Neuro-Educational Data Mining: Bridging Brain-Computer Interfaces and Predictive Learning Analytics for Personalized Instruction
Abstract
Background. Rapid transformations in labor markets driven by digitalization and platform-based employment have reshaped traditional career trajectories, particularly among Generation Z. Emerging gig economy structures require adaptive competencies that extend beyond conventional career preparation, yet many career development models remain oriented toward stable, long-term employment pathways.
Purpose. This study aimed to examine the role of career counseling in enhancing Generation Z’s readiness for gig economy participation. Specifically, it investigated the extent to which career adaptability, digital career competence, entrepreneurial readiness, and career self-efficacy contribute to preparedness for non-traditional and platform-based employment.
Method. A mixed-methods sequential explanatory design was employed. Quantitative data were collected from 450 participants using validated instruments measuring career adaptability, digital career competence, entrepreneurial readiness, career self-efficacy, and gig economy career readiness. Structural Equation Modeling (SEM) was applied to test the relationships among variables. Qualitative interviews were conducted to deepen understanding of participants’ perceptions of career counseling experiences and alternative career pathways.
Results. The findings indicate that career counseling has a significant positive effect on all examined variables. Career adaptability emerged as the strongest predictor of gig economy readiness, followed by digital career competence and entrepreneurial readiness. Career self-efficacy also contributed significantly to readiness outcomes. The qualitative data supported these findings by showing that students who experienced structured career guidance demonstrated greater confidence in navigating uncertain and project-based labor markets. However, some participants still exhibited limited awareness of gig economy risks and unstable income structures, indicating uneven preparedness.
Conclusion. The study highlights that career counseling plays a critical role in preparing Generation Z for evolving labor market demands. Strengthening adaptive, digital, and entrepreneurial dimensions within counseling frameworks is essential for improving readiness for gig and platform-based employment. These findings suggest that traditional career guidance models require substantial redesign to align with the realities of contemporary work ecosystems.
Full text article
References
Adamakis, M. (2025). Artificial Intelligence in Higher Education: A State-of-the-Art Overview of Pedagogical Integrity, Artificial Intelligence Literacy, and Policy Integration. Encyclopedia, 5(4). https://doi.org/10.3390/encyclopedia5040180
Almheiri, A. S. B. (2025). AI-based tutoring systems in education: A systematic literature review on personalized learning, intelligent agents, and learning analytics. Generators Bots and Tutors Creative Approaches to Human AI Synergy in Classroom Instruction, (Query date: 2026-06-19 03:17:58), 185–210. https://doi.org/10.4018/979-8-3373-0847-0.ch007
Almuqhim, S. (2025). AI-Driven Personalized Microlearning Framework for Enhanced E-Learning. Computer Applications in Engineering Education, 33(3). https://doi.org/10.1002/cae.70040
Anbumaheshwari, K. (2025). AI-Driven Curriculum Innovation for Adaptive and Learner-Centric Education. Advancing Society 5 0 Through AI Driven Curriculum Innovation, (Query date: 2026-06-19 03:17:58), 99–132. https://doi.org/10.4018/979-8-3373-1062-6.ch004
Ariana, S. (2025). AI-Powered Adaptive E-Learning to Improve Accessibility for Diverse Learner Demographics. Proceeding 2025 4th International Conference on Creative Communication and Innovative Technology Empowering Transformative Mature Leadership Harnessing Technological Advancement for Global Sustainability Iccit 2025, (Query date: 2026-06-19 03:17:58). https://doi.org/10.1109/ICCIT65724.2025.11167531
Asrifan, A. (2025). AI for Bilingual Mastery: Personalized Learning and Intelligence Tutoring in Language Education. AI Powered Solutions for Bilingual Proficiency and Communication, (Query date: 2026-06-19 03:17:58), 177–205. https://doi.org/10.4018/979-8-3373-0275-1.ch006
Boutabia, I. (2025). A Survey on AI Applications in the Open Classroom Approach. Icnas 2025 7th International Conference on Networking and Advanced Systems, (Query date: 2026-06-19 03:17:58). https://doi.org/10.1109/ICNAS68168.2025.11298090
Cao, C. (2023). A New Cloud with IoT-Enabled Innovation and Skill Requirement of College English Teachers on Blended Teaching Model. International Journal on Recent and Innovation Trends in Computing and Communication, 11(6), 127–137. https://doi.org/10.17762/ijritcc.v11i6s.6816
Deng, X. (2026). AI-driven emotional intelligence in piano education: Deep learning models for expressive performance coaching. Acta Psychologica, 263(Query date: 2026-06-19 03:17:58). https://doi.org/10.1016/j.actpsy.2026.106264
Hadyaoui, A. (2026). AI-driven adaptive stealth assessment for socially regulated learning in collaborative environments. Journal of Research on Technology in Education, 58(1), 130–150. https://doi.org/10.1080/15391523.2025.2586501
Jalaluddin, M. M. (2025). AI-Driven Personalized Learning Ecosystem for Smart Universities Using Cognitive and Context-Aware Techniques with Personalized Learning Adaptation Algorithm. Proceedings of the International Conference on Electrical Engineering and Informatics, (Query date: 2026-06-19 03:17:58). https://doi.org/10.1109/ICEEI68459.2025.11330781
Joseph, B. (2022). Analyzing the Cognitive Process Dimension and Rate of Learning to Identify the Slow Learners in e-Learning. 2022 International Conference on Innovative Trends in Information Technology Icitiit 2022, (Query date: 2026-06-19 03:17:58). https://doi.org/10.1109/ICITIIT54346.2022.9744144
Kaswan, K. S. (2024). AI in personalized learning. Advances in Technological Innovations in Higher Education Theory and Practices, (Query date: 2026-06-19 03:17:58), 103–117. https://doi.org/10.1201/9781003376699-9
Khor, E. T. (2024). A Systematic Review of the Role of Learning Analytics in Supporting Personalized Learning. Education Sciences, 14(1). https://doi.org/10.3390/educsci14010051
Koukaras, C. (2025). AI-Driven Telecommunications for Smart Classrooms: Transforming Education Through Personalized Learning and Secure Networks. Telecom, 6(2). https://doi.org/10.3390/telecom6020021
Kucharski, S. (2023). An Adaptive, Structure-Aware Intelligent Tutoring System for Learning Management Systems. Proceedings 2023 IEEE International Conference on Advanced Learning Technologies Icalt 2023, (Query date: 2026-06-19 03:17:58), 367–369. https://doi.org/10.1109/ICALT58122.2023.00113
Lee, C. A. (2023). AI-Based Diagnostic Assessment System: Integrated With Knowledge Map in MOOCs. IEEE Transactions on Learning Technologies, 16(5), 873–886. https://doi.org/10.1109/TLT.2023.3308338
Li, H. (2025). An Intelligent Educational System: Analyzing Student Behavior and Academic Performance Using Multi-Source Data. Electronics Switzerland, 14(16). https://doi.org/10.3390/electronics14163328
Ling, Y. (2026). AI-Enabled Learning Analytics and Intelligent Interaction System for Chinese College English Flipped Classrooms: Model Reconstruction and Effectiveness Evaluation. Proceedings of 2026 5th International Conference on Big Data Information and Computer Network Bdicn 2026, (Query date: 2026-06-19 03:17:58), 103–109. https://doi.org/10.1145/3801228.3801244
López-Pernas, S. (2025). AI, Explainable AI and Evaluative AI: Informed Data-Driven Decision-Making in Education. Advanced Learning Analytics Methods AI Precision and Complexity, (Query date: 2026-06-19 03:17:58), 17–39. https://doi.org/10.1007/978-3-031-95365-1_2
Manz, J. (2025). Automated Tracking of User Interactions in Web-Based Adaptive Learning for Software Engineering. Proceedings of the 6th Ecsee 2025 European Conference on Software Engineering Education, (Query date: 2026-06-19 03:17:58), 180–184. https://doi.org/10.1145/3723010.3723020
Marouf, M. A. A. (2024). AI in real-time student performance monitoring using IoE. Role of Internet of Everything Ioe VLSI Architecture and AI in Real Time Systems, (Query date: 2026-06-19 03:17:58), 275–287. https://doi.org/10.4018/979-8-3693-7367-5.ch019
Mon, B. F. (2023). A Study on Role of Artificial Intelligence in Education. Proceedings 2023 International Conference on Computing Electronics and Communications Engineering Iccece 2023, (Query date: 2026-06-19 03:17:58), 133–138. https://doi.org/10.1109/iCCECE59400.2023.10238613
Ojha, B. (2025). Artificial Intelligence Integration in Higher Education. Adopting Artificial Intelligence Tools in Higher Education Teaching and Learning, (Query date: 2026-06-19 03:17:58), 1–23. https://doi.org/10.1201/9781003469315-1
Park, E. (2023). Adaptive or adapted to: Sequence and reflexive thematic analysis to understand learners’ self-regulated learning in an adaptive learning analytics dashboard. British Journal of Educational Technology, 54(1), 98–125. https://doi.org/10.1111/bjet.13287
Patil, S. (2025). A Comprehensive Review of Current Practices in AI-Assisted Learning. Proceedings of 6th International Conference on Iot Based Control Networks and Intelligent Systems Icicnis 2025, (Query date: 2026-06-19 03:17:58), 1951–1957. https://doi.org/10.1109/ICICNIS66685.2025.11315702
Pillai, S. (2024). AI in Education: Balancing Innovation and Responsibility. Proceedings of the 4th International Conference on AI Research Icair 2024, (Query date: 2026-06-19 03:17:58), 345–354.
Piñera-Castro, H. J. (2025). Applications of artificial intelligence in neurosurgical education: A scoping review. Egyptian Journal of Neurology Psychiatry and Neurosurgery, 61(1). https://doi.org/10.1186/s41983-025-01015-x
Ranjan, R. (2025). AI-powered data platforms bridging the gap between analytics and action in smart education. Smart Education and Sustainable Learning Environments in Smart Cities, (Query date: 2026-06-19 03:17:58), 107–122. https://doi.org/10.4018/979-8-3693-7723-9.ch007
Rodrigues, B. (2025). A Systematic Literature Review of AI-Driven Intelligent Tutoring Systems in Engineering Education: Emphasizing Personalization, Feedback, and Student Monitoring. IEEE Access, 13(Query date: 2026-06-19 03:17:58), 190152–190177. https://doi.org/10.1109/ACCESS.2025.3626473
Romero, M. (2024). Affordances for AI-Enhanced Digital Game-Based Learning. Palgrave Studies in Creativity and Culture, (Query date: 2026-06-19 03:17:58), 117–128. https://doi.org/10.1007/978-3-031-55272-4_9
Ruzimboev, K. (2025). A Neuro-Symbolic, Multi-Modal Architecture for Advancing Adaptive Intelligent Tutoring Systems. Proceedings of the 17th International Scientific and Technical Conference Actual Problems of Electronic Instrument Engineering Apeie 2025, (Query date: 2026-06-19 03:17:58). https://doi.org/10.1109/APEIE66761.2025.11289439
Saeed, M. M. A. (2024). AI technologies in engineering education. AI Enhanced Teaching Methods, (Query date: 2026-06-19 03:17:58), 61–87. https://doi.org/10.4018/979-8-3693-2728-9.ch003
Sakri, L. I. (2025). AI-Enabled Transformation of Online Learning through Personalization. Journal of Engineering Education Transformations, 39(Query date: 2026-06-19 03:17:58), 26–33. https://doi.org/10.16920/jeet/2025/v39is1/25131
Sameephet, B. (2025). A Comparative Analysis of Machine Learning Models for Predicting EFL Student Language Performance in Smart Learning Environments. Emerging Science Journal, 9(2), 615–639. https://doi.org/10.28991/ESJ-2025-09-02-07
Sheshadri, T. (2025). Analysing the Intersection of Education and Data Science: Enhancing Learning Outcomes through Information Systems-An Analytical Study. Indian Journal of Information Sources and Services, 15(1), 12–19. https://doi.org/10.51983/ijiss-2025.IJISS.15.1.03
Shoaib, M. (2024). AI student success predictor: Enhancing personalized learning in campus management systems. Computers in Human Behavior, 158(Query date: 2026-06-19 03:17:58). https://doi.org/10.1016/j.chb.2024.108301
Staufer, S. (2025). A Tool Landscape for Adaptive Learning. Proceedings of the 6th Ecsee 2025 European Conference on Software Engineering Education, (Query date: 2026-06-19 03:17:58), 30–39. https://doi.org/10.1145/3723010.3723028
Suhag, N. (2025). Blended Learning in the Age of Artificial Intelligence: Transforming Education Through Innovation. Reshaping Blended Learning Environments with AI, (Query date: 2026-06-19 03:17:58), 29–52. https://doi.org/10.4018/979-8-3373-3815-6.ch002
Tran, M. T. (2024). A systematic literature review on the human-AI partnership roles in higher education. Enhancing and Predicting Digital Consumer Behavior with AI, (Query date: 2026-06-19 03:17:58), 28–38. https://doi.org/10.4018/979-8-3693-4453-8.ch003
Trivedi, N. B. (2023). AI in Education-A Transformative Force. 2023 1st Dmiher International Conference on Artificial Intelligence in Education and Industry 4 0 Idicaiei 2023, (Query date: 2026-06-19 03:17:58). https://doi.org/10.1109/IDICAIEI58380.2023.10406541
Upadhyay, P. (2025). Artificial Intelligence Tools for Instructors and Learners to Optimize the Teaching and Learning Processes. AI Based Solutions for Inclusive Quality Education, (Query date: 2026-06-19 03:17:58), 45–56. https://doi.org/10.1201/9781003560814-4
Xu, W. (2023). Artificial intelligence in constructing personalized and accurate feedback systems for students. International Journal of Modeling Simulation and Scientific Computing, 14(1). https://doi.org/10.1142/S1793962323410015
Yamijala, S. M. S. (2024). AI-powered learning revolutionizing smart education with personalized learning styles. Internet of Behavior Based Computational Intelligence for Smart Education Systems, (Query date: 2026-06-19 03:17:58), 191–211. https://doi.org/10.4018/979-8-3693-8151-9.ch007
Yang, M. (2023). AI-Powered Personalized Learning Journeys: Revolutionizing Information Management for College Students in Online Platforms. Journal of Information Systems Engineering and Management, 8(1). https://doi.org/10.55267/IADT.07.14079
Zhang, H. (2025). AI-driven innovation and entrepreneurship education: A K-means clustering approach for Chinese university students. Discover Artificial Intelligence, 5(1). https://doi.org/10.1007/s44163-025-00341-6
Zhang, J. (2024). Application of Artificial Intelligence Tools in Educational Assessment: Enhancing Teaching and Learning Management in Beijing Junior High Schools. Eurasian Journal of Educational Research, 2024(112), 301–320. https://doi.org/10.14689/ejer.2024.112.017
Zhong, Y. (2025). Affordances, constraints, and implications of ChatGPT in education from a social-ecological perspective: A data mining approach. Education and Information Technologies, 30(12), 16407–16440. https://doi.org/10.1007/s10639-024-13237-2
Authors
Copyright (c) 2026 Catur Lestari Wijayanti

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.