Artificial Intelligence in the Classroom: Transforming Assessment and Inclusivity in the Era of Smart Education-Supporting SDG 4 and SDG 9

Abstract

The current research examines the implementation of Artificial Intelligence (AI) in learning measurement and instructional development with respect to the effect it has on students in terms of learning outcomes, engagement, and accessibility in urban and semi-urban settings. The study adopts a mixed-methodology as it uses a quantitative methodology involving the analysis of pre and post-test scores, engagement survey, and teacher feedback with qualitative information on it in the form of semi-structured interviews and focus groups. The results indicate a large positive effect on the performance of the students, especially on Mathematics and Language Arts whereby the average score improvement on the test was 20% in the urban schools, as opposed to 12 percent in the semi-urban schools. These findings indicate that AI-based learning technologies affect the academic outcomes in a beneficial way, particularly in schools that are better equipped. Regarding student engagement, the post-engagement surveys had a 27% increase in student engagement with urban students (38 percent) indicating a higher increase to semi-urban students (23 %). This implies that the quality of infrastructure is very crucial towards getting the AI tools to reach their maximum potential in engaging students. The qualitative data highlight the lack of access to AI tools in teachers, especially in semi-urban communities, because of insufficient infrastructure. The urban school teachers were more confident in implementing AI tools, and both settings showed that humanities teachers doubted the capability of AI to measure the creative subjects. Nonetheless, educators in both groups emphasized the possibility of the AI to enhance the grading efficiency, and the grading time decreased by a third through the use of the AI-based grading tools. The paper also reveals major obstacles to the adoption of AI, such as lack of teacher training, issues with language proficiency, and psychological issues like AI-anxiety and language anxiety, which are potential and can destroy the effectiveness of AI. The results also support the significance of a psychological-linguistic nexus, in which linguistic competence and emotional preparedness are the key determinants to allow students to interact with AI tools successfully. Finally, the paper notes that equitable digital infrastructure, teacher empowerment, and ethical AI implementation are necessary to implement AI successfully in the classroom that addresses SDG4 and SDG9. The study provides practical recommendations to policy makers that will bring inclusive, accessible, and effective AI-based learning.