<p>Supporting abstract concepts in chemistry instruction through structured instructional models is important; however, the literature indicates that experimental evidence regarding the integrated use of artificial intelligence applications with constructivist models, particularly the 5E instructional model, is limited. This study aims to examine the effect of using an artificial intelligence tool during the exploration and elaboration phases of the 5E instructional model in teaching the periodic table on students’ Attitudes Toward Science and Motivation Toward Science Learning. The study was conducted using a pretest–posttest quasi-experimental design with a control group and included a total of 34 eighth-grade students enrolled in two classes during the 2023–2024 academic year. In both groups, the instructional process was planned based on the 5E model; AI-supported activities were implemented in the relevant phases in the experimental group, whereas the control group used the textbook and printed materials. Data were collected through attitude and motivation scales and analysed using mixed-design analysis of variance. The findings indicated significant increases in attitude and motivation scores over time in both groups. The time × group interaction was not significant, suggesting that AI integration did not produce a significant differentiation compared to the 5E model alone within this sample. The results demonstrate that structured chemistry instruction based on the 5E model in teaching the periodic table improved students’ Attitudes Toward Science and Motivation Toward Science Learning, and that AI-supported applications may be considered as tools that support the pedagogical structure.</p>