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Closing the feedback loop

Primary supervisor

Yi-Shan Tsai

Research area

Learning & Analytics

Student satisfaction with feedback is consistently low in higher education, and there is a lack of understanding regarding how students interpret and interact with feedback. Learning analytics promises to enhance feedback practice by providing real-time data and insights into learning behaviour and outcomes, so as to inform educational interventions. However, the feedback loop remains open without an understanding of how students make use of the received feedback or the #sustainability of such feedback practice. As technology-mediated feedback becomes an integral part of learning, there is growing urgency in developing ‘digital feedback literacy’ among learners, understanding how technology shapes feedback pedagogy, and exploring areas where learning and teaching in the digital age can be supported by technology. I am seeking PhD students who are interested in taking inter-disciplinary approaches to exploring the issues above. Example questions to investigate are as follows:

  • How do students make sense of technology-mediated/ data-based feedback and act on it?
  • How can we enhance digital feedback literacy among learners through the development of feedback tools?
  • How can we enhance the understanding of learner engagement with feedback using trace data?
  • How can the understanding of learner interactions with technology-mediated/ data-based feedback inform teaching?
  • How can we improve the effectiveness of data-based feedback using storytelling elements?


Required knowledge

  • Experience in designing and conducting quantitative, qualitative or mixed-method studies
  • Interest in educational research, design-focused research, or ethnographic research.
  • Skills in one or more of the following areas including software development (highly desirable), data mining, data analytics, experimental design, and qualitative research methods.
  • A Master’s degree (research-based), Honours distinction or equivalent with at least above-average grades in computer science, education, psychology, or relevant fields.
  • IELTS 7.0 (overall) and good written and spoken communication skills.

Project funding


Learn more about minimum entry requirements.