A program visualization model to enhance student engagement in introduction to programming course

High attrition and failure rates are common phenomena in introductory programming courses. Thus, program visualization (PV) is introduced to enhance programming skills among novices. However, there is some doubt about the effectiveness of PV and its ability to engage students in using it effectively...

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Bibliographic Details
Main Author: Al-Sakkaf, Abdullah Mohammed Hussein
Format: Thesis
Language:eng
eng
eng
Published: 2022
Subjects:
Online Access:https://etd.uum.edu.my/10454/1/depositpermission-embargo%201years_s902324.pdf
https://etd.uum.edu.my/10454/2/s902324_01.pdf
https://etd.uum.edu.my/10454/3/s902324_02.pdf
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Summary:High attrition and failure rates are common phenomena in introductory programming courses. Thus, program visualization (PV) is introduced to enhance programming skills among novices. However, there is some doubt about the effectiveness of PV and its ability to engage students in using it effectively. Therefore, the PV needs to be enhanced by integrating engagement factors to improve students’ learning outcomes. Unfortunately, current PV models lack multi-dimensional student engagement aspects, including cognitive, behavioral, and emotional engagement. This study aims to develop and validate a model that explains the PV design of student engagement in learning programming. The study employed a design-based research with a mixed-method evaluation approach. The developed PV Engagement Design Model (PVEDM) consists of four components: engagement design features (EDFs), student engagement, learning outcome, and design principles. The model was evaluated through three different methods: expert reviews, usability testing, and two controlled experiments. Firstly, seven experts evaluated the consistency and relevancy of the PVEDM through an expert review method. Then, a usability test was conducted with five domain experts to verify the usefulness of the tool. Finally, the two controlled experiments in an academic setting were conducted to evaluate the effectiveness and practicality of the PVEDM. The empirical evaluation results show that the PVEDM improved learning outcomes (p= .033), engagement (p= .255), and time-on-tool (p= .011). Furthermore, it reveals that the PVEDM is able to encourage cognitive and emotional engagement among novices. Theoretically, this study contributes to the PVEDM, which includes EDFs and EDFs taxonomy to improve students’ programming skills. Furthermore, this study contributes to the categorization of the EDFs taxonomy, which consists of four categories: interactive, collaborative, cognitive, and gamification. Practically, a SocialWorked-Examples Technique (SWET) tool was developed based on PVEDM to engage novices in an active learning environment, thus cultivating their programming skills.