Teaching Opportunity: Exploring the Future of Economics: AI Integration, Bayesian Methods, and Impact Evaluation

June 15-26

Cape Coast, Ghana

Full Programme Details

Apply by April 8

Partner

Professors Without Borders, a UK-based charity, is in our second year of a partnership with the University of Cape Coast, Ghana. The current programme would be hosted by the Department of Data Science and Economic Policy, which is part of the School of Economics under the college of humanities and legal studies.

Qualifications

The ideal candidate will have a PhD or be enrolled in a PhD programme related to Economics and/or Generative AI. They should have a dynamic personality and love of teaching, with at least 5 years of classroom teaching experience at the tertiary level.

Participants

Faculty and Staff
Economics and Data Science Postgraduates

Accommodation & Logistics

Flights, Travel Insurance, and Visa (where applicable) will be provided by Professors Without Borders
Accommodation, Meals, and Local Transportation will be provided by UCC

Programme Focus

1. AI Integration and Adoption into Academic Workflow

This training programme aims to promote the systematic adoption of Artificial Intelligence in academic and research practices for both graduate students and faculty.

Graduate students will learn:

How to apply AI Technologies responsibly and ethically
Techniques in advanced prompt engineering tailored for academic research
Methods to identify and address AI Hallucinations and algorithmic bias
Strategies to establish reproducible research workflows using AI Tools

Faculty will learn:

Using intelligent platforms to content generation to streamline teaching material preparation and organization
Implementing adaptive learning systems to personalized education for students with diverse abilities
Utilizing automated assessment platforms to improve grading efficiency and feedback quality
Leveraging AI-supported solutions for research and academic writing assistance
Applying Natural Language Processing (NLP) technologies to enhance both academic and administrative tasks

2. Application of Bayesian Network Analysis in Economics

Participants will gain hands-on experience in advanced Bayesian Network Modelling Techniques relevant to both faculty and students. The core learning outcomes include:

Analysing discrete economic phenomena using Multinomial Bayesian Networks
Modelling and interpreting continuous economic data through Gaussian Bayesian Networks
Applying Dynamic Bayesian Networks for time series analysis of economic trends

The focus will be on leveraging these methods for real-world economic modelling and policy evaluation.

3. Impact Evaluation in Economics

Participants will develop practical skills in conducting rigorous impact evaluation within the field of economics. Key learning outcomes include:

Calculating statistical power and determining appropriate sample sizes for studies
Designing and implementing Randomised Control Trials (RCTs) for evaluatory economic intervention
Applying essential impact evaluation methodologies, such as:
- Propensity Score Matching (PSM) for constructing comparable treatment and control groups
- Difference-in-Differences (DiD) for measuring changes over time between groups
- Regression Discontinuity Design (RDD) to estimate casual effects at specific thresholds

Application Process

Please complete our application form by Wednesday April 8. As part of this, you will be required to submit a cover letter and CV. The cover letter is a very important indication of your seriousness about this programme and will be considered greatly. It should be written primarily by yourself without the dominant contribution coming from AI tools, which are easily recognizable to the reader. It should address your commitment to SDG #4–the delivery of Quality Education–and the skills and attributes you can contribute to this programme.

If shortlisted, you will be invited to complete a situational judgement test to assess your approach to safeguarding, followed by an interview with our Co-Heads of Programmes to discuss teaching ideas for the programme and your pedagogical approach.

If your browser is blocking pop-ups and preventing the form from loading, you can complete the application process directly using this link.