TY - GEN
T1 - A Social Profile-Based Recommendation Architecture for E-Learning Systems
AU - Ntlangula, Xola
AU - Leung, Wai Sze
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - The increased reliance of education institutions on e-learning systems to provide learning and teaching activities and resources has prompted a need for innovative strategies that deliver effective learning to students. One approach being considered involves enhancing personalized learning experiences through the implementation of personalized learning paths. Personalized learning paths have proven highly beneficial for students; however, they are predominantly guided by learning objectives rather than the unique attributes of each student. Additionally, the inflexibility observed in e-learning systems poses a challenge in integrating customization options. This paper proposes an architecture for a recommendation system that creates personalized learning paths from a student's profile. The resulting architecture enhances an e-learning system's personalization by using external student data to create a more comprehensive student profile, thereby improving the system’s ability to generate learning paths and deliver technology-enhanced learning experiences.
AB - The increased reliance of education institutions on e-learning systems to provide learning and teaching activities and resources has prompted a need for innovative strategies that deliver effective learning to students. One approach being considered involves enhancing personalized learning experiences through the implementation of personalized learning paths. Personalized learning paths have proven highly beneficial for students; however, they are predominantly guided by learning objectives rather than the unique attributes of each student. Additionally, the inflexibility observed in e-learning systems poses a challenge in integrating customization options. This paper proposes an architecture for a recommendation system that creates personalized learning paths from a student's profile. The resulting architecture enhances an e-learning system's personalization by using external student data to create a more comprehensive student profile, thereby improving the system’s ability to generate learning paths and deliver technology-enhanced learning experiences.
KW - Personalized learning paths
KW - Recommendation systems
KW - Social profile
UR - http://www.scopus.com/inward/record.url?scp=85197418447&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-62277-9_20
DO - 10.1007/978-3-031-62277-9_20
M3 - Conference contribution
AN - SCOPUS:85197418447
SN - 9783031622762
T3 - Lecture Notes in Networks and Systems
SP - 330
EP - 343
BT - Intelligent Computing - Proceedings of the 2024 Computing Conference
A2 - Arai, Kohei
PB - Springer Science and Business Media Deutschland GmbH
T2 - Science and Information Conference, SAI 2024
Y2 - 11 July 2024 through 12 July 2024
ER -