Leveraging Large Language Models for Analysis of Student Course Feedback

被引：1
|
作者：
Wang, Zixuan [1 ]
Denny, Paul [1 ]
Leinonen, Juho [1 ]
Luxton-Reilly, Andrew [1 ]
机构：
[1] Univ Auckland, Auckland, New Zealand
来源：
PROCEEDINGS OF THE 16TH ANNUAL ACM INDIA COMPUTE CONFERENCE, COMPUTE 2023 | 2023年
关键词：
Student Evaluation of Teaching; Large Language Model; Student Feedback; Natural Language Processing;
D O I：
10.1145/3627217.3627221
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This study investigates the use of large language models, specifically ChatGPT, to analyse the feedback from a Summative Evaluation Tool (SET) used to collect student feedback on the quality of teaching. We find that these models enhance comprehension of SET scores and the impact of context on student evaluations. This work aims to reveal hidden patterns in student evaluation data, demonstrating a positive first step towards automated, detailed analysis of student feedback.
引用
收藏
页码：76 / 79
页数：4
相关论文
共 50 条
  • [21] Leveraging large language models to foster equity in healthcare
    Rodriguez, Jorge A.
    Alsentzer, Emily
    Bates, David W.
    JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2024, 31 (09)
  • [22] Leveraging Large Language Models for Clinical Abbreviation Disambiguation
    Hosseini, Manda
    Hosseini, Mandana
    Javidan, Reza
    JOURNAL OF MEDICAL SYSTEMS, 2024, 48 (01)
  • [23] Leveraging large language models for peptide antibiotic design
    Guan, Changge
    Fernandes, Fabiano C.
    Franco, Octavio L.
    de la Fuente-nunez, Cesar
    CELL REPORTS PHYSICAL SCIENCE, 2025, 6 (01):
  • [24] Leveraging large language models for academic conference organization
    Luo, Yuan
    Li, Yikuan
    Ogunyemi, Omolola
    Koski, Eileen
    Himes, Blanca E.
    NPJ DIGITAL MEDICINE, 2025, 8 (01):
  • [25] On Leveraging Large Language Models for Multilingual Intent Discovery
    Chow, Rudolf
    Suen, King yiu
    Lam, Albert Y. S.
    ACM TRANSACTIONS ON MANAGEMENT INFORMATION SYSTEMS, 2025, 16 (01)
  • [26] LEVERAGING LARGE LANGUAGE MODELS WITH VOCABULARY SHARING FOR SIGN LANGUAGE TRANSLATION
    Lee, Huije
    Kim, Jung-Ho
    Hwang, Eui Jun
    Kim, Jaewoo
    Park, Jong C.
    2023 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING WORKSHOPS, ICASSPW, 2023,
  • [27] Formative Feedback on Student-Authored Summaries in Intelligent Textbooks Using Large Language Models
    Morris, Wesley
    Crossley, Scott
    Holmes, Langdon
    Ou, Chaohua
    Dascalu, Mihai
    Mcnamara, Danielle
    INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION, 2024,
  • [28] Leveraging the power of generative Al: a case study on feedback analysis of student evaluation in an undergraduate physiology practical course
    Fong, Angelina
    Lin, Julian
    Ryan, Lauren
    Chang, Melody
    PHYSIOLOGY, 2024, 39
  • [29] Propagating Large Language Models Programming Feedback
    Koutcheme, Charles
    Hellas, Arto
    PROCEEDINGS OF THE ELEVENTH ACM CONFERENCE ON LEARNING@SCALE, L@S 2024, 2024, : 366 - 370
  • [30] Leveraging large language models for generating responses to patient messages-a subjective analysis
    Liu, Siru
    Mccoy, Allison B.
    Wright, Aileen P.
    Carew, Babatunde
    Genkins, Julian Z.
    Huang, Sean S.
    Peterson, Josh F.
    Steitz, Bryan
    Wright, Adam
    JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2024, 31 (06) : 1367 - 1379
12345