Automated Assessment of Students’ Work using AI Tools for Grading and Feedback Processes in Selected Tertiary Institutions in Akwa Ibom State, Nigeria

Abstract

This study examined automated assessment using Artificial Intelligence (AI) to automate grading and provide timely feedback of students work in public tertiary institution Akwa Ibom State. The challenges associated with traditional assessment methods, including delayed feedback, grading inconsistency, and high teacher workload informed the study. The study aimed at investigating effectiveness of automated assessment systems in public tertiary institutions. The study adopted a descriptive survey research design. A sample of 300 respondents, comprising lecturers and students from tertiary institutions were selected using stratified random sampling technique. Data were collected using a structured questionnaire titled AI-Based Automated Assessment and Feedback Questionnaire (AIAAFQ). The instrument was validated by experts and tested for reliability using Cronbach Alph reliability and a coefficient of 0.72 was obtain. Data collected were analyzed using mean and standard deviation to answer research questions, while t-test and Chi-Square Analysis were used to test the hypotheses at 0.05 level of significance. The findings revealed that AI-based automated assessment systems significantly enhance: Speed and efficiency of grading student work, consistency and reliability of assessment, timeliness and quality of feedback. The integration of AI tools to students’ assessment should be encouraged to improve grading efficiency and feedback delivery.