International Journal of
Information and Education Technology

Abstract—This research investigates the influence of technological innovation—namely Artificial Intelligence (AI), data analysis, and virtual guidance platforms—on Chinese higher education student satisfaction with educational counselling services. Utilizing a quantitative design, the data were gathered via a structured survey of 232 students who had received counselling services. Statistical analyses involving regression and mediation modeling through Statistical Package for the Social Sciences (SPSS) were carried out in order to evaluate direct and indirect relationships between the variables. The results show that AI integration, data analytics utilization, and virtual guidance platform availability individually have a strong positive impact on student satisfaction. In addition, the research establishes personalized student support as a mediating factor in these relationships, highlighting the need to customize services based on individual student needs to best capitalize on technological innovations. These findings imply that technology optimizes access and efficiency but that its real impact on satisfaction is only achieved when blended with actual personalization. The study provides useful guidance for higher education institutions seeking to reform their counselling systems and enhance student outcomes. By underscoring the complementarity of technology and personalization, this research offers a theoretical and empirical framework for the design and implementation of student-centered, technology-enhanced support services in higher education.

Keywords—artificial intelligence, data analytics, virtual guidance platforms, student satisfaction, personalized support

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Cite: Qiuhong Zhang and Nurul Fazzuan Khalid, "Technological Advancements in Educational Counselling: Exploring the Role of AI, Data Analytics, and Virtual Guidance Platforms in Student Support Systems," International Journal of Information and Education Technology, vol. 15, no. 11, pp. 2441-2454, 2025.

Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).