The Effects Of Segmenting And Computational Thinking In Digital Video Courseware On Knowledge Achievement, Self-Efficacy And Motivation Among Students With Different Thinking Styles - Ali, Wan Nor Ashiqin Wan (2023)
The lack of 21st-century skills of digital video knowledge and computational thinking (CT), as well as the inflexibility of a student to control the learning pace results in low-quality video being produced. Hence, the researcher aims to design, develop, and analyse the effects of integration between learner-paced predefined segment and CT algorithmic thinking in "Digital Video Courseware (DVC)" development on knowledge achievement, self-efficacy, and motivation in students with different thinking styles. This research used a quasi-experimental design using a 2 x 3 factorial. This study's variables include (i) two treatment modes, "DVC: Learner-paced predefined segment (DVC-LS)" and "DVC: System predefined segment (DVC-SS)"; (ii) knowledge achievement, self-efficacy, and motivation; and (iii) thinking style, which includes legislative, executive, and judicial. The undergraduate students from "Malaysian Technical University Network (MTUN)" university are categorised into two groups which are mode 1: DVC-LS and mode 2: DVC-SS. Descriptive and inferential statistics (ANOVA and ANCOVA) were used to analyse the experimental data. The researcher found significant main and interaction effects of the learner-paced predefined segment on all dependent variables. This research broadens students' understanding of both the multidisciplinary realms of CT and digital video production and enhances their digital video knowledge, and self-efficacy.