Primary supervisor

Ee Hui Lim

Feedback is central to student learning, but feedback does not automatically lead to improvement. Students need opportunities to understand, evaluate, and act on feedback, while teachers and teaching teams need to design feedback practices that are clear, actionable, timely, and connected to learning activities.

This project will investigate how feedback practices mature over time within a university unit. The student will analyse teacher-written feedback, Moodle activity data, and SETU feedback across multiple semesters to examine how feedback practices, student engagement, and student perceptions change over time. The project will also examine how feedback-to-action practices were progressively embedded in the unit, including regular feedback activities, visible teaching-team responses, and reflective opportunities for students. Where available and appropriate, the project may also draw on supplementary perception data from analytics-informed feedback tools. 

The expected outcome is a proposed model describing how a unit may move from one-way feedback provision toward more actionable, dialogic, student-centred, and evidence-informed feedback processes. The findings may help educators design feedback practices that better support students in turning feedback into action.t analysis, learning analytics, or natural language processing methods.

Access to unit-level learning data will be subject to relevant ethics approval, data governance requirements, and appropriate de-identification.

Aim/outline

This project aims to develop a feedback literacy maturity model by analysing how feedback practices, student engagement, and student perceptions evolve across multiple semesters.

The project will address three main questions:

  1. How does teacher-written feedback to students change across semesters?
  2. How do student engagement and perceptions, as reflected in Moodle and SETU data, change as feedback-to-action practices are embedded in the unit?
  3. What stages might describe the development of feedback literacy maturity at the unit or teaching-team level?

The student will analyse teacher-written feedback provided to students across multiple semesters. The analysis may examine features such as clarity, specificity, actionability, tone, reference to assessment criteria, learner-centredness, and opportunities for student reflection or follow-up action.

The student may also analyse Moodle activity data and SETU responses to examine student engagement and perceptions over time. Where appropriate, supplementary perception data from analytics-informed feedback tools may be considered, but the project will remain focused on unit-level feedback practice rather than tool evaluation.

The project may involve:

  • Reviewing literature on student feedback literacy, teacher feedback literacy, feedback quality, and feedback design.
  • Developing or adapting a coding framework for analysing teacher-written feedback.
  • Analysing changes in feedback quality and feedback design across semesters.
  • Examining Moodle and SETU data to identify changes in student engagement and perceptions.
  • Mapping how feedback-to-action activities were embedded into the unit over time.
  • Developing a proposed maturity model that describes stages of feedback practice at the unit or teaching-team level.

The project can be adapted to the student’s background. A student with qualitative research interests may focus on coding and interpreting teacher feedback and SETU comments. A student with technical interests may extend the project using text analysis, learning analytics, or natural language processing methods.

 

URLs/references

Carless, D., & Boud, D. (2018). The development of student feedback literacy: Enabling uptake of feedback. Assessment & Evaluation in Higher Education, 43(8), 1315–1325. https://doi.org/10.1080/02602938.2018.1463354

Carless, D., & Winstone, N. (2023). Teacher feedback literacy and its interplay with student feedback literacy. Teaching in Higher Education, 28(1), 150–163. https://doi.org/10.1080/13562517.2020.1782372

Henderson, M., Phillips, M., Ryan, T., Boud, D., Dawson, P., Molloy, E., & Mahoney, P. (2019). Conditions that enable effective feedback. Higher Education Research & Development, 38(7), 1401–1416. https://doi.org/10.1080/07294360.2019.1657807

Ryan, T., Henderson, M., Ryan, K., & Kennedy, G. (2023). Identifying the components of effective learner-centred feedback information. Teaching in Higher Education, 28(7), 1565–1582. https://doi.org/10.1080/13562517.2021.1913723

Required knowledge

This project is suitable for students interested in educational technology, feedback, learning analytics, human-centred computing, natural language processing, or data-driven educational research.

Recommended knowledge:

  • Qualitative or quantitative data analysis skills.
  • Interest in education, feedback, and student learning.
  • Programming or data analysis experience in Python or R.
  • Experience with text analysis, natural language processing, or machine learning.
  • Willingness to work with educational data ethically and carefully.