Educational Research in Engineering and Technology (ERET)

elearning.jpeg The Educational Research in Engineering and Technology (ERET) Research Group performs research in the improvement of educational practices in the subjects of engineering and computer science and eLearning practices.

ERET research focusses on how teaching and learning can be done better within the context of the School's programmes and beyond. Education is a very broad research area and the group's research includes pedagogies, assessment, delivery models, students' perspectives, ethics, equity, inclusion, power relations.

The ERET is primarily from a technological perspective while studying the socio-technical implications of new innovations. The range of study is broad, including algorithmic, systems and pedagogical issues. Current work focuses on Massive Open Online Courses (MOOC), mobile teaching and learning, learning analytics, gamification, and AI in teaching and learning.

Relevant courses at VUW

  • Master’s by Research
  • PhD

Staff with eLearning interests

PhD opportunities

Māori/Pasifika Educational Research

Regarding tools for engaging in Māori/Pasifika 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 Māori/Pasifika material in this area and that eLearning tools (ranging from full courses to individual tools) based on Māori/Pasifika cultural concepts could be created to support and engage this demographic 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 up 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.

Learning 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.


Karsten Lundqvist, Senior Lecturer of Software Engineering at Victoria, has published several papers on the topics of eLearning, Artificial Intelligence in eLearning, socio-technical issues, gamification and Massive Open Online Course (MOOC) teaching and learning.