Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/311950 
Erscheinungsjahr: 
2024
Schriftenreihe/Nr.: 
IZA Discussion Papers No. 17511
Verlag: 
Institute of Labor Economics (IZA), Bonn
Zusammenfassung: 
Grading and providing feedback are two of the most time-consuming activities in education. We developed a randomised controlled trial (RCT) to test whether they could be performed by generative artificial intelligence (Gen-AI). We randomly allocated undergraduate students to feedback provided either by a human instructor, ChatGPT 3.5, or ChatGPT 4. Our results show that: (i) Students treated with the freely accessible ChatGPT 3.5 received lower grades in subsequent assessments than their peers in the control group who always received human feedback; (ii) No such penalty was observed for ChatGPT 4. Separately, we tested the capacity of Gen-AI to grade student work. Gen-AI grades and ranks were significantly different than human-generated grades. Overall, while the newest LLM helps learning as well as a human, its ability to grade student work is still inferior.
Schlagwörter: 
feeback
grading
Artificial Intelligence
learning with Gen-AI
JEL: 
A22
C93
I23
I24
Dokumentart: 
Working Paper

Datei(en):
Datei
Größe
1.21 MB





Publikationen in EconStor sind urheberrechtlich geschützt.