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Journal of Social Computing 2023, 4(1): 30-45 https://doi.org/10.23919/JSC.2023.0005
Open Access | Issue | Published: 30 March 2023

Emotional Mechanisms in Supervisor-Student Relationship: Evidence from Machine Learning and Investigation

Show Author's Information Jingyi Hu1,  Yaxuan Liu2,  Qijian Zheng3,  Feng Liu4( )
Faculty of Economics and Management, East China Normal University, Shanghai 200062, China
Faculty of Education, East China Normal University, Shanghai 200062, China
School of Computer Science and Technology, East China Normal University, Shanghai 200062, China
School of Computer Science, East China Normal University, Shanghai 200062, China, and also with School of Internet of Things Engineering, Wuxi University, Wuxi 210044, China
Keywords:
machine learning, supervisor-student relationship, power stereotype threat, emotional labor, computable perception
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Hu J, Liu Y, Zheng Q, et al. Emotional Mechanisms in Supervisor-Student Relationship: Evidence from Machine Learning and Investigation. Journal of Social Computing, 2023, 4(1): 30-45. https://doi.org/10.23919/JSC.2023.0005
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Abstract Full text About this article

How to cultivate innovative talents has become an important educational issue nowadays. In China’s long-term mentorship education environment, supervisor-student relationship often affects students’ creativity. From the perspective of students’ psychology, we explore the influence mechanism of supervisor-student relationship on creativity by machine learning and questionnaire survey. In Study 1, based on video interviews with 16 postgraduate students, we use the machine learning method to analyze the emotional states exhibited by the postgraduate students in the videos when associating them with the supervisor-student interaction scenario, finding that students have negative emotions in bad supervisor-student relationship. Subsequently, we further explore the impact of supervisor-student relationship on postgraduate students’ development in supervisor-student interaction scenarios at the affective level. In Study 2, a questionnaire survey is conducted to explore the relationship between relevant variables, finding that a good supervisor-student relationship can significantly reduce power stereotype threat, decrease emotional labor surface behaviors, and promote creativity expression. The above results theoretically reveal the internal psychological processes by which supervisor-student relationship affects creativity, and have important implications for reducing emotional labor and enhancing creativity expression of postgraduate students.


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About this article

Emotional Mechanisms in Supervisor-Student Relationship: Evidence from Machine Learning and Investigation

Show Author's information Jingyi Hu1, Yaxuan Liu2, Qijian Zheng3, Feng Liu4( )
Faculty of Economics and Management, East China Normal University, Shanghai 200062, China
Faculty of Education, East China Normal University, Shanghai 200062, China
School of Computer Science and Technology, East China Normal University, Shanghai 200062, China
School of Computer Science, East China Normal University, Shanghai 200062, China, and also with School of Internet of Things Engineering, Wuxi University, Wuxi 210044, China

Abstract

How to cultivate innovative talents has become an important educational issue nowadays. In China’s long-term mentorship education environment, supervisor-student relationship often affects students’ creativity. From the perspective of students’ psychology, we explore the influence mechanism of supervisor-student relationship on creativity by machine learning and questionnaire survey. In Study 1, based on video interviews with 16 postgraduate students, we use the machine learning method to analyze the emotional states exhibited by the postgraduate students in the videos when associating them with the supervisor-student interaction scenario, finding that students have negative emotions in bad supervisor-student relationship. Subsequently, we further explore the impact of supervisor-student relationship on postgraduate students’ development in supervisor-student interaction scenarios at the affective level. In Study 2, a questionnaire survey is conducted to explore the relationship between relevant variables, finding that a good supervisor-student relationship can significantly reduce power stereotype threat, decrease emotional labor surface behaviors, and promote creativity expression. The above results theoretically reveal the internal psychological processes by which supervisor-student relationship affects creativity, and have important implications for reducing emotional labor and enhancing creativity expression of postgraduate students.

Keywords: machine learning, supervisor-student relationship, power stereotype threat, emotional labor, computable perception

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Received: 05 March 2023
Revised: 29 May 2023
Accepted: 02 June 2023
Published: 30 March 2023
Issue date: March 2023

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