Educational Research in Engineering and Technology (ERET)

elearning.jpegThe 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 focuses on how teaching and learning can be done better within the context of technology, engineering programmes and beyond. It is an interdisciplinary group with members from several schools and units. 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, Virtual Reality in education, and AI in teaching and learning.

Relevant courses at VUW

  • Master’s by Research
  • PhD

Research themes and PhD opportunities

The group is researching various aspects of teaching and learning. The themes include.

Distance Learning

The number of distance learning degrees has increased dramatically over the last decade. Yet, despite this increase, teaching IT courses online remains challenging. Due to the COVID-19 pandemic, distance learning and active practices to engage online learners are now centre-focused in educational institutions' everyday praxis. Tertiary educators have often struggled during enforced lockdowns to convert courses from face-to-face delivery to pure online delivery. This change has presented challenges in curriculum development as academics strive to achieve best practices. It is also a challenge to design a pedagogically sound and engaging course for diverse students from a broad spectrum of educational backgrounds. Online classes often require unique infrastructures such as devices with specific tools or hardware requirements.

Research interests:
  1. Innovative ways of designing engaging courses for online delivery.
  2. The impact of the used online pedagogical model on retention, completion, and success rates.
  3. Comparative analysis of current and various pedagogical models used in distance learning is also a priority.

Artificial Intelligence in Education and Learner Analytics

Artificial Intelligence has been used for adaptive tutoring, tailoring the delivery of content to the student's needs and context. The increasing power applied to deep learning and language generation now provides an opportunity and a challenge. With AI-assisted programming and text generation, what we teach and how we assess students needs to adapt.

Online teaching and learning produce a large amount of data. By using data mining techniques (such as statistics, AI, visualizations) through learning analytics, learners and teachers have opportunities to improve how they learn and teach. The group has used learning analytics from Massive Open Online Courses and educational data from traditional university courses developing visualizations, recommender systems, natural language processes to improve learning.

Game-based Learning and Gamification

Games and techniques “borrowed” from games (gamification) can be used to inspire and engage learners. Games can often help learners to view situations and material from a non-traditional point of view. These techniques have been studied within the research group in several ways, including using games to teach computational thinking through cultural (Māori) games, introducing engineering ethics dilemmas, and through game-based assessments.

Cross-cultural Engineering and Computer Science Education

Educational Tools

We are interested in the use and development of software tools that help both educators and learners in their teaching/learning journey, including educational programming interfaces and languages, pedagogical metric tools, code assistants, and automated assessment systems. Different tools may best support undergraduates, young children, working non-programmers, or professional programmers enhancing particular skills, and some apply to learning broadly across disciplines. We are active across the full range of tool varieties and learners, from guiding assistants for learning to write secure or performant code as an undergraduate or professional to visual programming interfaces for children, and from educational programming languages for novices to live visualisation tools for tracking students' performance in a MOOC.

Research Interests:
  1. The development of software tools to support distance learning educators and learners (i.e. visualisation, meeting/conferencing, assessment, privacy-preserving, etc.).
  2. The development of software tools, techniques and methods to support software developers writing code (i.e. usability, security, etc.)
  3. Analysing existing educational tools for programming, and tools used for programming education, to establish the most effective aspects incorporated within.

Staff involved in the research group

  •  Jimmi Rosa profile picture

    Jimmi Rosa

    Teaching Fellow School of Engineering and Computer Science

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