Education, and Educational and Assistive Technology

A list of potential topics for PhD students in the area of Education, and Educational and Assistive Technology.

Using AI and Machine Learning to study Fairness in Education 

Supervisor:  Kobi Gal

Education is increasingly mediated by technology, and is used by a wide array of learners from different age groups, socio-economic backgrounds and cultures. This provides new opportunities for Artificial Intelligence  to support students in their learning process,  and teachers and researchers in their understanding of how students learn.  This project will study the role of ethics and fairness in the design of AI systems in educational domains, from online forums to Massive Open Online Courses (MOOCs). The project will combine AI and machine learning to study the following research problems: Modelling and reasoning about fairness and bias in educational technology; how analytics methods can produce, or reduce,  social inequities in  education;  the design of fair and interpretable algorithms for sequencing educational content to students.  


Understanding how different structures of first year support students in computer science

Supervisor:  Fiona McNeill

Description: First year is a challenging time in any subject but especially in CS, where students’ CS background ranges from highly experienced to complete novices.  There is evidence that this can create a difficult environment for students, and particularly those from widening participation backgrounds and groups that can be marginalised in computing such as women.  This project focussed on exploring different ways first year can be structured - in Scotland, across the UK and beyond, and working both with data on completion rates and other salient factors and with different groups of students to understand their experiences.  There has been particular success at including marginalised groups in some US universities, and the project could include looking more deeply into how that has been achieved and how any lessons from that could translate into the Scottish/UK university system. 


What is going on with computing in schools: understanding how young people are making their subjects choices in schools and why CS uptake is dropping

Supervisor: Fiona McNeill

Description: The number of young people taking CS in schools in Scotland has been dropping - with levels now only around 35% of where they were in 2000.  This is problem because of the skills gap in the job market and because of the loss of opportunity to young people.  But the cause of the problem is not well understood.  This project will look into this issue from various angles: for example, analysing existing data, working closely with young people in schools across Scotland to understand how they are making their choices and what their views of CS are, and looking at initiatives to increase uptake of CS that have been successful in other countries.


Effective interventions to support diversity in CS education

Supervisor: Fiona McNeill

Description: There is a significant lack of diversity in CS education, with around 20% of CS undergraduates being female, and other axis of exclusion such as some ethnicities and young people from widening participation backgrounds.  This project will explore different initiatives to counterbalance this from around the world and explore their efficacy and the costs and benefits of implementing them.  It will involve devising an implementable intervention, taking into account constraints on implementation, measure its efficacy and use this to develop a plan for CS education that is more equitable.