Machine Learning and Assessment: Political Barrier to its Implementation in Educational Policy, Research and Practice in Nigeria University

Abstract

The paper examined machine learning and assessment: political barrier to its implementation in educational policy, research and practice in Nigeria University. The paper adopted analytical method because several articles, journals and literatures related machine learning and assessment were reviewed. The aim of machines learning in assessment is to perform cognitive functions in a manner associated with the human’s mind. It powers feedback and also helps students identify areas for improvement on their own. This growth has not only led to improvements in students’ proficiency in traditional core abilities but has also contributed to development in the emerging construction of 21st century skills. These key transformations witnessed in the realm of technical advancement in statistical method within academic related literature in the area of adaptive learning, predictive analytic and personalized learning automated grading system and the political obstacles to its implementation was discussed. This research also suggested that teachers should be included as significant stakeholders for formulating and implementing educational policies considering that they play a crucial role in converting policy on education documents into practical use. Machine learning and assessment as an emerging aspect of educational assessment provides significant diagnostic feedback should be incorporated into educational policy in the country.