STRATEGIC HUMAN RESOURCE MANAGEMENT AND INNOVATION: TRANSLATING PEDAGOGICAL FRAMEWORKS FROM LINGUISTIC AND EDUCATIONAL AI SIMULATIONS TO FACILITATE NON-TECHNICAL SKILL DEVELOPMENT
DOI:
https://doi.org/10.35794/v49hth29Abstract
Industry 5.0 has increased the importance of non-technical skills (NTS), such as communication, collaborative reasoning, and stakeholder engagement, as strategic capabilities for organizational innovation. However, engineering education continues to exhibit a persistent gap between technical competence and industry expectations. This study conducts a Systematic Literature Review (SLR) to identify pedagogical frameworks from healthcare, language education, and AI-supported simulations that can be translated to support non-technical skill development in Human Factors Engineering and Strategic Human Resource Management. Using a two-track "Anchor-and-Expand" review strategy, the study synthesized evidence from 88 core studies selected from more than 800 screened publications. The findings indicate that effective AI-supported learning environments are inherently transdisciplinary, integrating structured diagnostic reasoning from healthcare with adaptive conversational scaffolding from language education. The review further identifies five key design principles: differentiated pedagogical strategies, functional specialization through multi-agent architectures, immersive role-play, multimodal competency assessment, and cross-domain translation of validated behavioral assessment frameworks. These findings provide an evidence-informed conceptual foundation for designing AI-supported learning systems capable of developing communication, qualitative inquiry, collaboration, and other human-centered competencies required in Industry 5.0. The review contributes to Strategic Human Resource Management by demonstrating how transferable pedagogical frameworks can support workforce capability development and organizational innovation.
References
Actis-Grosso, R., Bossi, F., & Ricciardelli, P. (2021). Implicit Measures as a Useful Tool for Evaluating User Experience. Advancing Educational and Clinical AI Through Intelligent Chatbot Interaction, 339-347.
Aleedy, M. A., Atwell, E. S., & Meshoul, S. (2025). A Multi-Agent Chatbot Architecture for AI-Driven Language Learning. Advancing Educational and Clinical AI Through Intelligent Chatbot Interaction, 1-20.
Almetnawy, H., Orabi, A., Alneyadi, A. R., Ahmed, T., & Lakas, A. (2025). An Adaptive Intelligent Tutoring System Powered by Generative AI. Proceedings of the 2025 IEEE Global Engineering Education Conference (EDUCON), 1-8.
Bassner, P., & Lottner, A. (2025). Towards Understanding the Impact of Context-Aware AI Tutors and General-Purpose AI Chatbots on Student Learning. Advancing Educational and Clinical AI Through Intelligent Chatbot Interaction, 1-12.
Benamara, A., Martin, J.-C., Prigent, E., & Ravenet, B. (2023). Evaluating a Model of Pathological Affect based on Pedagogical Situations for a Virtual Patient. Proceedings of the 23rd ACM International Conference on Intelligent Virtual Agents (IVA '23), 1-8.
Bolu, C., et al. (2024). Collaborative Pathways Enhancing Engineering Education through Industry-Academia Partnerships in Africa. IEEE Transactions on Education, 1-10.
Borg, A., Parodis, I., & Skantze, G. (2024). Creating Virtual Patients using Robots and Large Language Models: A Preliminary Study with Medical Students. Advancing Educational and Clinical AI Through Intelligent Chatbot Interaction, 1-15.
Bueno, et al. (2024). Industry 4.0 Skills in Industrial Engineering Courses Contributing to the Role of Universities Toward Sustainability. IEEE Transactions on Engineering Management, vol. 71, pp. 353-358.
Cai, Z., & Nixon, N. (2024). Advancing Knowledge Together: Integrating Large Language Model-based Conversational AI in Small Group Learning. Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems, 1-14.
Chinnakannu Murthy, R., & Machel, M. (2022). Systematic Literature Review of Students’ Perception of Employability Skills. Modern Engineering Education: Skills, Industry Alignment, and Pedagogical Innovation, 1-15.
Choi, M. G., & Oh, S.-Y. (2026). Developing L2 turn-taking with ChatGPT: A longitudinal conversation analytic study. System, vol. 138, 103959.
Chuang, Y.-T., & Wang, S.-H. (2025). A ChatGPT-based dynamic assessment chatbot. Journal of Computer Languages, vol. 85, 101366.
Colim, A., et al. (2022). Occupational Safety & Ergonomics Training of Future Industrial Engineers: A Project-Based Learning Approach. Procedia Computer Science, vol. 200, pp. 1-10.
Craps, S., et al. (2021). Exploring Professional Roles for Early Career Engineers: A Systematic Literature Review. European Journal of Engineering Education, vol. 46, no. 2, pp. 1-15.
Doss, T. P., & Buck, L. (2024). Education for Industry 5.0 and ESD: Co-Creation of Engineering Design Challenges with Industry. Proceedings of the 2024 IEEE Global Engineering Education Conference (EDUCON), 1-9.
Eckerström, J., et al. (2025). Virtual patient simulation in an interactive educational module on intimate partner violence nursing. Frontiers in Digital Health, 1-12.
El Shazly, R. (2021). Effects of Artificial Intelligence on English Speaking Anxiety and Speaking Performance: A Case Study. Expert Systems, vol. 38, no. 1, pp. 129-142.
Firescu, V. (2025). Increasing Collaboration Between Humans and Technology Within Organizations: The Need for Ergonomics and Soft Skills in Engineering Education 5.0. Sustainability, vol. 17, no. 5, p. 1989.
Galster, M., et al. (2024). Video-based Training for Meeting Communication Skills. Proceedings of the 2024 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE), 1-7.
Gomathi, R. D., et al. (2024). Importance Of Developing Social Skills In Engineering Students Using Artificial Intelligence. Proceedings of the 15th International Conference on Computing Communication and Networking Technologies (ICCCNT), 1-7.
Graf, et al. (2024). Towards believable and educational conversations with virtual patients. Frontiers in Virtual Reality, 1-15.
Holderried, F., et al. (2024). A Language Model–Powered Simulated Patient With Automated Feedback for History Taking: Prospective Study. JMIR Medical Education, vol. 10, no. 1, e59213.
Hsieh, L.-H., Liu, E.-Y., Lin, C.-M., & Liu, C.-J. (2025). Developing Chatbots as Virtual Clients for Empathy Training in Counselor Education: Examining Feasibility from Users' Perspectives. Bulletin of Educational Psychology, vol. 56, no. 3, pp. 539-570.
Intan Ghayatrie, et al. (2025). Analyzing STEM Women’s Employability: A Machine Learning Framework with Clustering and Multi-Targeting. Modern Engineering Education: Skills, Industry Alignment, and Pedagogical Innovation, 1-12.
Ipatov, et al. (2024). Implementation of an AI-Powered Language Assistant for Enhancing Engineering Students' Communicative Proficiency. 35th DAAAM International Symposium on Intelligent Manufacturing and Automation, 119-125.
Jaberiansari, M., et al. (2024). Engineering Non-technical Skills Behavioral Taxonomy: A Sort and Grid Workshop. Modern Engineering Education: Skills, Industry Alignment, and Pedagogical Innovation, 1-14.
Jeon, J. (2023). Chatbot-assisted dynamic assessment (CA-DA) for L2 vocabulary learning and diagnosis. Computer Assisted Language Learning, vol. 36, no. 8, pp. 1339-1364.
Kamble, S., & Pandey, A. (2022). Perception Gap Analysis of Employability Amongst Academia, Information Technology Industry, and Fresh Graduates. Modern Engineering Education: Skills, Industry Alignment, and Pedagogical Innovation, 1-15.
Laverde, et al. (2025). Integrating Large Language Model-Based Agents into a Virtual Patient Chatbot for Clinical Anamnesis. Advancing Educational and Clinical AI Through Intelligent Chatbot Interaction, vol. 27, pp. 2481-2491.
Lee, K.-A., & Lim, S.-B. (2023). Designing a Leveled Conversational Teachable Agent for English Language Learners. Applied Sciences, vol. 13, no. 11, p. 6541.
Leontjev, D., et al. (2025). Reading with a Chatbot: The Added Value of Generative AI as a Resource in Mediating Learners in Dynamic Assessment. Advancing Educational and Clinical AI Through Intelligent Chatbot Interaction, 143-155.
Luk, et al. (2024). Are Technical Knowledge Sacrificed with the Integration of Transferable Skills into the Engineering Curriculum? International Journal of Educational Research, vol. 102, p. 101586.
Luo, et al. (2025). A Large Language Model Digital Patient System Enhances Ophthalmology History Taking Skills. Advancing Educational and Clinical AI Through Intelligent Chatbot Interaction, 1-15.
Maia, M., et al. (2023). Managing Soft Skills Development in Technological Innovation Project Teams: An Experience Report in the Automotive Industry. Proceedings of the 2023 IEEE Frontiers in Education Conference (FIE), 1-8.
Malekshahian, et al. (2025). Bridging the Skills Gap: Enhancing Employability for Chemical Engineering Graduates. Modern Engineering Education: Skills, Industry Alignment, and Pedagogical Innovation, 23-29.
Mitrovic, A., Galster, M., et al. (2025). Video-Based Empathy Training for Software Engineers. Advancing Educational and Clinical AI Through Intelligent Chatbot Interaction, 1-12.
Ochs, M., et al. (2022). Multimodal Behavioral Cues Analysis of the Sense of Presence and Social Presence During a Social Interaction with a Virtual Patient. Advancing Educational and Clinical AI Through Intelligent Chatbot Interaction, 1-15.
Øien, Netland, et al. (2022). How does the extent of student-active learning in engineering programmes influence students’ perceived learning outcomes? Proceedings of the 50th Annual Conference of the European Society for Engineering Education (SEFI), pp. 580-585.
Professor, Department of MCA, B H Gardi College of Engineering and Technology, India, et al. (2021). A Framework to Create Employability Skills for Small and Medium Scale Industry. Modern Engineering Education: Skills, Industry Alignment, and Pedagogical Innovation, 1-14.
Rahman, K. A. A., et al. (2025). Optimizing ESL Learners’ Speech Act Performance: The Role of AI-Powered Chatbots in Pragmatic Competence. Advancing Educational and Clinical AI Through Intelligent Chatbot Interaction, 45-60.
Rigou, M., Gkamas, V., Perikos, I., Kovas, K., & Kontodiakou, P. (2025). Utilizing Virtual Worlds for Training Professionals: The Case of Soft Skills Training of Smart City Engineers and Technicians. Computers, vol. 14, no. 6, p. 206.
Shah, M., Wang, Y., et al. (2024). Clinical judgment, person-centered care and professionalism: A transmodal ordered network analysis of nursing virtual patient simulations. Advancing Educational and Clinical AI Through Intelligent Chatbot Interaction, 365-380.
Sjawie, F., & Ardi, R. (2021). The Impact of Employability Skills on Employers' Satisfaction: A Conceptual Model for Fresh Graduates of Engineering. In 4th Asia Pacific Conference on Research in Industrial and Systems Engineering 2021 (APCORISE 2021), 1-7.
Son, T., et al. (2024). Exploring Elementary Preservice Teachers’ Responsive Teaching in Mathematics Through an Artificial Intelligence-Based Chatbot. Advancing Educational and Clinical AI Through Intelligent Chatbot Interaction, 1-20.
Stiff, A., White, M., Fosler-Lussier, E., Jin, L., Jaffe, E., & Danforth, D. (2024). A randomized prospective study of a hybrid rule- and data-driven virtual patient. Natural Language Engineering, vol. 30, pp. 31-72.
Talbot, T., et al. (2021). Perceptive Patient: Important Factors for Practical Emotion Sensing in Conversational Human-Computer Interaction. Advances in Intelligent Systems and Computing, vol. 264, pp. 3-10.
Tusher, et al. (2022). Learning from Accidents: Nontechnical Skills Deficiency in the European Process Industry. Chemical Engineering Department, Universiti Teknologi PETRONAS, 1-12.
Wang, T., Long, T., Mei, A., Li, J., & Liu, Z. (2026). Fusing Six-Hat thinking with AI: How the Green Hat and ChatGPT Co-Regulate pre-service teachers' instructional design—insights from epistemic network analysis. Thinking Skills and Creativity, vol. 59, 102025.
