Published
2024-09-24
Issue
Section
Articles
How to Cite
Perceived usefulness of a machine learning-assisted recommendation system for generic competency development
Simon Wong
Division of Science, Engineering and Health Studies, College of Professional and Continuing Education, The Hong Kong Polytechnic University, Hong Kong.
https://orcid.org/0000-0003-3408-9747
Ka Lok Wong
Division of Science, Engineering and Health Studies, College of Professional and Continuing Education, The Hong Kong Polytechnic University, Hong Kong.
https://orcid.org/0000-0001-7288-0199
Yui-Yip Lau
Division of Business and Hospitality Management, College of Professional and Continuing Education, The Hong Kong Polytechnic University, Hong Kong.
https://orcid.org/0000-0002-2053-6238
Kia Tsang
Division of Science, Engineering and Health Studies, College of Professional and Continuing Education, The Hong Kong Polytechnic University, Hong Kong.
https://orcid.org/0000-0003-2513-7102
Ada Chan
Smart Location Limited, Suite 1300, 1500 West Georgia Street, Vancouver, British Columbia, V6G 2Z6, Canada.
https://orcid.org/0000-0001-5546-0838
DOI: https://doi.org/10.20448/jeelr.v11i3.5971
Keywords: Generic competency development activities, Higher education, Leisure activities, Machine learning, Task-technology fit, Technology acceptance.
Abstract
Generic competency development activities (GCDAs) help students develop critical thinking, problem-solving, innovation, creativity, communication and social skills. This study evaluated students’ acceptance of a machine learning-assisted recommendation system (MARS) developed to recommend GCDAs for students in a higher education institution. This study adopted a quantitative approach to evaluate the higher education students’ perceived usefulness of MARS based on a new appropriate model derived from three widely used models related to technology adoption and leisure activities. In August 2023, the participants of orientation for freshmen were invited to complete an online questionnaire after they tried MARS. 351 valid responses were analyzed using multiple regression. The results revealed that the students positively perceive accepting MARS as a useful tool for choosing GCDAs and indicated the students’ perceptions were affected more by their programs of study, career development and personal interests than by social influence and facilitating conditions on their selection of GCDAs. These findings based on the new model provide implications for the implementation of education technology for generic competency development.