Artificial Intelligence (AI) Based Instructional Model for Enhancing Personalized Learning in the Classroom
Year: 2025
Type: article
Study design: Clinical Trial
Abstract: In this research, I address the question of whether an instructional model based on Artificial Intelligence (AI) can help provide more individual learning experiences in an engaging English classroom context among the learners in the ninth grade. A quantitative type of research using a sample size of 30 students was performed through pre- and post-intervening surveys, engagement and performance monitoring. The main aims were presenting the effectiveness of AI in providing personalized content provision, measuring its influence on the student engagement and performance, the interaction of a teacher with the system, and revealing the distinctions based on gender in terms of system acceptance and effectiveness. The results indicated that the AI instruction model contributed to significant increases in the personalized learning results. The level of engagement, educational performance, and the interaction with the AI system proved to be higher in case of male students and lower in case of female students. It was discovered that teacher participation was an important key to the effective implementation of the AI tool and the greater the interaction of a teacher with students, the better are the results of the learning. These findings are indicative of the fact that gender relations, as well as an active teacher intervening process, are critical factors in the process of AI-guided instruction optimization. On the basis of those results, it is suggested that schools should utilize AI based models in facilitating personal learning, as well as well-planned teacher education and gender-sensitive interaction patterns. The research is an addition to the existing evidence of the usefulness of AI in the educational environment and the criticality of the inclusive practices approach that would help realize the potential value of AI to its maximum. To further elaborate, future studies ought to consider these findings beyond the short-term effects, different subjects, and large classes of students with the intention of comprehending how such AI-based learning interventions are scalable and sustainable.
Source: Scholar Insight Journal
DOI: 10.68024/52kz3v92
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7204693983