The effect of the role of artıfıcıal ıntellıgence supported learnıng envıronments on dıfferent varıables ın matter and ındustry unıt

In recent years, artificial intelligence (AI) technologies have been increasingly adopted in the field of education, and are believed to have the potential to transform learning processes, particularly in science courses where abstract concepts are prevalent. This study aims to examine the effects of an AI-supported learning tool, implemented within the "Matter and Industry" unit of the 8th grade science curriculum, on students' academic achievement in science, science self-efficacy, critical thinking skills related to science, and Next Generation Science Standards (NGSS) competencies. The research was conducted using a quasi-experimental design with pre-test and post-test control groups. The study group consisted of 34 eighth-grade students enrolled in a middle school located in the central district of Düzce, Türkiye. While the control group continued learning based on the current curriculum, the experimental group received instruction enriched with an AI-supported learning environment. Data collection instruments were selected in line with the research objectives, and applied at the beginning and end of the 28-lesson implementation process. Data were analyzed using SPSS 27.0 software. The results revealed that the experimental group demonstrated significant improvements across all variables, whereas the control group showed only a limited change in academic achievement and significant decreases in the other three measures. These findings suggest a strong correlation among the four variables. Notably, the observed improvement in science self-efficacy appeared to enhance students' active participation in learning, which in turn was reflected in the development of their critical thinking skills, ultimately leading to improvements in their NGSS competencies. The holistic development observed in the experimental group indicates that AI-supported learning environments not only support cognitive development but also contribute to students' affective and scientific process skills. In contrast, the significant declines observed in the control group may be attributed to the limitations of traditional teaching methods emphasized in the literature, as well as to possible student motivation loss and resentful demoralization. This situation suggests that students' science self-efficacy, critical thinking skills, and alignment with NGSS are influenced not only by the instructional program but also by multiple variables. In conclusion, the findings highlight that when used appropriately, AI-supported learning environments hold substantial potential to support students' cognitive and affective development, providing a pedagogical transformation in science education that empowers students not only as consumers of knowledge but also as active participants in scientific processes.