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Can GenAI complement supervisor support in shaping postgraduates' research experiences? A mixed-methods approach.

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Title: Can GenAI complement supervisor support in shaping postgraduates' research experiences? A mixed-methods approach.
Authors: Huang, Yating (AUTHOR), Li, Sihui (AUTHOR), Liu, Zihan (AUTHOR)
Source: Studies in Higher Education. Apr2026, Vol. 51 Issue 4, p836-854. 19p.
Subjects: Generative artificial intelligence, Mentors, Mixed methods research, Graduate students, Social interaction
Geographic Terms: China
Abstract: The rise of Generative Artificial Intelligence (GenAI) in postgraduate education has garnered increasing attention, yet it has also sparked debates regarding its capacity to complement human supervisors. Despite the ongoing discussion, the complex interplay of supervisor support and GenAI support on research experiences of postgraduate students remains under-explored. This study aimed to address the gap by employing an explanatory sequential mixed methods design, with the quantitative study conducted with a sample of 1,515 postgraduate students in China to examine the effects of supervisor support and GenAI support on their research experiences. The qualitative study involving interviews with 20 postgraduate students unraveled the nuanced mechanisms underlying the quantitative results. The findings revealed a complementary alliance between supervisor support and GenAI support in fostering postgraduate students' positive research experiences, and the synergistic integration of supervisor-GenAI maximized their complementary strengths, enhancing the depth and quality of support while preserving the irreplaceable value of human interactions rather than diminishing the role of human supervisors. This study contributed to envisioning an educational environment where GenAI and supervisors coexist harmoniously to enrich postgraduate students' research experiences. [ABSTRACT FROM AUTHOR]
Copyright of Studies in Higher Education is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Can GenAI complement supervisor support in shaping postgraduates' research experiences? A mixed-methods approach.
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  Data: <searchLink fieldCode="AR" term="%22Huang%2C+Yating%22">Huang, Yating</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Sihui%22">Li, Sihui</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Zihan%22">Liu, Zihan</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Studies+in+Higher+Education%22">Studies in Higher Education</searchLink>. Apr2026, Vol. 51 Issue 4, p836-854. 19p.
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  Data: <searchLink fieldCode="DE" term="%22Generative+artificial+intelligence%22">Generative artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Mentors%22">Mentors</searchLink><br /><searchLink fieldCode="DE" term="%22Mixed+methods+research%22">Mixed methods research</searchLink><br /><searchLink fieldCode="DE" term="%22Graduate+students%22">Graduate students</searchLink><br /><searchLink fieldCode="DE" term="%22Social+interaction%22">Social interaction</searchLink>
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  Data: The rise of Generative Artificial Intelligence (GenAI) in postgraduate education has garnered increasing attention, yet it has also sparked debates regarding its capacity to complement human supervisors. Despite the ongoing discussion, the complex interplay of supervisor support and GenAI support on research experiences of postgraduate students remains under-explored. This study aimed to address the gap by employing an explanatory sequential mixed methods design, with the quantitative study conducted with a sample of 1,515 postgraduate students in China to examine the effects of supervisor support and GenAI support on their research experiences. The qualitative study involving interviews with 20 postgraduate students unraveled the nuanced mechanisms underlying the quantitative results. The findings revealed a complementary alliance between supervisor support and GenAI support in fostering postgraduate students' positive research experiences, and the synergistic integration of supervisor-GenAI maximized their complementary strengths, enhancing the depth and quality of support while preserving the irreplaceable value of human interactions rather than diminishing the role of human supervisors. This study contributed to envisioning an educational environment where GenAI and supervisors coexist harmoniously to enrich postgraduate students' research experiences. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Studies in Higher Education is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/03075079.2025.2495710
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      – Code: eng
        Text: English
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        Type: general
      – SubjectFull: Mentors
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      – SubjectFull: Mixed methods research
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      – SubjectFull: Graduate students
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      – SubjectFull: Social interaction
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      – SubjectFull: China
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              Text: Apr2026
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