Abstract:
With the advent of generative artificial intelligence (GenAI), there is a strong need to revisit the grading or assessment mechanism. In this paper, we present a 3R frame...Show MoreMetadata
Abstract:
With the advent of generative artificial intelligence (GenAI), there is a strong need to revisit the grading or assessment mechanism. In this paper, we present a 3R framework to facilitate the grading of GenAI-based assignments. Basically, there are three essential components: Report, Revise and Reflect. Students should report on how they use GenAI tool(s). They should also revise its output by providing their own input or contributions. Last but not least, they should provide a learning reflection. We also present a 3R rubric for evaluation purposes and propose a GPT formula for determining an effective grade. For illustration purposes, we discuss two cases, covering essay assignments and programming assignments. Furthermore, to evaluate the 3R framework from the student perspective, we present and discuss student survey results. The 3R framework can provide the basis for further research study as well.
Published in: 2023 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE)
Date of Conference: 28 November 2023 - 01 December 2023
Date Added to IEEE Xplore: 26 January 2024
ISBN Information: