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Human and AI-Generated Feedback in Higher Education: A Systematic Review of Effectiveness and Student Perceptions

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Title: Human and AI-Generated Feedback in Higher Education: A Systematic Review of Effectiveness and Student Perceptions
Language: English
Authors: Candy Haydee Guardia-Paniura (ORCID 0000-0003-1141-2820), Timoteo Cueva-Luza (ORCID 0000-0002-2199-5671), Favio Mauricio Cruz-Carpio (ORCID 0000-0001-6605-6734), Raúl Reynaldo Ito-Díaz (ORCID 0000-0003-3370-5990), David Victor Apaza-Paco (ORCID 0000-0002-8553-2879), Nilda Rosas-Rojas (ORCID 0000-0002-6509-5528), Benedicta Mamani-Mamani (ORCID 0000-0003-4502-4981), Ángel Terrero-Pérez (ORCID 0000-0002-7338-3642), Renato Yassutaka Faria Yaedú (ORCID 0000-0002-2576-7887), Mariela Peralta-Mamani (ORCID 0000-0002-0243-9194)
Source: Contemporary Educational Technology. 2026 18(1):623.
Availability: Contemporary Educational Technology. Faculty of Communication Sciences, Anadolu University, Yunus Emre Campus, Eskisehir 26470, Turkey. e-mail: editor@cedtech.net; Web site: http://www.cedtech.net
Peer Reviewed: Y
Page Count: 18
Publication Date: 2026
Document Type: Journal Articles
Information Analyses
Education Level: Higher Education
Postsecondary Education
Descriptors: Artificial Intelligence, Student Attitudes, Feedback (Response), Instructional Effectiveness, College Students, Technology Uses in Education, College Faculty, Teacher Student Relationship, Foreign Countries, Educational Quality
Geographic Terms: Saudi Arabia, United States, China, Montenegro, Poland
ISSN: 1309-517X
Abstract: This study aims to compare the feedback provided by human professors and ChatGPT on university students' work and to report on students' perceptions of both types of feedback. A systematic review was conducted following PRISMA 2020 guidelines. Databases research included Web of Science, Scopus, EBSCO, ACM Digital Library, and IEEE Xplore, with additional gray literature sources, until October 2024. Inclusion criteria were cross-sectional studies evaluating university students' work, comparing feedback from ChatGPT with human professors. Data extraction was performed using a standardized form, and risk of bias was assessed with the Joanna Briggs Institute critical appraisal tool. A narrative synthesis of the results was made. PROSPERO registration number: CRD42024566691. This review included 8 studies with 461 students. ChatGPT feedback was detailed and rapid, while human feedback was valued for its personalization and emotional support. Students appreciated the detailed and immediate nature of ChatGPT feedback but noted its lack of emotional nuance and context-specific guidance. Human feedback was preferred for addressing individual learning needs and providing affective support. A combination of both types of feedback to maximize benefits. ChatGPT can assist human teachers by providing detailed and timely feedback to university students. However, human supervision is essential to ensure feedback is nuanced and contextually appropriate. A hybrid approach can optimize the learning experience in higher education. Further research is necessary to explore AI applications in educational settings and understand their impact on learning outcomes.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1499514
Database: ERIC
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  Data: Human and AI-Generated Feedback in Higher Education: A Systematic Review of Effectiveness and Student Perceptions
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  Data: <searchLink fieldCode="AR" term="%22Candy+Haydee+Guardia-Paniura%22">Candy Haydee Guardia-Paniura</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-1141-2820">0000-0003-1141-2820</externalLink>)<br /><searchLink fieldCode="AR" term="%22Timoteo+Cueva-Luza%22">Timoteo Cueva-Luza</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-2199-5671">0000-0002-2199-5671</externalLink>)<br /><searchLink fieldCode="AR" term="%22Favio+Mauricio+Cruz-Carpio%22">Favio Mauricio Cruz-Carpio</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-6605-6734">0000-0001-6605-6734</externalLink>)<br /><searchLink fieldCode="AR" term="%22Raúl+Reynaldo+Ito-Díaz%22">Raúl Reynaldo Ito-Díaz</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-3370-5990">0000-0003-3370-5990</externalLink>)<br /><searchLink fieldCode="AR" term="%22David+Victor+Apaza-Paco%22">David Victor Apaza-Paco</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-8553-2879">0000-0002-8553-2879</externalLink>)<br /><searchLink fieldCode="AR" term="%22Nilda+Rosas-Rojas%22">Nilda Rosas-Rojas</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-6509-5528">0000-0002-6509-5528</externalLink>)<br /><searchLink fieldCode="AR" term="%22Benedicta+Mamani-Mamani%22">Benedicta Mamani-Mamani</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-4502-4981">0000-0003-4502-4981</externalLink>)<br /><searchLink fieldCode="AR" term="%22Ángel+Terrero-Pérez%22">Ángel Terrero-Pérez</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-7338-3642">0000-0002-7338-3642</externalLink>)<br /><searchLink fieldCode="AR" term="%22Renato+Yassutaka+Faria+Yaedú%22">Renato Yassutaka Faria Yaedú</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-2576-7887">0000-0002-2576-7887</externalLink>)<br /><searchLink fieldCode="AR" term="%22Mariela+Peralta-Mamani%22">Mariela Peralta-Mamani</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-0243-9194">0000-0002-0243-9194</externalLink>)
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  Data: Contemporary Educational Technology. Faculty of Communication Sciences, Anadolu University, Yunus Emre Campus, Eskisehir 26470, Turkey. e-mail: editor@cedtech.net; Web site: http://www.cedtech.net
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  Data: 18
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  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
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– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Saudi+Arabia%22">Saudi Arabia</searchLink><br /><searchLink fieldCode="DE" term="%22United+States%22">United States</searchLink><br /><searchLink fieldCode="DE" term="%22China%22">China</searchLink><br /><searchLink fieldCode="DE" term="%22Montenegro%22">Montenegro</searchLink><br /><searchLink fieldCode="DE" term="%22Poland%22">Poland</searchLink>
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  Data: 1309-517X
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This study aims to compare the feedback provided by human professors and ChatGPT on university students' work and to report on students' perceptions of both types of feedback. A systematic review was conducted following PRISMA 2020 guidelines. Databases research included Web of Science, Scopus, EBSCO, ACM Digital Library, and IEEE Xplore, with additional gray literature sources, until October 2024. Inclusion criteria were cross-sectional studies evaluating university students' work, comparing feedback from ChatGPT with human professors. Data extraction was performed using a standardized form, and risk of bias was assessed with the Joanna Briggs Institute critical appraisal tool. A narrative synthesis of the results was made. PROSPERO registration number: CRD42024566691. This review included 8 studies with 461 students. ChatGPT feedback was detailed and rapid, while human feedback was valued for its personalization and emotional support. Students appreciated the detailed and immediate nature of ChatGPT feedback but noted its lack of emotional nuance and context-specific guidance. Human feedback was preferred for addressing individual learning needs and providing affective support. A combination of both types of feedback to maximize benefits. ChatGPT can assist human teachers by providing detailed and timely feedback to university students. However, human supervision is essential to ensure feedback is nuanced and contextually appropriate. A hybrid approach can optimize the learning experience in higher education. Further research is necessary to explore AI applications in educational settings and understand their impact on learning outcomes.
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        PageCount: 18
        StartPage: 623
    Subjects:
      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Student Attitudes
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      – SubjectFull: Feedback (Response)
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