sici)1098-237x(200001)84:13.3.co;2-8.
M. Greene, “Chapter 10: Epistemology and Educational Research: The Influence of Recent Approaches to Knowledge,” Review of Research in Education, vol. 20, no. 1, pp. 423–464, Jan. 1994, doi: 10.3102/0091732x020001423.
S. T. M. Peek et al., “Older Adults’ Reasons for Using Technology while Aging in Place,” Gerontology, vol. 62, no. 2, pp. 226–237, Jun. 2015, doi: 10.1159/000430949.
Y. Jabareen, “A New Conceptual Framework for Sustainable Development,” Environment, Development and Sustainability, vol. 10, no. 2, pp. 179–192, Jul. 2006, doi: 10.1007/s10668-006-9058-z.
D. Yore and D. F. Treagust, “Current Realities and Future Possibilities: Language and science literacy—empowering research and informing instruction,” International Journal of Science Education, vol. 28, no. 2–3, pp. 291–314, Feb. 2006, doi: 10.1080/09500690500336973.
E. Haines et al., “Heart Rhythm Society Expert Consensus Statement on Electrophysiology Laboratory Standards: Process, Protocols, Equipment, Personnel, and Safety,” Heart Rhythm, vol. 11, no. 8, pp. e9–e51, Aug. 2014, doi: 10.1016/j.hrthm.2014.03.042.
R. Kanfer and P. L. Ackerman, “Motivation and cognitive abilities: An integrative/aptitude^treatment interaction approach to skill acquisition.,” Journal of Applied Psychology, vol. 74, no. 4, pp. 657–690, 1989, doi: 10.1037//0021-9010.74.4.657.
P. D. Zelazo, A. Carter, J. S. Reznick, and D. Frye, “Early development of executive function: A problem-solving framework.,” Review of General Psychology, vol. 1, no. 2, pp. 198–226, 1997, doi: 10.1037//1089-2680.1.2.198.
S. Ainsworth, “DeFT: A conceptual framework for considering learning with multiple representations,” Learning and Instruction, vol. 16, no. 3, pp. 183–198, Jun. 2006, doi: 10.1016/j.learninstruc.2006.03.001.
M. L. Gick and K. J. Holyoak, “Schema induction and analogical transfer,” Cognitive Psychology, vol. 15, no. 1, pp. 1–38, Jan. 1983, doi: 10.1016/0010-0285(83)90002-6.
J. Xi and J. P. Lantolf, “Scaffolding and the zone of proximal development: A problematic relationship,” Journal for the Theory of Social Behaviour, vol. 51, no. 1, pp. 25–48, Sep. 2020, doi: 10.1111/jtsb.12260.
G. Garcı́a-Cardeña et al., “Dissecting the Interaction between Nitric Oxide Synthase (NOS) and Caveolin,” Journal of Biological Chemistry, vol. 272, no. 41, pp. 25437–25440, Oct. 1997, doi: 10.1074/jbc.272.41.25437.
N. Kemp and R. Grieve, “Face-to-face or face-to-screen? Undergraduates’ opinions and test performance in classroom vs. online learning,” Frontiers in Psychology, vol. 5, Nov. 2014, doi: 10.3389/fpsyg.2014.01278.
S. L. Benko, “Scaffolding: An Ongoing Process to Support Adolescent Writing Development,” Journal of Adolescent & Adult Literacy, vol. 56, no. 4, pp. 291–300, Nov. 2012, doi: 10.1002/jaal.00142.
J. M. Carroll and J. C. Thomas, “Metaphor and the Cognitive Representation of Computing Systems,” IEEE Transactions on Systems, Man, and Cybernetics, vol. 12, no. 2, pp. 107–116, 1982, doi: 10.1109/tsmc.1982.4308795.
K. Allen, M. L. Kern, D. Vella-Brodrick, J. Hattie, and L. Waters, “What Schools Need to Know About Fostering School Belonging: a Meta-analysis,” Educational Psychology Review, vol. 30, no. 1, pp. 1–34, Oct. 2016, doi: 10.1007/s10648-016-9389-8.
X. Lin, “Designing metacognitive activities,” Educational Technology Research and Development, vol. 49, no. 2, pp. 23–40, Jun. 2001, doi: 10.1007/bf02504926.
D. Jonassen, “Supporting Problem Solving in PBL,” Interdisciplinary Journal of Problem-Based Learning, vol. 5, no. 2, Sep. 2011, doi: 10.7771/1541-5015.1256.
K.-E. Chang, Y.-L. Chen, H.-Y. Lin, and Y.-T. Sung, “Effects of learning support in simulation-based physics learning,” Computers & Education, vol. 51, no. 4, pp. 1486–1498, Dec. 2008, doi: 10.1016/j.compedu.2008.01.007.
R. Brydges et al., “Self-regulated learning in simulation-based training: a systematic review and meta-analysis,” Medical Education, vol. 49, no. 4, pp. 368–378, Mar. 2015, doi: 10.1111/medu.12649.
E. J. Lehr, “Blazing the trail for robot-assisted cardiac surgery,” The Journal of Thoracic and Cardiovascular Surgery, vol. 152, no. 1, pp. 14–17, Jul. 2016, doi: 10.1016/j.jtcvs.2016.05.001.
W. L. Oberkampf and T. G. Trucano, “Verification and validation in computational fluid dynamics,” Progress in Aerospace Sciences, vol. 38, no. 3, pp. 209–272, Apr. 2002, doi: 10.1016/s0376-0421(02)00005-2.
L. Treleaven and R. Voola, “Integrating the Development of Graduate Attributes Through Constructive Alignment,” Journal of Marketing Education, vol. 30, no. 2, pp. 160–173, May 2008, doi: 10.1177/0273475308319352.
CRediT Author Statement
The author reviewed the results and approved the final version of the manuscript.
Acknowledgements
The authors would like to thank to the reviewers for nice comments on the manuscript.
Funding
No funding was received to assist with the preparation of this manuscript.
Ethics declarations
Conflict of interest
The authors have no conflicts of interest to declare that are relevant to the content of this article.
Availability of data and materials
No data available for above study.
Author information
Contributions
All authors have equal contribution in the paper and all authors have read and agreed to the published version of the manuscript.
Corresponding author
Mohd Shahid Ali
School of Management, IILM University, Gurugram, Haryana, 122003.
Open Access This article is licensed under a Creative Commons Attribution NoDerivs is a more restrictive license. It allows you to redistribute the material commercially or non-commercially but the user cannot make any changes whatsoever to the original, i.e. no derivatives of the original work. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/
Cite this article
Mohd Shahid Ali, “A Meta Analysis of Simulation Based Learning and Instructional Support in Higher Education”, Journal of Enterprise and Business Intelligence, vol.5, no.4, pp. 234-247, October 2025. doi: 10.53759/5181/JEBI202505023.