TY - GEN
T1 - Exploring ChatGPT-Generated Assessment Scripts of Probability and Engineering Statistics from Bloom’s Taxonomy
AU - Kwan, Christopher Chung Lim
N1 - Publisher Copyright:
© 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2023/11/9
Y1 - 2023/11/9
N2 - Subject Instructors, class teachers, and educational practitioners always devote much time to preparing assessment scripts, suggested solutions, and marking schemes such as mid-term and final examination scripts for assessing students’ learning and performance as well as measuring their achievements of the subject learning outcomes. With precise prompts, ChatGPT seems to be able to work as an assistant to them in education, generating responses and deliverables in a quite structured and almost instant manner. In this paper, a ChatGPT-generated assessment script with its marking scheme and suggested solution of Probability and Engineering Statistics is explored based on Bloom’s Taxonomy. It is found that the ChatGPT-generated assessment script is partially complete and one of the multiple-choice questions is incorrect. The total score of the assessment script is not consistent with that of its marking scheme. Its suggested solution to one of the questions is missing. In addition, there are many application-oriented questions but few analysis-based questions and no evaluation-based question at all in the assessment script as per Bloom’s Taxonomy. Overall, ChatGPT-generated assessment scripts should further be reviewed and refined by educational practitioners to ascertain different levels of difficulty of questions which are in good alignment with the subject curriculum and the subject learning outcomes.
AB - Subject Instructors, class teachers, and educational practitioners always devote much time to preparing assessment scripts, suggested solutions, and marking schemes such as mid-term and final examination scripts for assessing students’ learning and performance as well as measuring their achievements of the subject learning outcomes. With precise prompts, ChatGPT seems to be able to work as an assistant to them in education, generating responses and deliverables in a quite structured and almost instant manner. In this paper, a ChatGPT-generated assessment script with its marking scheme and suggested solution of Probability and Engineering Statistics is explored based on Bloom’s Taxonomy. It is found that the ChatGPT-generated assessment script is partially complete and one of the multiple-choice questions is incorrect. The total score of the assessment script is not consistent with that of its marking scheme. Its suggested solution to one of the questions is missing. In addition, there are many application-oriented questions but few analysis-based questions and no evaluation-based question at all in the assessment script as per Bloom’s Taxonomy. Overall, ChatGPT-generated assessment scripts should further be reviewed and refined by educational practitioners to ascertain different levels of difficulty of questions which are in good alignment with the subject curriculum and the subject learning outcomes.
KW - Bloom’s taxonomy
KW - ChatGPT
KW - learning outcome
KW - probability and engineering statistics
KW - subject curriculum
UR - http://www.scopus.com/inward/record.url?scp=85177183243&partnerID=8YFLogxK
U2 - 10.1007/978-981-99-8255-4_24
DO - 10.1007/978-981-99-8255-4_24
M3 - Conference article published in proceeding or book
AN - SCOPUS:85177183243
SN - 9789819982547
T3 - Communications in Computer and Information Science
SP - 275
EP - 286
BT - Technology in Education. Innovative Practices for the New Normal - 6th International Conference on Technology in Education, ICTE 2023, Proceedings
A2 - Cheung, Simon K.S.
A2 - Wang, Fu Lee
A2 - Li, Kam Cheong
A2 - Paoprasert, Naraphorn
A2 - Charnsethikul, Peerayuth
A2 - Phusavat, Kongkiti
PB - Springer Science and Business Media Deutschland GmbH
T2 - 6th International Conference on Technology in Education, ICTE 2023
Y2 - 19 December 2023 through 21 December 2023
ER -