Data analytic framework on student participation in generic competence development activities

Abstract

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.