Student and Faculty Perceptions of Generative Artificial Intelligence in Student Writing

被引:3
作者
Hostetter, Autumn B. [1 ]
Call, Natalie [1 ]
Frazier, Grace [1 ]
James, Tristan [1 ]
Linnertz, Cassandra [1 ]
Nestle, Elizabeth [1 ]
Tucci, Miaflora [1 ]
机构
[1] Kalamazoo Coll, Dept Psychol, 1200 Acad St, Kalamazoo, MI 49006 USA
关键词
student writing; generative artificial intelligence; plagiarism; TO-LEARN ASSIGNMENTS; PSYCHOLOGY; RETENTION;
D O I
10.1177/00986283241279401
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Background Psychology instructors frequently assign writing-to-learn exercises that include personal reflection. Generative Artificial Intelligence (GenAI) can write text that passes for humans in other domains.Objective Do students and faculty rate a reflection written by GenAI differently than reflections written by students? Do students and faculty agree about the appropriateness of using GenAI for college-level writing?Method Eighty-three students and 82 faculty read four reflections (three written by undergraduate students and one by GenAI). After rating the quality of each, they chose which one they thought was AI-generated. Participants then rated the ethicality of nine potential ways to use GenAI in college-level writing and the potential of each to compromise learning.Results Participants rated the AI-generated reflection similarly to the student-generated reflections and failed to reliably detect AI-generated writing. Faculty and students agreed that using GenAI to produce the final text for a student likely compromises learning more than using it to generate ideas.Conclusion AI-generated reflections blend in with student-written reflections, and students and faculty agree about the potential detriments to learning.Teaching Implications GenAI can be hard to detect in the psychology classroom. Rather than implementing one-size-fits-all policies, instructors might focus classroom conversations on how GenAI could compromise learning.
引用
收藏
页数:11
相关论文
共 28 条
  • [1] American Psychological Association, 2023, APA Guidelines for the Undergraduate Psychology Major
  • [2] Anderson L. W., 2001, TAXONOMY LEARNING TE
  • [3] A systematic review of algorithm aversion in augmented decision making
    Burton, Jason W.
    Stein, Mari-Klara
    Jensen, Tina Blegind
    [J]. JOURNAL OF BEHAVIORAL DECISION MAKING, 2020, 33 (02) : 220 - 239
  • [4] Exploring EFL Students' Writing Performance and Their Acceptance of AI-based Automated Writing Feedback
    Chang, Tsung-Shu
    Li, Yitong
    Huang, Hui-Wen
    Whitfield, Beth
    [J]. 2021 2ND INTERNATIONAL CONFERENCE ON EDUCATION DEVELOPMENT AND STUDIES, ICEDS 2021, 2021, : 31 - 35
  • [5] ENTER THE ROBOT JOURNALIST Users' perceptions of automated content
    Clerwall, Christer
    [J]. JOURNALISM PRACTICE, 2014, 8 (05) : 519 - 531
  • [6] Colman AndrewM., 2009, DICT PSYCHOL, DOI [10.1093/acref/9780199534067.001.0001, DOI 10.1093/ACREF/9780199534067.001.0001]
  • [7] Algorithm Aversion: People Erroneously Avoid Algorithms After Seeing Them Err
    Dietvorst, Berkeley J.
    Simmons, Joseph P.
    Massey, Cade
    [J]. JOURNAL OF EXPERIMENTAL PSYCHOLOGY-GENERAL, 2015, 144 (01) : 114 - 126
  • [8] Evidence-based teaching: Tools and techniques that promote learning in the psychology classroom
    Dunn, Dana S.
    Saville, Bryan K.
    Baker, Suzanne C.
    Marek, Pam
    [J]. AUSTRALIAN JOURNAL OF PSYCHOLOGY, 2013, 65 (01) : 5 - 13
  • [9] Fahmi M. A., 2021, JEES (Journal of English Educators Society), V6, P18, DOI [10.21070/jees.v6i1.849, DOI 10.21070/JEES.V6I1.849]
  • [10] DIDN'T YOU RUN THE SPELL CHECKER? EFFECTS OF TYPE OF SPELLING ERROR AND USE OF A SPELL CHECKER ON PERCEPTIONS OF THE AUTHOR
    Figueredo, Lauren
    Varnhagen, Connie K.
    [J]. READING PSYCHOLOGY, 2005, 26 (4-5) : 441 - 458