Academic Profile : Faculty

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Assoc Prof Ring Joyce Pang Shu Min
Associate Dean (Research), College of Humanities, Arts, and Social Sciences
Associate Professor, School of Social Sciences
Director, CLASS, College of Humanities, Arts and Social Sciences
External Links
 
I received my B.A. training in psychology from Smith College, MA, USA, and my PhD in personality psychology from The University of Michigan, MI, USA.

As a personality psychologist, I am broadly interested in the influences of multiple social identities and individual differences on well-being, performance, and health psychology outcomes within different social contexts. In all my research, I adopt a person x situation perspective to understand how individual differences predict different reactions within different social contexts, which in turn lead to important personal and social outcomes.

To this end, I have two major lines of research. First, I am a motivation researcher who develops, validates, and refines methods of assessing implicit motives. In this line of work, I publish and investigate best practices for using the Picture Story Exercise, the most commonly used measure of implicit motives. I have also explored the use of machine learning for automating the laborious content coding process that is involved in scoring implicit motives in text. Second, I investigate how individual differences (such as in motivation and in social identities) can affect performance, interpersonal outcomes, and physiological and emotional changes during motive-relevant contexts. I have explored the intersection between the person and the situation on a wide range of personal and social outcomes such as addictive behaviors, body image, internet radicalization, consumerism, medical adherence, adolescent aggression, and inter-group relations.
* Implicit motives
* Personality assessment
* Gender
* Adolescents
* Health psychology
 
  • CoHASS Seed Funding Grant
  • Investigating the co-occurrence between implicit motives and emotion in naturally occurring texts using a natural language processing and a machine learning approach
  • Towards the development of a machine learning database for implicit motive coding