Karsten Lundqvist

Karsten Lundqvist profile picture

Senior Lecturer School of Engineering and Computer Science

Teaching in 2020


I received my BSc honours degree (2005) and PhD (2010) from University of Reading. I also graduated with a Postgraduate Certificate in Academic Practice (2014) for which I won the David Malvern Portfolio Prize. I am a fellow of the higher education academy (HEA) in the UK.

Research Interests

I find it fascinating to explore how technology and artificial intelligence can be used to improve teaching and learning. Not only in the subject of computer science or at university level, but broadly and often in unusual settings. My research is often interdisciplinary and socio-technical, yet involves improving technological systems and methods to work better with humans.

The following gives examples of current and previous project areas that I have worked on:

MOOCs (Massively Open Online Courses).

I am academic lead on the popular Computer Science MOOCs Begin Programming, which is a collaboration between University of Reading and Victoria University of Wellington. I am using this course as a platform for research
  • Learning analystics to understand common trends within the course and MOOCs in general

  • Studying MOOC pedagogies and how technology can support them

  • Exploring benefits of developing MOOCs

Create and use tools to improve teaching and learning within various cultural settings
  • Games to teach Computer Science to Māori children
  • Use of avatars in gender segregated societies in the Middle East

  • eLearning methods in Iraq

  • Improvements of using smart phones over feature phones for female business women in sub-Saharan Africa.

Use of games and gaming methods in education
  • Learning through designing games

  • Design teaching methods using gaming aspects

Social networking to support formal education
  • Introduced social networking spaces to study how they can aid discovery of common interests amongst students

  • Studied the effect of Facebook, and the active use of Facebook, in higher education

  • Use data mining to support teachers in online courses.

  • Use conversational agents (chatbots) to automate surveys

Improve feedback provision
  • Use of video for rapid feedback and feedforward processes

PhD Ideas

If you would be interested in studying under my supervision then please contact me describing why and what you would like to research. I have a few current areas that I would be especially interested in working on:

Maori/Pacifica eLearning Tools

Tools for engaging in Maori/Pacifica computer science teaching and learning. New Zealand schools are currently being encouraged to teach computer science topics as part of the curriculum. This in itself poses several opportunities and challenges. It is the perception that there is a lack of Maori/Pacifica material in this area and that eLearning tools (ranging from full courses to individual tools) based on Maori/Pacifica cultural concepts could be created support and engage this demography better. The proposed work is to develop these technical approaches and study the impact of introducing these in teaching and learning situations.

Massive Open Online Course Teaching and Learning (MOOC)

MOOCs have recently shaken the world of Higher Education. Courses with thousands of participants run by a small team have become the norm. The eLearning group is also active in this area. However, there are still many unresolved issues in running such courses. The PhD candidate is expected to identify and/or address some of the following areas in this field: Supporting and engaging massive numbers of students online, intelligent tutoring, cultural and socio-technical differences in user experiences, and impact of MOOCs to stake holders.

Learner Analytics and MOOCs

The analysis of MOOC data is non-trivial. It typically consists of utterances and social connections within the MOOC. The research group has access to a large dataset of user interactions from MOOCs and is currently studying approaches to analysing the data to improve understanding of underlying aspects of the interactions within the MOOC. The proposed work is to further this work using statistical and artificial intelligence approaches to analyse these datasets.


Please find my academic publications here.