Evaluation of Using Educational Technologies in Service-Learning Programs at Hong Kong Universities

This project investigates the integration of advanced technologies—such as artificial intelligence, big data analytics, and digital learning platforms—into Service-Learning (SL) programs across universities in Hong Kong. These technologies aim to enhance teaching and learning experiences by facilitating personalized learning, improving access to educational resources, and fostering collaborative environments. By leveraging these tools, educators can tailor instruction to meet diverse student needs, streamline administrative processes, and engage students through interactive and immersive experiences, ultimately preparing them for a technology-driven workforce.

A survey involving 687 students assessed three key areas: knowledge of advanced technologies, attitudes toward their adoption in SL (using the Technology Acceptance Model, TAM), and the effects of technology adoption on learning outcomes (measured by the SELEB Scale). The survey predominantly included participants from The Chinese University of Hong Kong, comprising 620 respondents (90.2% of the total), while smaller representations included Hong Kong Baptist University with 44 participants (6.4%), Lingnan University with 21 participants (3.1%), and The Hong Kong Polytechnic University with 2 participants (0.3%).

Data analysis revealed that students' attitudes toward adopting new or advanced technologies in SL generally fell within a moderately positive range of 3.50 to 5.50, indicating overall favourable perceptions. The highest mean score of 5.50 reflected very positive attitudes, while the lowest score of 3.75 indicated relatively less favourable perceptions in certain contexts. This variation suggests that perceptions and experiences can differ significantly based on specific circumstances, emphasizing the need for tailored approaches in technology integration in SL programs.