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Transforming Student Assessments in the Era of Machine Learning: Balancing Innovation and Ethics
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Author(s): S. Valai Ganesh (Ramco Institute of Technology, India), V. Suresh (National Engineering College, India), S. Rajakarunakaran (Ramco Institute of Technology, India), L. Ganesan (Ramco Institute of Technology, India)and V. Suryakumar (Ramco Institute of Technology, India)
Copyright: 2025
Pages: 26
Source title:
Driving Quality Education Through AI and Data Science
Source Author(s)/Editor(s): Thangavel Murugan (United Arab Emirates University, UAE), Karthikeyan P. (Thiagarajar College of Engineering, India)and A.M. Abirami (Thiagarajar College of Engineering, India)
DOI: 10.4018/979-8-3693-8292-9.ch017
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Abstract
Machine learning algorithms are now being used to improve personalised student assessments in higher education. This chapter examines the benefits and ethical considerations of using these algorithms to develop personalised and customised testing experiences. Through the analysis of vast datasets, machine learning algorithms may offer useful insights into student progress and identify specific areas that require work. This allows educators to customise their teaching methods to meet the individual needs of each student. Nevertheless, the implementation of these technologies gives rise to ethical considerations pertaining to privacy, bias, and openness. This chapter examines the difficulties associated with machine learning in personalised student assessments and proposes creative methods to ensure fair and responsible use. The objective of the discussion is to find a middle ground between utilising the potential advantages of these algorithms and upholding ethical principles, thereby promoting a more efficient and inclusive learning environment in higher education.
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