Effects of artificial intelligence applications and coding training on algorithmic thinking competencies and attitudes towards the course

This study aims to investigate the effects of coding education with artificial intelligence applications on algorithmic thinking skills and attitudes towards the course. A quasi-experimental design with a pre-test post-test control group was used in the study. The study group consisted of 60 5th grade students studying at a middle school in Muradiye district of Van province in the 2022-2023 academic year. The study group was divided into experimental and control groups. Pictoblox AI and Mblock AI programs were used with the experimental group students. Control group students used computerless coding and flowcharts based on the activities in the MEB Informatics and Software course program. In the collection of research data, the "Coding Attitude Scale for Middle School Students" developed by Akkuş, Özhan and Kan (2019), the "Self-Efficacy Perception Scale towards Computational Thinking Skills" developed by Gülbahar, Kert and Kalelioğlu (2018) and the "Personal Information Form" where students' demographic information was taken were used. While no difference was observed in the pre-test scores of attitude towards coding and algorithmic thinking skills between the control and experimental groups, a difference was observed in favor of the experimental group in the post-test scores. The post-test scores of the experimental group students for algorithmic thinking skills and attitude towards coding were higher than their pre-test scores. There was no difference between the pre-test and post-test scores of the control group students for algorithmic thinking skills and attitude towards coding. There was no difference between the pre-test and post-test scores of the control group students for algorithmic thinking skills and attitude towards coding according to gender. While a difference was found in favor of males in the post-test scores of algorithmic thinking skills of the experimental group students, there was no difference between the pre-test and post-test scores of their attitudes towards coding according to gender. While there was no difference between the algorithmic thinking skill scores of the control group students according to their BIT (information and communication technologies) usage times, a difference was found between their BIT usage times and attitude towards coding scores in the post-test. It was observed that this difference was between 1 year and 4 years, 1-2 years and 4 years, and 3 years and 4 years. However, the average time spent at the beginning of BIT did not have a difference on algorithmic thinking skills and attitude towards coding scores. While there was no difference between the pre-test scores of algorithmic thinking skills and attitude towards coding of the experimental group students according to their BIT usage times, a difference was found in the post-test. This difference was observed between 1 year and 1-2 years, 1-2 years and 4 years in the post-test scores of algorithmic thinking skills of students using BIT, while it was observed between 1 year and 4 years, 1-2 years and 4 years in the post-test scores of attitude towards coding. There was no difference between the pre-test-post-test scores of algorithmic thinking skills according to the average time spent at the beginning of BIT of the experimental group students. Similarly, no difference was observed between the pre-test-post-test scores of attitude towards coding. In line with the findings obtained, it can be suggested that artificial intelligence applications should be given more place in education programs in order to increase the level of algorithmic thinking skills and attitudes towards coding of the students. Keywords: algorithmic thinking skill, coding, attitude, artificial intelligence