طراحی چارچوب شبیه‌ساز شناختی برای ارتقای یادگیری مدیریت دانش در برنامه‌های آموزشی سازمانی

نوع مقاله : مقاله پژوهشی با اصالت

نویسندگان

1 استادیار، گروه علوم شناختی، دانشکده و پژوهشکده هوش مصنوعی و علوم شناختی، دانشگاه جامع امام حسین علیه السلام ، تهران، ایران، aminamini@ihu.ac.ir

2 استادیار، گروه مدیریت دانش، دانشکده و پژوهشکده هوش مصنوعی و علوم شناختی، دانشگاه جامع امام حسین علیه السلام، تهران، ایران، krasalehnj@ihu.ac.ir

3 دانشجوی کارشناسی ارشد مدیریت دانش، گروه مدیریت دانش، دانشکده و پژوهشکده هوش مصنوعی و علوم شناختی، دانشگاه جامع امام حسین علیه السلام، تهران، ایران، farshchianmohamadreza@gmail.com

10.47176/SMOK.2026.1984

چکیده

هدف: هدف پژوهش، طراحی چارچوب شبیه‌ساز شناختی برای یادگیری مدیریت دانش با بهره‌گیری از علوم شناختی در محیط‌های سازمانی است.
روش پژوهش: مطالعه کیفی با تحلیل مضمون، مصاحبه نیمه‌ساختاریافته با خبرگان مدیریت دانش، علوم شناختی، آموزش و فناوری (نمونه‌گیری گلوله‌برفی) انجام شد. روایی از طریق بازبینی مشارکت‌کنندگان و پایایی با ضریب توافق ۸۲٪ تأیید گردید. تحلیل داده‌ها با نرم‌افزار مکس کیودی‌آ و مراحل ولکات صورت گرفت.
یافته‌ها: هشت مؤلفه اصلی شناسایی شد: معرفی و هدف، بازیگران، طراحی و معماری، محیط، محتوای آموزشی، روش‌های ارزیابی، توسعه و به‌روزرسانی، عملکرد و کارایی. از ۱۲۰ مضمون پایه، ۳۲ مضمون سازمان‌دهنده و ۸ مضمون فراگیر استخراج شد. یادگیری مؤثر مستلزم فعالیت‌های تعاملی، نقش‌های شفاف، اشتراک دانش، بازخورد مستمر، هم‌راستایی اهداف و محیط شبیه‌سازی‌شده با ریسک و تصمیم‌گیری چندسطحی است.
بحث: این پژوهش در راستای همگرایی سه حوزه مدیریت دانش، علوم شناختی و شبیه‌سازی آموزشی است و این پژوهش نخستین چارچوب بومی شبیه‌ساز شناختی برای یادگیری مدیریت دانش در ایران و همگرایی سه حوزه مدیریت دانش، علوم شناختی و شبیه‌سازی آموزشی است.
نتیجه‌گیری: چارچوب ارائه‌شده می‌تواند به عنوان مدلی ساختاریافته برای طراحی شبیه‌سازهای شناختی در یادگیری مدیریت دانش مورد استفاده قرار گیرد و با افزایش تعامل، مشارکت و تجربه‌ورزی، کیفیت آموزش و توانمندی‌های دانشی یادگیرندگان را به شکل معناداری ارتقا دهد. این چارچوب به سازمان‌ها کمک می‌کند تا فرآیندهای یادگیری مدیریت دانش را واقعی‌سازی، فردمحور و پایدار سازند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Designing a cognitive simulator framework to enhance knowledge management learning in organizational training programs

نویسندگان [English]

  • Amin Amini 1
  • Abdollah Salehnezhad 2
  • Mohammad Ali Farshchian 3
1 Assistant Professor, Faculty of Artificial Intelligence and Cognitive Sciences, Imam Hossein University, Teheran, Iran, aminamini@ihu.ac.ir
2 Assistant Professor, Faculty of Artificial Intelligence and Cognitive Sciences, Imam Hossein University, Teheran, Iran, krasalehnj@ihu.ac.ir
3 Student Master's in the field of Knowledge Management, Faculty of Artificial Intelligence and Cognitive Sciences, Imam Hossein University, Teheran, Iran, farshchianmohamadreza@gmail.com
چکیده [English]

Purpose: The aim of the research is to design a cognitive simulator framework for knowledge management learning by utilizing cognitive sciences in organizational environments.
Methodology: A qualitative study with thematic analysis, semi-structured interviews with experts in knowledge management, cognitive sciences, education, and technology (snowball sampling) was conducted. Validity was confirmed through participant review, and reliability with an agreement coefficient of 82%. Data analysis was carried out using MAXQDA software and Wolcott's stages.
Results: Eight main components were identified: introduction and objective, actors, design and architecture, environment, educational content, evaluation methods, development and updating, performance and efficiency. From 120 basic themes, 32 organizing themes and 8 global themes were extracted. Effective learning requires interactive activities, clear roles, knowledge sharing, continuous feedback, alignment of objectives, and a simulated environment with risk and multi-level decision-making.
Discussion: This research is in line with the convergence of the three domains of knowledge management, cognitive sciences, and educational simulation, and this research is the first indigenous framework of a cognitive simulator for knowledge management learning in Iran and the convergence of the three domains of knowledge management, cognitive sciences, and educational simulation.
Conclusion: The presented framework can be used as a structured model for designing cognitive simulators in knowledge management learning and, by increasing interaction, participation, and experiential practice, significantly enhance the quality of education and the knowledge capabilities of learners. This framework helps organizations to make knowledge management learning processes realistic, person-centered, and sustainable.

کلیدواژه‌ها [English]

  • Cognitive simulator
  • Knowledge management learning
  • Simulation-based education
  • Thematic analysis
  • Cognitive science
  • Game-based learning
  • Organizational learning

Copyright ©, Amin Amini; Abdollah Salehnezhad; Mohammad Ali Farshchian

License

Published by Imam Hossein University. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode  

Abdillah, A., Widianingsih, I., Buchari, R. A., & Nurasa, H. (2024). The knowledge-creating company: How Japanese companies create the dynamics of innovation. Learning: Research and Practice, 10(1). https://doi.org/10.1080/23735082.2023.2272611
Ahmed, A., & Sutton, M. J. D. (2017). Gamification, serious games, simulations, and immersive learning environments in knowledge management initiatives. World Journal of Science, Technology and Sustainable Development, 14, 78-83.  https://doi.org/10.1108/wjstsd-02-2017-0005
Alavi, M., & Leidner, D. E. (2001). Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS Quarterly: Management Information Systems, 25(1). https://doi.org/10.2307/3250961
Alharbi, A., Nurfianti, A., Mullen, R. F., McClure, J. D., & Miller, W. H. (2024). The effectiveness of simulation-based learning (SBL) on students’ knowledge and skills in nursing programs: a systematic review. BMC Medical Education, 24. https://doi.org/10.1186/s12909-024-06080-z
Amin Amini. (2025). The defensive realm of cognitive science in optimizing human performance. Imam Hossein University Publications. (In Persian)
Samadiansari, H., Razavi, M., & Jafari, P. (2024). Developing A Model For Improving The Business Performance Of Nanotechnology Knowledge-Based Companies Based On Technological Learning Modes. Strategic Management of Organizational Knowledge7(1), 191-226. https://doi.org/10.47176/smok.2024.1678 (In Persian)
Asad, U., Khan, M., Khalid, A., & Lughmani, W. (2023). Human-Centric Digital Twins in Industry: A Comprehensive Review of Enabling Technologies and Implementation Strategies. Sensors (Basel, Switzerland), 23.  https://doi.org/10.3390/s23083938
Baceviciute, S., Cordoba, A. L., Wismer, P., Jensen, T. V., Klausen, M., & Makransky, G. (2021). Investigating the value of immersive virtual reality tools for organizational training: An applied international study in the biotech industry. J. Comput. Assist. Learn., 38, 470-487. https://doi.org/10.1111/jcal.12630
Bakken, B. T., & Gilljam, M. (2002). Training to Improve Decision Making - System dynamics applied to higher-level military operations. 20th International System Dynamics Conference. https://search.informit.org/doi/abs/10.3316/informit.196580402788886
Bandura, A. (1987). Social Foundations of Thought and Action (Book Review). Education, 108(1). https://doi.org/10.3143/geriatrics.44.107
Barrouillet, P., Bernardin, S., Portrat, S., Vergauwe, E., & Camos, V. (2007). Time and Cognitive Load in Working Memory. Journal of Experimental Psychology: Learning Memory and Cognition, 33(3). https://doi.org/10.1037/0278-7393.33.3.570
Birt, J., Stromberga, Z., Cowling, M., & Moro, C. (2018). Mobile mixed reality for experiential learning and simulation in medical and health sciences education. Information (Switzerland), 9(2). https://doi.org/10.3390/info9020031
Boghrati, F., ShamiZanjani, M., & Manian, A. (2019). Designing a Conceptual Framework for Knowledge Governance in Project-Based Organizations. Iranian Journal of Information Management, 4(2), 129–150. https://www.aimj.ir/article_87337.html
Bolisani, E., & Bratianu, C. (2017). Knowledge strategy planning: an integrated approach to manage uncertainty, turbulence, and dynamics. Journal of Knowledge Management, 21(2). https://doi.org/10.1108/JKM-02-2016-0071
Bratianu, C., & Bolisani, E. (2015). Knowledge strategy: An integrated approach for managing uncertainty. Proceedings of the European Conference on Knowledge Management, ECKM, 0. https://hdl.handle.net/11577/3188318
Cabana, G. C. (2021). The Wise Company: How Companies Create Continuous Innovation, by Ikujiro Nonaka and Hirotaka Takeuchi. Oxford: Oxford University Press, 2019. 304 pp. Business Ethics Quarterly, 31(2), 312–315. https://doi.org/10.1017/beq.2021.9
Chan, C. K. Y. (2012). Exploring an experiential learning project through Kolb’s Learning Theory using a qualitative research method. European Journal of Engineering Education, 37(4). https://doi.org/10.1080/03043797.2012.706596
Chen, B., & Teasley, S. (2020). Learning Analytics for Understanding and Supporting Collaboration (pp. 86–95). https://doi.org/10.18608/hla22.009
Chernikova, O., Heitzmann, N., Stadler, M., Holzberger, D., Seidel, T., & Fischer, F. (2020). Simulation-Based Learning in Higher Education: A Meta-Analysis. Review of Educational Research, 90, 499 - 541.  https://doi.org/10.3102/0034654320933544
Chernova, L., & Chernova, L. (2020). COGNITIVE MODELING OF KNOWLEDGE MANAGEMENT MECHANISMS IN THE TRAINING OF SPECIALISTS. Innovative Technologies and Scientific Solutions for Industries.  https://doi.org/10.30837/itssi.2020.14.086
Clausen, M., Miller, B., Bird, E., Payne, T., Bird, E., & Edu. (2025). Integrating Cognitive and Skills Training in a Simulated UAS (Unmanned Aerial Systems) Pilot Training Course. https://doi.org/10.2514/6.2025-3410
Cooke, N. J., Cohen, M. C., Fazio, W. C., Inderberg, L. H., Johnson, C. J., Lematta, G. J., Peel, M., & Teo, A. (2024). From Teams to Teamness: Future Directions in the Science of Team Cognition. Human Factors, 66(6). https://doi.org/10.1177/00187208231162449
Coulon, T., Cheikh‐Ammar, M., Bourdeau, S., & Petit, M.-C. (2025). Acquiring complex knowledge and skills through digital simulation‐based training: Evidence from an agile project management teaching experience. British Journal of Educational Technology.  https://doi.org/10.1111/bjet.70009
Cronan, T. P., Léger, P.-M., Robert, J., Babin, G., & Charland, P. (2012). Comparing Objective Measures and Perceptions of Cognitive Learning in an ERP Simulation Game. Simulation & Gaming, 43, 461 - 480.  https://doi.org/10.1177/1046878111433783
Davidovitch, L., Parush, A., & Shtub, A. (2006). Simulation-based learning in engineering education: Performance and transfer in learning project management. Journal of Engineering Education, 95(4).  https://doi.org/10.1002/j.2168-9830.2006.tb00904.x
De Fino, M., Cassano, F., Bernardini, G., Quagliarini, E., & Fatiguso, F. (2025). On the user-based assessments of virtual reality for public safety training in urban open spaces depending on immersion levels. Safety Science, 185, 106803.  https://doi.org/https://doi.org/10.1016/j.ssci.2025.106803
Deaton, S. (2015). Social Learning Theory in the Age of Social Media: Implications for Educational Practitioners. I-Manager’s Journal of Educational Technology, 12(1). https://doi.org/10.26634/jet.12.1.3430
Deranek, K., & Hewitt, B. (2022). Knowledge Management Model Development and Validation Using an ERP Simulation. Journal of Computer Information Systems, 63, 1139 - 1152.   https://doi.org/10.1080/08874417.2022.2128936
Endsley, T., Reep, J., McNeese, M. D., & Forster, P. (2015). Crisis Management Simulations: Lessons Learned from a Cross-cultural Perspective. Procedia Manufacturing, 3.  https://doi.org/10.1016/j.promfg.2015.07.918
Eskerod, P., & Min, K. K. (2025). Learning Outcomes in Advanced Simulations Within Higher Education – A Systematic Literature Review. LIMEN - International Scientific-Business Conference - Leadership, Innovation, Management and Economics: Integrated Politics of Research.   https://doi.org/10.31410/limen.2024.859
Fan, X., & Yen, J. (2004). Modeling and simulating human teamwork behaviors using intelligent agents. In Physics of Life Reviews (Vol. 1, Number 3). https://doi.org/10.1016/j.plrev.2004.10.001
Fraser, K. L., Ayres, P., & Sweller, J. (2015). Cognitive load theory for the design of medical simulations. In Simulation in Healthcare (Vol. 10, Number 5). https://doi.org/10.1097/SIH.0000000000000097
Grijalvo, M., Segura, A., & Núñez, Y. (2022). Computer-based business games in higher education: A proposal of a gamified learning framework. Technological Forecasting and Social Change.   https://doi.org/10.1016/j.techfore.2022.121597
Hendriks, P. H. J. (2005). Book Review: Knowledge Management in Organizations: A Critical Introduction. Management Learning, 36(4).  https://doi.org/10.1177/135050760503600411
Henry, H. R. (2011). Book Review: Learning to Solve Problems: A Handbook for Designing Problem-Solving Learning Environments. Interdisciplinary Journal of Problem-Based Learning, 5(2).  https://doi.org/10.7771/1541-5015.1257
Hirsto, L., Väisänen, S., Sointu, E., & Valtonen, T. (2024). Learning Analytics in Supporting Teaching and Learning: Pedagogical Perspectives (pp. 3–17).  https://doi.org/10.1007/978-3-031-54207-7_1
Hwang, A.-S. (2003). Training strategies in the management of knowledge. J. Knowl. Manag., 7, 92-104.   https://doi.org/10.1108/13673270310485659
Jossberger, H., Breckwoldt, J., & Gruber, H. (2022). Promoting Expertise Through Simulation (PETS): A conceptual framework. Learning and Instruction.  https://doi.org/10.1016/j.learninstruc.2022.101686
Kahol, K., Vankipuram, M., & Smith, M. L. (2009). Cognitive simulators for medical education and training. Journal of Biomedical Informatics, 42(4).  https://doi.org/10.1016/j.jbi.2009.02.008
Khademizadeh, S., Mohammadi, Z., Kohirostami, M., & Mehralizadeh, Y. (2024). Presenting the model of knowledge management in universities with a meta-synthesis approach. Strategic Management of Organizational Knowledge, 7(2), 75-106. https://doi.org/10.47176/smok.2024.1751  (In Persian)
Khaleghi, A., Aghaei, Z., & Mahdavi, M. (2021). A Gamification Framework for Cognitive Assessment and Cognitive Training: Qualitative Study. JMIR Serious Games, 9.   https://doi.org/10.2196/21900
King, W., Chung, R., & Haney, M. (2008). Knowledge Management and Organizational Learning. Omega, 36, 167–172.  https://doi.org/10.1016/j.omega.2006.07.004
Kolb, D. A. (1984). Experiential Learning: Experience as The Source of Learning and Development. Prentice Hall, Inc., (1984).  https://doi.org/10.1016/B978-0-7506-7223-8.50017-4
Kumar, B. (2022). Integration of AI and Neuroscience for Advancing Brain-Machine Interfaces: A Study. International Journal of New Media Studies: International Peer Reviewed Scholarly Indexed Journal, 9(1), 25–30. Retrieved from https://ijnms.com/index.php/ijnms/article/view/246
Kuzin, O. V. (2025). GAME-BASED LEARNING IN DEVELOPING ORGANIZATIONAL AND MANAGEMENT COMPETENCIES. The Modern Higher Education Review.   https://doi.org/10.28925/2617-5266/2025.108
Lavorato, D., & Piedepalumbo, P. (2023). How Smart Technologies Affect the Decision-Making and Control System of Food and Beverage Companies—A Case Study. Sustainability (Switzerland), 15(5).  https://doi.org/10.3390/su15054292
Leidner, D., Alavi, M., & Kayworth, T. (2006). The Role of Culture in Knowledge Management: A Case Study of Two Global Firms. International Journal of E-Collaboration (IJeC), 2(1).  https://doi.org/10.4018/jec.2006010102
Lin, C.-C., Huang, A. Y. Q., & Lu, O. H. T. (2023). Artificial intelligence in intelligent tutoring systems toward sustainable education: a systematic review. Smart Learning Environments, 10, 1-22.   https://doi.org/10.1186/s40561-023-00260-y
Lin, Y.-C., Chien, S.-Y., & Hou, H. (2024). A multi-dimensional scaffolding-based virtual reality educational board game design framework for service skills training. Education and Information Technologies, 30,  11251 - 11278.   https://doi.org/10.1007/s10639-024-13243-4
Lin, Y.-L., & Wang, W.-T. (2025). Using Business Simulation Games to Explore the Effects of Instructional and Technological Support on Students’ Psychological Needs, Cognitive Load, and Learning Achievement. Journal of Educational Computing Research, 63, 587 - 626.   https://doi.org/10.1177/07356331241313128
Liu, J., Luo, A. M., & Luo, X. S. (2009). A new military decision-making model from cognitive perspective. Proceedings of the 2009 International Conference on Machine Learning and Cybernetics, 2. https://doi.org/10.1109/ICMLC.2009.5212390
Loia, F., Capolupo, N., & Adinolfi, P. (2025). Training me softly. Metaverse-based immersive and gamified learning through a knowledge management perspective. J. Knowl. Manag., 29, 1465-1489.  https://doi.org/10.1108/jkm-08-2024-0929
Loibl, K., Leuders, T., & Dörfler, T. (2020). A Framework for Explaining Teachers’ Diagnostic Judgements by Cognitive Modeling (DiaCoM). In Teaching and Teacher Education (Vol. 91).  https://doi.org/10.1016/j.tate.2020.103059
Longo, F., Padovano, A., Felice, F., Petrillo, A., & Elbasheer, M. (2023). From "prepare for the unknown" to "train for what's coming": A digital twin-driven and cognitive training approach for the workforce of the future in smart factories. J. Ind. Inf. Integr., 32, 100437.  https://doi.org/10.1016/j.jii.2023.100437
M G, P. (2024). Augmenting Knowledge Management with Immersive Technologies: Exploring Transformative Use Cases for AR and VR.
Makhija, A., Jha, M., Richards, D., & Bilgin, A. (2022). Designing a feedback framework to reconnect students with learning in a game-based learning environment. ASCILITE Publications. https://doi.org/10.14742/apubs.2022.115
Mejeh, M., Sarbach, L., & Hascher, T. (2024). Effects of adaptive feedback through a digital tool – a mixed-methods study on the course of self-regulated learning. Education and Information Technologies, 29(14). https://doi.org/10.1007/s10639-024-12510-8
Moreno-Domínguez, M., Escobar-Rodríguez, T., Pelayo-Díaz, Y. M., & Tovar-García, I. (2024). Organizational culture and leadership style in Spanish Hospitals: Effects on knowledge management and efficiency. Heliyon, 10.  https://doi.org/10.1016/j.heliyon.2024.e39216
Mousavi, M., Rastgar, A. A., & Shafiei Nikabadi, M. (2025). The role of Artificial Intelligence in Promoting The Knowledge Of Positive Human Resource Management: A Causal Model. Strategic Management of Organizational Knowledge8(3), 11-35. https://doi.org/10.47176/smok.2025.1891 (In Persian)
Mousavinasab, E., Zarifsanaiey, N., Kalhori, S. R. N., Rakhshan, M., Keikha, L., & Saeedi, M. (2018). Intelligent tutoring systems: a systematic review of characteristics, applications, and evaluation methods. Interactive Learning Environments, 29, 142 - 163.  https://doi.org/10.1080/10494820.2018.1558257
Nonaka, I. (2009). A dynamic theory of organizational knowledge creation. In Knowledge, Groupware and the Internet. https://doi.org/10.1287/orsc.5.1.14
Nonaka, I., & Takeuchi, H. (2019). The wise company: How companies create continuous innovation. Oxford University Press. https://www.hbs.edu/faculty/Pages/item.aspx?num=56978
North, K. (2018). Knowledge Management Value Creation Through Organizational Learning. In Springer International Publishing AG, part of Springer Nature. https://doi.org/10.1007/978-3-319-59978-6
Oberlander, J. (1994). What is Cognitive Science? Teaching Philosophy, 17(4). https://doi.org/10.5840/teachphil199417443
Palmunen, L.-M., Lainema, T., & Pelto, E. (2021). Towards a manager's mental model: Conceptual change through business simulation. The International Journal of Management Education.  https://doi.org/10.1016/j.ijme.2021.100460
Pecaric, M., Boutis, K., & Pusic, M. (2016a). A Big Data and Learning Analytics Approach to Process-Level Feedback in Cognitive Simulations. Academic Medicine, 92, 1. https://doi.org/10.1097/ACM.0000000000001234
Pecaric, M., Boutis, K., & Pusic, M. (2016b). A Big Data and Learning Analytics Approach to Process-Level Feedback in Cognitive Simulations. Academic Medicine, 92, 1. https://doi.org/10.1097/ACM.0000000000001234
Ploder, C., Dilger, T., & Bernsteiner, R. (2020). IMPROVING KNOWLEDGE TRANSFER IN SIMULATION GAMES BASED ON COGNITIVE LOAD THEORY. https://doi.org/10.36315/2020end039
Reedy, G. (2015). Using Cognitive Load Theory to Inform Simulation Design and Practice. Clinical Simulation in Nursing, 11, 355-360.  https://doi.org/10.1016/j.ecns.2015.05.004
Reinhold, F., Leuders, T., Loibl, K., Nückles, M., Beege, M., & Boelmann, J. M. (2024). Learning Mechanisms Explaining Learning With Digital Tools in Educational Settings: a Cognitive Process Framework. In Educational Psychology Review (Vol. 36, Number 1). https://doi.org/10.1007/s10648-024-09845-6
Robert D. Galliers ir kt. (2020). Strategic Information Management: Theory and Practice. In Reutlege. https://doi.org/10.4324/9780429286797
Rochon, L.-J., Karran, A., Rolon-Merette, T., Courtemanche, F., Senecal, S., & Léger, P.-M. (2025). Cognition in the cockpit: assessing instructional modalities in pilot training simulations. Frontiers in Psychology, 16. https://doi.org/10.3389/fpsyg.2025.1625321
Rui, Z., El-Den, J., & Qianzhu, C. (2015). Knowledge Sharing in Enterprise Business Simulative Games: An Empirical Analysis. Journal of Information and Knowledge Management, 14(4). https://doi.org/10.1142/S021964921550032X
Salas-Guerra, R. (2025). Cognitive AI framework: advances in the simulation of human thought. https://doi.org/10.48550/arXiv.2502.04259
Salehnezhad, A., Shadmanfar, M. H., & Zolfaghari, Y. (2024). Presenting a model of key competencies and specialized skills of knowledge workers in the knowledge-based era using content analysis. Strategic Management of Organizational Knowledge, 7(4), 35-61. https://doi.org/10.47176/smok.2024.1810  (In Persian)
Șandor, A., & Tonţ, G. (2021). Knowledge Management in Military Organizations. A Seci Model Perspective. International Conference KNOWLEDGE-BASED ORGANIZATION, 27(1). https://doi.org/10.2478/kbo-2021-0036
Schinko, T., & Bednar-Friedl, B. (2022). Fostering social learning through role-play simulations to operationalize comprehensive climate risk management: Insights from applying the RESPECT role-play in Austria. Climate Risk Management, 35. https://doi.org/10.1016/j.crm.2022.100418
Secundo, G., Schiuma, G., & Passiante, G. (2017). Entrepreneurial learning dynamics in knowledge-intensive enterprises. International Journal of Entrepreneurial Behaviour and Research, 23(3). https://doi.org/10.1108/IJEBR-01-2017-0020
Segura, S., & Morris, M. W. (2005). Scenario simulations in learning: Forms and functions at the individual and organizational levels. In The Psychology of Counterfactual Thinking. https://doi.org/10.4324/9780203963784
Sennersten, C. (2010). Model Based Simulation Training Supporting Military Operational Process. In Blekinge Institute of Technology Doctoral Dissertation Series No.2010:05.
Shwedeh, F., Aburayya, A., Gbemisola, O., & Adelaja, A. A. (2024). Assessing the role of augmented reality in enhancing employee operational engagement and knowledge retention in UAE business training. Global Knowledge, Memory and Communication. https://doi.org/10.1108/GKMC-05-2024-0287
Sisakhti, M., Sachdev, P. S., & Batouli, S. A. H. (2021). The Effect of Cognitive Load on the Retrieval of Long-Term Memory: An fMRI Study. Frontiers in Human Neuroscience, 15. https://doi.org/10.3389/fnhum.2021.700146
Sitzmann, T. (2011). A META-ANALYTIC EXAMINATION OF THE INSTRUCTIONAL EFFECTIVENESS OF COMPUTER-BASED SIMULATION GAMES. Personnel Psychology, 64, 489-528.  https://doi.org/10.1111/j.1744-6570.2011.01190.x
Sottilare, R. A. (2024). Examining the Role of Knowledge Management in Adaptive Military Training Systems. In R. A. Sottilare & J. Schwarz (Eds.), Adaptive Instructional Systems (pp. 300–313). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-60609-0_22
Sun, R., Coward, L. A., & Zenzen, M. J. (2005). On levels of cognitive modeling. In Philosophical Psychology (Vol. 18, Number 5).  https://doi.org/10.1080/09515080500264248
Sweller, J. (2011). Cognitive load theory. In Psychology of learning and motivation (Vol. 55, pp. 37–76). Elsevier. https://doi.org/10.1007/s10648-011-9179-2
Tahanpour, S., Araei, V., Azimzadeh Irani, M., & Pourezat, A. (2024). The use of artificial intelligence and knowledge management in improving corporate governance a case study of mapna company. Strategic Management of Organizational Knowledge7(4), 141-163. https://doi.org/10.47176/smok.2024.1813 (In Persian)
Tavakoli, M. H., & Momivand, H. (2025). The Evolution of Knowledge Management Generations with a Focus on the Fourth Generation: Revisiting the SECI Model. Strategic Management of Organizational Knowledge, 8(3), 114-146. https://doi.org/10.47176/smok.2025.1938 (In Persian)
Tavallaei, R. (2024). The importance of organizational knowledge management in the process of scientific theorizing. Strategic Management of Organizational Knowledge, 7(1), 11-18. https://doi.org/10.47176/smok.2024.1118 (In Persian)
Tomé, E., & Gromova, E. (2021). Development of emergent knowledge strategies and new dynamic capabilities for business education in a time of crisis. Sustainability (Switzerland), 13(8). https://doi.org/10.3390/su13084518
van Ments, L., & Treur, J. (2021). Reflections on dynamics, adaptation and control: A cognitive architecture for mental models. Cognitive Systems Research, 70. https://doi.org/10.1016/j.cogsys.2021.06.004
van Ments, L., & Treur, J. (2022). Dynamics, Adaptation and Control for Mental Models: A Cognitive Architecture. In Studies in Systems, Decision and Control (Vol. 394). https://doi.org/10.1007/978-3-030-85821-6_1
Waring, S. (2012). Immersive Simulated Learning Environments for Researching Critical Incidents: A Knowledge Synthesis of the Literature and Experiences of Studying High-Risk Strategic Decision Making. Journal of Cognitive Engineering and Decision Making, 20. https://doi.org/10.1177/1555343412468113
Wolcott, H. F. (2002). Writing up qualitative research... better. Qualitative Health Research, 12(1), 91–103. https://doi.org/10.1177/1049732302012001007
Wolcott, H., & Schnitter Castellanos, M. (2008). Writing up qualitative research … better. Investigación y Educación En Enfermería, 22(2). https://doi.org/10.17533/udea.iee.2961
Xu, Q., Liu, Y., & Li, X. (2025). Unlocking student potential: How AI-driven personalized feedback shapes goal achievement, self-efficacy, and learning engagement through a self-determination lens. Learning and Motivation, 91, 102138. https://doi.org/https://doi.org/10.1016/j.lmot.2025.102138
Yeşil, S., Koska, A., & Büyükbeşe, T. (2013). Knowledge Sharing Process, Innovation Capability and Innovation Performance: An Empirical Study. Procedia - Social and Behavioral Sciences, 75. https://doi.org/10.1016/j.sbspro.2013.04.025
Zachary, W. W., Ryder, J. M., & Hicinbothom, J. H. (2004). Cognitive task analysis and modeling of decision making in complex environments. In Making decisions under stress: Implications for individual and team training. https://doi.org/10.1037/10278-012
Zahedi, A., Lynn, S., & Sommer, W. (2024). Cognitive simulation along with neural adaptation explain effects of suggestions: a novel theoretical framework. Frontiers in Psychology, 15. https://doi.org/10.3389/fpsyg.2024.1388347
Zbrishchak, S. (2025). Cognitive modeling: theoretical bases, methods, limitations. Russian Journal of Economics and Law.   https://doi.org/10.21202/2782-2923.2025.3.675-695
Zenios, M. (2020). Educational theory in technology enhanced learning revisited: A model for simulation-based learning in higher education. Studies in Technology Enhanced Learning. https://doi.org/10.21428/8c225f6e.1cf4dde8
Zerafati, M. H., & Hosseinpour, R. (2024). Knowledge management in higher education: a meta-synthesis of success factors, challenges, and implementation strategies. Strategic Management of Organizational Knowledge, 7(4), 63-90. https://doi.org/10.47176/smok.2024.1792 (In Persian)
Zhang, F., Yang, B., & Zhu, L. (2023). Digital technology usage, strategic flexibility, and business model innovation in traditional manufacturing firms: The moderating role of the institutional environment. Technological Forecasting and Social Change, 194. https://doi.org/10.1016/j.techfore.2023.122726
Zwikael, O., Shtub, A., & Chih, Y.-Y. (2015). Simulation-Based Training for Project Management Education: Mind the Gap, As One Size Does Not Fit All. Journal of Management in Engineering, 31, 04014035. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000238

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