In this section
@inproceedings{Yin:2025:10.1017/pds.2025.10046,
author = {Yin, Y and Wang, B and Zuo, H and Liu, R and Vohra, SI and Haydon-Rowe, S and Childs, PRN},
doi = {10.1017/pds.2025.10046},
pages = {319--328},
publisher = {Cambridge University Press},
title = {Abilities of design professors to distinguish design assignments generated by students and AI},
url = {http://dx.doi.org/10.1017/pds.2025.10046},
year = {2025}
}
TY - CPAPER
AB - This study aims to detect the ability of professors to distinguish design assignments generated by students with and without using AI. Ten students were recruited to undertake a conceptual design task twice, one with and one without the help of AI. 105 higher-education associate, assistant and full professors from industrial and product design programmes were recruited to assess the generated designs using a 7-point Likert Scale with nine indexes. The results indicate that assessors have moderate ability to distinguish between design assignments of students using AI and those where students did not use AI. Three cues to suggest the risk of the design assignment is made with AI instead of students who did not use AI were identified. By considering the three cues, lecturers distinguish design assignments generated by students with or without AI.
AU - Yin,Y
AU - Wang,B
AU - Zuo,H
AU - Liu,R
AU - Vohra,SI
AU - Haydon-Rowe,S
AU - Childs,PRN
DO - 10.1017/pds.2025.10046
EP - 328
PB - Cambridge University Press
PY - 2025///
SN - 2732-527X
SP - 319
TI - Abilities of design professors to distinguish design assignments generated by students and AI
UR - http://dx.doi.org/10.1017/pds.2025.10046
UR - https://doi.org/10.1017/pds.2025.10046
ER -