The effect of Toxicode and Google Blockly applications on students' computational thinking skills and self-efficacy perceptions regarding algorithm development

This study aims to investigate the impact of Toxicode and Google Blockly applications on students' computational thinking skills and algorithm development self-efficacy. The research was conducted using the Solomon four-group design, an experimental design method, to control internal and external validity threats and mitigate potential pretest effects. The study group consisted of a total of 102 students, 54 in the experimental groups using Toxicode and 48 in the control groups using Google Blockly, from the 5th grade of middle schools in Samsun, Turkey. Two branches from the participating four branches were randomly assigned to the experimental groups using Toxicode, while the other two branches were assigned to the control groups using Google Blockly, all within the same curriculum. During the experimental process, Toxicode program activities were implemented in the experimental groups, while the control groups followed various activities guided by teachers through the Google Blockly application tool as part of the Ministry of National Education's Information Technologies and Software Course Teaching Materials. Post-tests were administered to all groups, whereas pre-tests were only conducted with the experimental group 1 and control group 1. Data was collected using the "Computer Thinking Skill Levels Scale" and the "Self-Efficacy Perception Scale for Algorithm Development". At the end of the experimental process, a meta-analytic approach was employed for intergroup comparisons. The results indicate that both Toxicode and Google Blockly applications have a positive impact on both skill sets. Comparative analysis results show a significant increase in students' self-efficacy perception for algorithm development and computational thinking skills. However, this improvement was found to be more significant in favor of the control groups. While students' self-efficacy perception for algorithm development and computational thinking skills increased, it was concluded that this increase only led to a significant difference in favor of the control group in terms of algorithm development self-efficacy perception. In conclusion, block-based and visual programming tools contribute to the development of various skills such as computational thinking and self-efficacy for algorithm development by making learning programming easier and more enjoyable. With this potential, these tools could reach a wide range of users. When these tools used effectively, they can play an important role in developing students' computational thinking skills, increasing their confidence in algorithm development, and teaching programming skills, contributing to more people having digital skills in the future.