Technology-Enhanced Learning: An Optimal CPS Learning Application

Abstract

Collaborative problem-solving (CPS) is highly valued in the sustainability of learning to foster the key soft power of talent for the future. In this study, a CPS learning application was built to train and assess individuals with the aim of increasing CPS skills. For effective learning to take place, several issues need to be carefully considered, and these were investigated while testing the proposed application. This study examined the impact of collaborative interactions (CIs) (human–computer agent (HCA) and human–human (HH) interactions) on the CPS performance of students. Gender and learning styles, which may have interaction effects with CIs on CPS performance, were also explored. The results show that the students’ CPS performance in HCA was significantly greater than that in HH. The interaction effect between gender and CI was not significant. The impact of learning style on CPS performance in HH was not significant. In contrast, in HCA, students with verbal, global, and reflective learning styles performed significantly better on CPS tasks than did students with visual, sequential, and active learning styles. Finally, we discussed the optimal ways to teach CPS and the practical effects of a CPS learning application.