Enhancing Educational Assessment Through Genai: Leveraging Revised Bloom's Taxonomy for Question Generation With Chatgpt

Abstract

With advancing technology, effective evaluation methods are increasingly crucial. This chapter examines how well ChatGPT can generate educational assessment questions on the cognitive process dimension of the Revised Bloom's Taxonomy (RBT), consisting of six levels: remember, understand, apply, analyze, evaluate, and create. The chapter begins with emphasizing the significance of AI-driven technology in educational assessment and discusses related studies. Then Bloom Taxonomy's original and revised versions were explained. To illustrate the practice of generating different types of questions, multiple-choice and open-ended questions were generated with ChatGPT. We offered a preliminary prompt structure with determined variables: the role, number of questions, type of questions, and cognitive process level of RBT. To check the efficiency of the prompt, questions were generated across six cognitive process levels of RBT. Additionally, the pitfalls of generating assessment questions by ChatGPT and suggestions for further research were addressed. Consequently, by providing a structured framework for various cognitive levels, RBT significantly facilitates the use of prompt engineering in generating questions with ChatGPT. Although it may not yield successful results to the desired extent regarding learning outcomes, ChatGPT appears to have high potential as a valuable resource for educators in the initial stages of question generation. Lastly, it is worth emphasizing that repeating the process of generating questions with ChatGPT in different domains and using ChatGPT-generated questions without being filtered through the cognitive verification of the teacher for validity and meaningfulness should be avoided at this stage. Further research is recommended to explore the effectiveness and comprehensibility of the ChatGPT-generated questions. © 2024 Peter Lang Group AG, Lausanne.