The Relevance of Artificial Intelligence in Educational Measurement and Evaluation

Abstract

This paper generally examines the relevance of Artificial Intelligence (AI) in educational measurement and evaluation. It highlights AI-powered tools that are used in educational evaluation which includes automatic essay scoring, predictive analytic tools, Chatbots, intelligent tutoring systems, adaptive testing systems, plagiarism detection systems, computer vision, digital assessment tools, voice and speech recognition tools and learning management systems. Having analysed the above tools, the paper establishes that AI is relevant in educational measurement and evaluation for the purpose of efficiency and speed, personalised and adaptive assessment, fairness and equity, scalability and large scale assessment, data-driven decision making, programme evaluation and policy, continuous and formative assessment, automated grading; and simulation and performance based assessment. In order to promote and sustain the relevance of AI in educational measurement and evaluation, the paper delves into a comprehensive role of educators in AI enhanced assessment which includes; designing assessment, interpreting results, provision of feedback, monitoring AI systems, development of AI literacy among students, curriculum development and using AI tools to support teaching activities. Additionally, the paper elucidates the challenges and limitations of AI in educational evaluation and offers comprehensive recommendations which if educators, policy makers and AI developers can implement will assist in enhancing and sustaining relevance of AI in educational measurement and evaluation, thus resulting in a better way of students’ learning and assessment in schools.