TY - GEN
T1 - Data Analytic Framework on Student Participation in Generic Competence Development Activities
AU - So, Joseph C.H.
AU - Chan, Ada P.L.
AU - Wong, Simon C.W.
AU - Wong, Adam K.L.
AU - Chan, Henry C.B.
AU - Tsang, Kia H.Y.
N1 - Funding Information:
This study was supported by the Faculty Development Scheme (No. UGC/FDS24/E09/20) of the University Grant Committee of Hong Kong.
Publisher Copyright:
© 2021 IEEE.
PY - 2021/12
Y1 - 2021/12
N2 - Generic competence is an important element in the development of students in tertiary education. Many scholars have emphasised the strong correlation between generic competence and engagement in co-curricular and extra-curricular activities. However, in the context of higher education, research into the frameworks of learning support platforms providing evidence-based support for students' whole-person development is very limited. This study aims to investigate the potential of applying data analytics to learning support platforms with the purpose of developing students' generic competence in higher education. Recognising the potential of the latest advances in data analytics technology, the 'Student Activities Intelligent Learning Support' (SAILS) platform is proposed. To investigate its applicability and user acceptance, a prototype will be implemented and tested in a self-financing institution in Hong Kong. The users, including students and academic professionals, will be given suggestions regarding a student's involvement in various student activities with consideration of the past learning experiences, the personal developmental needs and the stated learning outcomes of the institution. The framework will benefit students as well as academics and institutions. Students, especially freshmen, can further enhance their generic competence by selecting suitable activities.
AB - Generic competence is an important element in the development of students in tertiary education. Many scholars have emphasised the strong correlation between generic competence and engagement in co-curricular and extra-curricular activities. However, in the context of higher education, research into the frameworks of learning support platforms providing evidence-based support for students' whole-person development is very limited. This study aims to investigate the potential of applying data analytics to learning support platforms with the purpose of developing students' generic competence in higher education. Recognising the potential of the latest advances in data analytics technology, the 'Student Activities Intelligent Learning Support' (SAILS) platform is proposed. To investigate its applicability and user acceptance, a prototype will be implemented and tested in a self-financing institution in Hong Kong. The users, including students and academic professionals, will be given suggestions regarding a student's involvement in various student activities with consideration of the past learning experiences, the personal developmental needs and the stated learning outcomes of the institution. The framework will benefit students as well as academics and institutions. Students, especially freshmen, can further enhance their generic competence by selecting suitable activities.
KW - AI assisted personal development
KW - data analytics
KW - generic competences
KW - Learning management system
KW - machine learning
UR - http://www.scopus.com/inward/record.url?scp=85125902544&partnerID=8YFLogxK
U2 - 10.1109/TALE52509.2021.9678754
DO - 10.1109/TALE52509.2021.9678754
M3 - Conference article published in proceeding or book
AN - SCOPUS:85125902544
T3 - TALE 2021 - IEEE International Conference on Engineering, Technology and Education, Proceedings
SP - 1079
EP - 1084
BT - TALE 2021 - IEEE International Conference on Engineering, Technology and Education, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Conference on Engineering, Technology and Education, TALE 2021
Y2 - 5 December 2021 through 8 December 2021
ER -