Enhancing students’ knowledge construction and affective-domain learning objectives through computational thinking integrated into project-based learning in online learning environments

Abstract

Conventional teaching methods often emphasize teacher-centered activities, limiting opportunities for students to develop professional and transferable skills. This disconnection between academic knowledge and workplace readiness highlights the need for innovative approaches to education. This study explores the integration of computational thinking (CT) into project-based learning (PjBL) as a means of enhancing student learning outcomes, particularly in online learning environments. A quasi-experimental design was adopted to evaluate the effectiveness of this strategy. The study involved two groups of university students: an experimental group (24 students) exposed to CT-integrated PjBL and a control group (23 students) taught using conventional PjBL method. Results demonstrated that CT-integrated PjBL significantly enhanced students’ knowledge construction and affective-domain learning objectives, including motivation, attitude, and self-efficacy, compared to the conventional approach. These findings underscore the potential of combining CT with PjBL to bridge the gap between theoretical knowledge and practical application. The study offers valuable insights and practical implications for educators, researchers, and course designers, advocating for the adoption of innovative teaching strategies that foster holistic skill development and better prepare students for professional challenges.