Practical Use of AI-Based Learning Recommendations in Higher Education

被引:0
|
作者
Dahal, Prabin [1 ]
Nugroho, Saptadi [1 ]
Schmidt, Claudia [1 ]
Saenger, Volker [1 ]
机构
[1] Offenburg Univ Appl Sci, Badstr 24, D-77652 Offenburg, Germany
关键词
Recommender component; learning experience platform; recommended resources evaluation; SYSTEMS;
D O I
10.1007/978-3-031-73538-7_6
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
A Learning Experience Platform (LXP) is an extension of a Learning Management System (LMS) with the emphasis on personalized learning support and learner motivation. In this paper extensions for the well established LMS Moodle are proposed, that include, beyond others, AI supported learning recommendations and user based feedback mechanisms to transform Moodle to Moodle LXP. The architecture of this Moodle LXP provides plug-ins for three types of recommendations, i.e. content-based and two collaborative recommendations. Furthermore, a separate module was developed that is responsible for data storage and calculation of recommended learning resources. Various metadata such as description, number of clicks of learning resources, rating, and feedback of the resources are used for the calculation. The extensions have been integrated into several lectures for three semesters. The system operates effectively and the students use the plug-ins for learning. To learn more about the quality of the recommendations, a mechanism for evaluating the results of the content-based recommendation using feedback from the lecturers was developed.
引用
收藏
页码:57 / 66
页数:10
相关论文
共 50 条
  • [21] Perceived value of AI-based recommendations service: the case of voice assistants
    Akdim, K.
    Casalo, Luis V.
    SERVICE BUSINESS, 2023, 17 (01) : 81 - 112
  • [22] Perceived value of AI-based recommendations service: the case of voice assistants
    K Akdim
    Luis V. Casaló
    Service Business, 2023, 17 : 81 - 112
  • [23] History, Status, and Development of AI-Based Learning Science
    Wang C.
    Cai J.
    Gao C.
    Ye X.
    SN Computer Science, 4 (3)
  • [24] An AI-based intervention for improving undergraduate STEM learning
    Hasan, Mohammad Rashedul
    Khan, Bilal
    PLOS ONE, 2023, 18 (07):
  • [25] AI-based Framework for Deep Learning Applications in Grinding
    Kaufmann, T.
    Sahay, S.
    Niemietz, P.
    Trauth, D.
    Maass, W.
    Bergs, T.
    2020 IEEE 18TH WORLD SYMPOSIUM ON APPLIED MACHINE INTELLIGENCE AND INFORMATICS (SAMI 2020), 2020, : 195 - 200
  • [26] AI-Based Adaptive Learning: A Systematic Mapping of the Literature
    Ezzaim, Aymane
    Dahbi, Aziz
    Haidine, Abdelfatteh
    Aqqal, Abdelhak
    JOURNAL OF UNIVERSAL COMPUTER SCIENCE, 2023, 29 (10) : 1161 - 1197
  • [27] Six Practical Recommendations Enabling Ethical Use of Predictive Learning Analytics in Distance Education
    Rets, Irina
    Herodotou, Christothea
    Gillespie, Anna
    JOURNAL OF LEARNING ANALYTICS, 2023, 10 (01): : 149 - 167
  • [28] Exploring the impact of generative AI-based technologies on learning performance through self-efficacy, fairness & ethics, creativity, and trust in higher education
    Shahzad, Muhammad Farrukh
    Xu, Shuo
    Zahid, Hira
    EDUCATION AND INFORMATION TECHNOLOGIES, 2025, 30 (03) : 3691 - 3716
  • [29] Blended Learning and AI: Enhancing Teaching and Learning in Higher Education
    Wong, Katrine K.
    BLENDED LEARNING: INTELLIGENT COMPUTING IN EDUCATION, ICBL 2024, 2024, 14797 : 39 - 61
  • [30] Expectations of Higher Education Teachers Regarding the Use of AI in Education
    Perez-Alvarez, Ronald
    Chavarria Villalobos, Cindy Rebeca
    Dalorso Cruz, Melber
    Miranda Loria, Jorge
    ARTIFICIAL INTELLIGENCE IN EDUCATION: POSTERS AND LATE BREAKING RESULTS, WORKSHOPS AND TUTORIALS, INDUSTRY AND INNOVATION TRACKS, PRACTITIONERS, DOCTORAL CONSORTIUM AND BLUE SKY, AIED 2024, PT I, 2024, 2150 : 208 - 213