Effective ways of assessment in the AI era

The integration of deep learning and machine learning algorithms has resulted in the development of advanced AI systems, presenting significant challenges across various sectors, including education. The utilization of sophisticated AI technologies and software by educators and students from diverse backgrounds has transformed teaching and learning practices. These AI systems, powered by extensive datasets, demonstrate remarkable accuracy in learning and prediction, exemplified by tools like ChatGPT that can predict answers to complex queries. The COVID-19 pandemic has further accelerated the adoption of digital platforms for exam setting, introducing new modes of assessment. However, alongside the benefits, these advancements also raise concerns regarding the effective assessment of students in alignment with educational curricula. At Lancaster University Ghana, both students and lecturers utilize AI tools for teaching and learning purposes. The problem, however, is that sometimes these tools are unethically utilized by students for academic success, especially with tasks that students are required to research and produce, thereby making it difficult for students to be effectively assessed. This paper aims to explore strategies for the effective assessment of students in the AI era, addressing the challenges posed by AI technologies. A comprehensive review of relevant literature in higher education has been conducted, with the findings offering critical insights for educators in navigating these challenges. References Byrne, N. (2020). An Introduction to Teaching in UK Higher Education : A Guide for International and Transnational Teachers. (C. Butcher (ed.)). Taylor & Francis Group. Carroll, J. (2013). Teaching in Transnational Higher Education. In Teaching in Transnational Higher Education. https://doi.org/10.4324/9780203930625 Cope, B., Kalantzis, M., & Searsmith, D. (2021). Artificial intelligence for education: Knowledge and its assessment in AI-enabled learning ecologies. Educational Philosophy and Theory, 53(12), 1229–1245. https://doi.org/10.1080/00131857.2020.1728732 Dennick, R., Wilkinson, S., & Purcell, N. (2009). Online eAssessment: AMEE Guide No. 39. Medical Teacher, 31(3), 192–206. https://doi.org/10.1080/01421590902792406 Diri, D. M. El. (2023). AI in Accounting Education: A Boon or a Bane in Employers’ Eyes? https://thesedablog.wordpress.com/2023/12/06/ai-in-accounting-education-a-boon-or-a-bane-in-employers-eyes/ Jiao, H. (2015). Enhancing students’ engagement in learning through a formative e-assessment tool that motivates students to take action on feedback. Australasian Journal of Engineering Education, 20(1), 9–18. https://doi.org/10.7158/D13-002.2015.20.1 John Biggs and Catherine Tang. (2011). Teaching For Quality Learning At University Fourt Edition (Vol. 2011). http://books.google.se/books/about/Teaching_for_Quality_Learning_at_Univers.html?id=XhjRBrDAESkC&pgis=1 Llamas-Nistal, M., Fernández-Iglesias, M. J., González-Tato, J., & Mikic-Fonte, F. A. (2013). Blended e-assessment: Migrating classical exams to the digital world. Computers and Education, 62, 72–87. https://doi.org/10.1016/j.compedu.2012.10.021 Sarah Earle. (2021). Principles and purposes of assessment in the classroom. Impact. https://my.chartered.college/impact_article/principles-and-purposes-of-assessment-in-the-classroom/ Solmaz, E. (2023). Follow-up of Artificial Intelligence Development and its Controlled Contribution to the Article: Step to the Authorship? European Journal of Therapeutics, 10–12. https://doi.org/10.58600/eurjther1733 Swiecki, Z., Khosravi, H., Chen, G., Martinez-Maldonado, R., Lodge, J. M., Milligan, S., Selwyn, N., & Gašević, D. (2022). Assessment in the age of artificial intelligence. Computers and Education: Artificial Intelligence, 3(August 2021). https://doi.org/10.1016/j.caeai.2022.100075 Wiggins, G., & Wiggins, G. (2019). The Case for Authentic Assessment The Case for Authentic Assessment . 2(November), 1990–1991. Zhu, C., & Wang, M. (2023). How to harness the potential of ChatGPT in education ? Recommended citation : Zhu , C ., Sun , M ., Luo , J ., Li , T ., & Wang , M . ( 2023 ). How to harness the How to harness the potential of ChatGPT in education ? Chenjia Zhu Jiutong Luo Tianyi Li Min. 15(2), 133–152.