@article{Cuong_2026, title={Academic Advising for University Students in the Digital Environment}, volume={5}, url={http://dx.doi.org/10.22161/ijtle.5.4.7}, DOI={10.22161/ijtle.5.4.7}, abstractNote={<jats:p>Academic advising serves as the connective link between students, training programs, and the university, directly shaping learning outcomes and student engagement within credit-based training systems. Digital transformation, big data, and artificial intelligence are profoundly reshaping how this activity is delivered, shifting from traditional face-to-face advising toward e-advising systems, AI-driven chatbots, and predictive learning-analytics tools. Using a literature-review approach, this paper synthesizes domestic and international research on academic advising to clarify: (1) the nature and theoretical models of academic advising; (2) the impact of digital transformation on the role and modalities of academic advising in universities; (3) the categories of technological tools currently applied to support academic advising in the digital environment, including e-advising systems, AI chatbots, and learning analytics combined with recommender systems for predicting academic performance and advising on course selection; and (4) the data-ethics and algorithmic-fairness risks that must be managed when deploying these tools. The review finds that academic advising in the digital environment is shifting from an administrative role toward a personalised, developmental advising role, technology-enabled yet still requiring human judgment in consequential decisions; it also identifies a gap in integrating predictive-analytics tools into academic-advising workflows in Vietnam, as well as a gap in the corresponding data-governance framework. On this basis, the paper proposes directions for applying digital technology to academic advising at Vietnamese universities in line with a responsible-AI approach.</jats:p>}, number={4}, journal={International Journal of Teaching, Learning and Education}, publisher={AI Publications}, author={Cuong, Trinh Van}, year={2026}, pages={50–56} }