AI and the future of Assessment in Higher Education: Opportunities and Threats

Description

As the use of artificial intelligence (AI) in all areas of life continues to expand, its potential to transform assessment in higher education (HE) is becoming increasingly evident (Bearman et al, 2022). AI tools have the potential to revolutionize assessment by providing new opportunities for personalization, efficiency, and effectiveness (Holmes, 2018). This paper explores the current state of AI in assessment, the opportunities and challenges it presents, and its potential implications for the future of HE.
The use of AI in assessment includes some promising applications, such as automated grading and personalized feedback (Ye & Manoharan, 2019), and adaptive testing. It also includes some significant challenges AI, such as the need for effective validation and evaluation, concerns around bias, fairness, and ethics (see below).
The potential benefits of AI in assessment in HE concerns the ability to improve the efficiency and accuracy of grading, (Shibani, et al, 2020) thus reducing workload for academic staff, and increasing the speed of providing feedback to students. AI can also personalize assessment, adapting to the learning style and needs of individual students (Moscardini, et al, 2002). Additionally, AI can enable more frequent and comprehensive assessment, which can support student learning and achievement.
However, there are also potential challenges and risks associated with the use of AI in assessment. One major concern is the risk of bias and discrimination in AI algorithms (Barshay & Aslanian, 2019), which could perpetuate and amplify existing inequalities in education. There is also a risk that overreliance on AI systems could lead to a loss of critical thinking and analytical skills among students and academic staff.
The paper concludes that AI has the potential to transform assessment in HE, but its development and implementation must be guided by careful consideration of its benefits and risks, effective training and support for educators, and a commitment to promoting fairness, equity, and human-centred education.

Sources:
Barshay, J., & Aslanian, S., 2019, Under a watchful eye. APM Reports. https://www.apmreports.org/episode/2019/08/06/college-data-tracking-students-graduation , accessed 21/02/23
Bearman, M., Ryan, J., Ajjawi, R., 2022, Discourses of artificial intelligence in higher education: a critical literature review, Higher Education, https://doi.org/10.1007/s10734-022-00937-2
Holmes, N., 2018, Engaging with assessment: increasing student engagement through continuous assessment, Active Learning in Higher Education, vol. 19, no. 1, pp. 23-34, 2018. DOI: https://doi.org/10.1177/1469787417723230.
Moscardini, A.O., Strachan, R., & Vlasova, T., 2020, The role of universities in modern society. Studies in Higher Education, 1–19. https://doi.org/10.1080/03075079.2020.1807493
Shibani, A., Knight, S., & Buckingham Shum, S., 2020, Educator perspectives on learning analytics in classroom practice. The Internet and Higher Education, 46, 100730. https://doi.org/10.1016/j.iheduc.2020.100730
Ye, X and Manoharan, S., 2019, Providing automated grading and personalized feedback, AIIPCC ‘19: Proceedings of the International Conference on Artificial Intelligence, Information Processing and Cloud Computing, Article 49, pp. 1-5, https://doi.org/10.1145/3371425.3371453 .

Period	12 Jul 2023
Event title	Teaching Excellence Academy International Teaching and Learning Conference 2023: Assessment and Feedback for Student Success
Event type	Conference
Location	Hull, United KingdomShow on map
Degree of Recognition	National