Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Transforming Educ-AI-tion in South Africa: Can AI-Driven Grading Transform the Future of Higher Education?
5
Zitationen
2
Autoren
2024
Jahr
Abstract
Aim: The objective of this paper was to explore students' attitudes and perceptions towards AI-driven grading systems in South African higher education, to ascertain whether AI grading can transform the future of higher education in South Africa. Methods: The study employed a qualitative methodology with an interpretive approach to gather the viewpoints, perceptions and experiences of higher education students in South Africa regarding AI grading of assessments. The sample consisted of thirteen (n=13) participants, including six (n=6) males and seven (n=7) females, ranging in age from 19 to 24. Participants were selected through purposive sampling and were from various years of study, such as first-year students pursuing a Bachelor of Commerce in Accounting and Supply Chain Management, as well as third-year students in Bachelor of Commerce General and Law programs. The study conducted semi-interviews to gather students' views, perceptions and experiences with the use of AI in education. Results: The research revealed that students see the advantages of AI, such as objectivity and faster feedback, but also express concerns about lack of empathy and the potential anxiety of being graded by a machine. Ethical considerations, including educating students on responsible AI use and ensuring data privacy, are also important. Conclusion: AI has the potential to revolutionize grading by providing consistent, objective feedback and freeing up educators to focus on teaching and student support, despite fears of AI replacing educators. Recommendations: The study suggests that educational institutions must have a strong culture for the digital era that is adaptable and responsive to the many opportunities, as well as the significant threats and challenges, presented by technology, market disruptions, changing customer behaviours, evolving workforce composition and changing work methods. Educators, policymakers and students must ultimately embrace the combination of digital and human interaction, which is crucial to achieving the necessary cultural shift.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.611 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.504 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 8.025 Zit.
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
2019 · 6.835 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.