Designing AI-based personalized learning environments and examining their impact on students motivation and academic achievement

Mehdi Elahi¹ zahra habibi²

1) Bachelor’s degree in Educational Sciences, Farhangian University (Shahid Motahari Campus, Nowshahr),
2) Bachelor’s degree in Educational Sciences from the University of Sari,

IOI Code : ACZF-ACACZZ
Publication : 6th.International Congress on Management, Economy, Humanities, Education and Business Development(6icmba.ir)
Abstract :
    The objective of this research is to design an AI-based personalized learning environment and to examine its impact on students motivation and academic achievement. To achieve this, a meta-synthesis approach—following the seven-step model proposed by Sandelowski and Barroso—is employed. This process encompasses formulating research questions, conducting a systematic literature review, searching for and selecting articles, extracting data, analyzing and synthesizing qualitative findings, ensuring quality control, and presenting the results. In the initial phase, research questions are defined based on the parameters of what, which population, when, and how to establish a search framework. Subsequently, a systematic search is conducted across reputable domestic and international databases using relevant keywords—such as personalized learning, artificial intelligence, motivation, and academic achievement —followed by a screening process based on predefined inclusion and exclusion criteria. In the next stage, relevant data are extracted from the selected studies and analyzed using qualitative content analysis, involving coding and categorization to identify common patterns. Findings from existing research indicate that AI-based personalized feedback has a moderate effect on academic achievement (g=0.58) and a strong effect on learning motivation (g=0.82). Furthermore, personalizing learning content based on student interests—facilitated by generative AI—enhances intrinsic motivation and learning performance. However, the effectiveness of such environments depends on implementation conditions, the role of the teacher, and the students ability levels; moreover, there is a risk that over-reliance on artificial intelligence could undermine critical thinking. Therefore, the design of a personalized learning environment must go beyond the mere replacement of digital tools and focus on pedagogical interaction and teacher support, in order to achieve sustained motivation and progress.

Keywords : personalized learning artificial intelligence motivation academic achievement students