Publication Details
Abstract
Nowadays, artificial intelligence (AI) is rapidly developing. ChatGPT, a modern chatbot, is built on a generative pre-trained transformer and was created by OpenAI. AI has sparked significant public interest, particularly in higher education, where it has secured a strong position. Therefore, this article examines the potential impact of AI on teaching and assessment, focusing on higher education, as these are fundamental aspects of the field. The widespread adoption of AI has introduced several innovations in this area. In the rapidly changing knowledge-based economy of the 21st century, understanding the significance of generative AI in ensuring the relevance, quality, and reliability of higher education is crucial. We conducted several experiments in which AI was used to generate academic articles. These articles were then checked for plagiarism and independently evaluated. The results show that AI can produce high-quality content with diverse perspectives in response to the same assessment task. However, it struggled to generate multiple original pieces of work from a single prompt and faced challenges in properly citing sources. The discussion highlights the need for higher education providers to reassess their approaches in response to AI-driven changes in teaching and assessment. By analyzing empirical data, we propose a new conceptual framework for AI-assisted continuous assessment, which extends beyond mere knowledge testing (what-know) to include skills assessment (what-can-do) and performance evaluation (how-demonstrate).