Leveraging Generative AI for Sustainable Academic Advising: Enhancing Educational Practices through AI-Driven Recommendations

被引:0
|
作者
Iatrellis, Omiros [1 ]
Samaras, Nicholas [1 ]
Kokkinos, Konstantinos [1 ]
Panagiotakopoulos, Theodor [2 ,3 ]
机构
[1] Univ Thessaly, Dept Digital Syst, Larisa 41500, Greece
[2] Hellen Open Univ, Sch Sci & Technol, Patras 26335, Greece
[3] Univ Nicosia, Business Sch, CY-2417 Nicosia, Cyprus
关键词
academic advising; generative AI; educational technology; sustainable educational practices;
D O I
10.3390/su16177829
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study explores the integration of ChatGPT, a generative AI tool, into academic advising systems, aiming to assess its efficacy compared to traditional human-generated advisories. Conducted within the INVEST European University, which emphasizes sustainable and innovative educational practices, this research leverages AI to demonstrate its potential in enhancing sustainability within the context of academic advising. By providing ChatGPT with scenarios from academic advising, we evaluated the AI-generated recommendations against traditional advisories across multiple dimensions, including acceptance, clarity, practicality, impact, and relevance, in real academic settings. Five academic advisors reviewed recommendations across diverse advising scenarios such as pursuing certifications, selecting bachelor dissertation topics, enrolling in micro-credential programs, and securing internships. AI-generated recommendations provided unique insights and were considered highly relevant and understandable, although they received moderate scores in acceptance and practicality. This study demonstrates that while AI does not replace human judgment, it can reduce administrative burdens, significantly enhance the decision-making process in academic advising, and provide a foundation for a new framework that improves the efficacy and sustainability of academic advising practices.
引用
收藏
页数:16
相关论文
共 50 条
  • [2] Bilingual AI-Driven Chatbot for Academic Advising
    Bilquise, Ghazala
    Ibrahim, Samar
    Shaalan, Khaled
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2022, 13 (08) : 50 - 57
  • [3] Towards Enhancing the Media Industry Through AI-Driven Image Recommendations
    Raptis, George E.
    Theodorou, Vasilis
    Katsini, Christina
    HUMAN-COMPUTER INTERACTION - INTERACT 2023, PT IV, 2023, 14145 : 574 - 579
  • [4] AI-driven adaptive learning for sustainable educational transformation
    Strielkowski, Wadim
    Grebennikova, Veronika
    Lisovskiy, Alexander
    Rakhimova, Guzalbegim
    Vasileva, Tatiana
    SUSTAINABLE DEVELOPMENT, 2024,
  • [5] Greening Automation: Policy Recommendations for Sustainable Development in AI-Driven Industries
    Doran, Nicoleta Mihaela
    Badareu, Gabriela
    Doran, Marius Dalian
    Enescu, Maria
    Staicu, Anamaria Liliana
    Niculescu, Mariana
    SUSTAINABILITY, 2024, 16 (12)
  • [6] AI-driven mock interview assessment: leveraging generative language models for automated evaluation
    Uppalapati, Padma Jyothi
    Dabbiru, Madhavi
    Kasukurthi, Venkata Rao
    INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, 2025,
  • [7] Enhancing Higher-Education Governance Through Telepresence Robots and Gamification: Strategies for Sustainable Practices in the AI-Driven Digital Era
    Addas, Abdullah
    Naseer, Fawad
    Tahir, Muhammad
    Khan, Muhammad Nasir
    EDUCATION SCIENCES, 2024, 14 (12):
  • [8] Enhancing Student Scholarly Writing Through AI-Driven Teaching Strategies
    Fritz, Ashlie
    Toothaker, Rebecca
    NURSE EDUCATOR, 2025,
  • [9] Generative AI-Driven Digital Twin for Mobile Networks
    Chai, Haoye
    Wang, Huandong
    Li, Tong
    Wang, Zhaocheng
    IEEE NETWORK, 2024, 38 (05): : 84 - 92
  • [10] A generative AI-driven interactive listening assessment task
    Runge, Andrew
    Attali, Yigal
    Laflair, Geoffrey T.
    Park, Yena
    Church, Jacqueline
    FRONTIERS IN ARTIFICIAL INTELLIGENCE, 2024, 7