Impact of AI-Based E-Testing on Grade 8 Students’ Academic Achievement and Motivation: Exploring Challenges and Opportunities: A Qualitative Study

Abstract

Educational practices are changing rapidly in AI especially in the area of evaluation and assessment. More and more educational institutes are using AI based testing. It provides automated assessment, adaptive learning help, immediate feedback, and personalized evaluation experiences. This study is qualitative in nature and it investigates the impact of AI based e-testing on academic motivation and achievement of 8th grade students. It also discusses the challenges and opportunities for these systems. The objective of this study is to understand students’ experiences with AI-supported e-testing environments and to investigate the effect of technologies on students’ learning outcomes and engagement in classrooms. The research will be based on a qualitative research design and will mainly use semi-structured interviews and student reflections as data collection methods. The target population is Grade 8 students who are regular users of AI-based e-testing systems within the school context. Data will be analysed thematically to identify key patterns, perceptions and experiences regarding the use of AI-based assessment practices. The findings should demonstrate that AI-based e-testing has the potential to enhance students’ motivation, engagement, self-confidence, and academic achievement via instant feedback, personalized learning, and interactive evaluation approaches. However, factors such as technical problems, dependence on the Internet, lack of digital literacy, distraction, and overdependence on AI technologies may affect the students’ learning experience. The results of this study can offer useful recommendations to teachers, school administrators and policy makers for the effective implementation of AI-based e-testing systems in support of Student Learning Outcomes (SLOs).