New AI research from China combines machine learning methods with questioning to reveal new dimensions in the connections between supervisor-student relationships

New AI research from China combines machine learning methods with questioning to reveal new dimensions in the connections between supervisor-student relationships

The supervisor-student relationship has a profound impact on creativity. A harmonious supervisor-student relationship is a basis for knowledge transfer and innovations, while a poor supervisor-student relationship mitigates the negative effects of the threat of the power stereotype. The researchers designed two studies to explore the emotional mechanism in the supervisor-student relationship. The researchers collected data from 74 East China Normal University graduates and selected 16 participants based on data from their questionnaire aimed at those who reported difficulties in their supervisor-student relationships. The researchers experimented in two phases: three-topic conversation interview (self-introduction topic, supervisor topic, and campus life topic) and a questionnaire evaluation.

In study 1, the researchers used the facial emotion detection method to analyze the emotional characteristics of the recorded video frames. Multi-activity convolutional neural network (MTCNN) and VGG19 neural network were used for facial detection and emotional recognition, respectively. Through this study, the researchers observed that the frequency of negative dynamic performance increased significantly in supervisor argument, and they also identified a distinct negative mood swing during the transition from self-introduction to supervisor argument.

Study 2 investigates the emotional mechanism through which the supervisor-student relationship influences creativity. The student-supervisor relationship is a multidimensional structure influenced by teaching and interpersonal relationships. Hypotheses are proposed to examine the relationships between the supervisor-student relationship, the threat of the stereotype of power, emotional labor and creativity. The researchers used a structural equation model (SEM) to study the connections between the variables. The questionnaire included measurements for supervisor-student relationships, power stereotype threat, emotional labor, and creativity. They collected 592 valid questionnaires from postgraduate students (53.7% male and 46.3% female, aged 21-29). The results revealed that a good student-supervisor ratio reduced the threat of the power stereotype. The threat of the power stereotype affected emotional work, where shallow acting had a negative impact on creativity, while deep acting had a positive effect. These results support the proposed hypotheses.

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To enhance creativity, supervisors should focus on emotional mechanisms, such as the threat of power stereotype, shallow acting, and deep acting. Institutions should strengthen the training and assessment of postgraduate supervisors, while at the same time students should actively engage in reporting and expressing their ideas. The researchers believe that future work should explore causal relationships and consider relevant factors to obtain more accurate results.


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Astha Kumari is a Consulting Intern at MarktechPost. She is currently pursuing the dual degree course in chemical engineering department of Indian Institute of Technology (IIT), Kharagpur. She is passionate about machine learning and artificial intelligence. She is passionate about exploring their real-life applications in various fields.


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