Primary supervisor

Sadia Nawaz

Co-supervisors

Project Description

Teamwork is a big part of university life, but not all teams work smoothly. Students often face issues such as uneven contributions, unclear communication, or members falling behind. Teaching staff receive a large amount of peer feedback. But the information is often dispersed across multiple reports and can be time-consuming to interpret—particularly in large cohorts. A system that could automatically identify which teams are struggling, and why, would allow educators to offer timely, targeted support.

This project aims to design and develop a working prototype dashboard that analyses peer-feedback data and converts it into meaningful, easy-to-understand insights. The dashboard will highlight teams that may require additional support, identify common patterns of teamwork challenges, and present these findings through clear visualisations for teaching staff.

This is a hands-on, technically focused project. Students will design system components, build machine learning and NLP/LLM models to analyse feedback data, develop data-processing pipelines, and create an interactive visual dashboard. While a brief literature review will help inform the design, the primary goal is to build a functional prototype with real-world application in Monash learning environments.

Student Cohort

If you love programming, enjoy building real systems, and are excited by AI, teamwork analytics, or educational innovation—this project is for you!

Single Semester: No
Double Semester: Yes

How to Apply

Interested students are encouraged to reach out via email to express their interest in the project. When contacting the supervisor, please include:

  • A brief statement outlining why you are interested in the project
  • Your CV
  • Your academic transcripts
  • Any additional evidence of relevant technical experience (e.g., GitHub, past projects)

Early contact is recommended, as places may be limited.

Aim/outline

This project has the following goals:

- Conduct a short literature review to understand teamwork analytics and dashboard approaches.
- Design and build the data-processing pipeline for peer feedback.
- Develop ML/NLP models to detect teamwork challenges.
- Create a functional prototype dashboard with interactive visualisations.
- Apply human-centred design principles to improve usability.
- Demonstrate and evaluate the final working system.

URLs/references

  • AI-Driven Contribution Evaluation and Conflict Resolution: A Framework & Design for Group Workload Investigation.
    Link: 
    https://arxiv.org/html/2511.07667v1
     
  • Teammates Stabilize over Time in How They Evaluate Their Team Experiences
    Link:
    https://dl.acm.org/doi/abs/10.1145/3506860.3506891
     
  • Supporting Equitable Team Experiences Using Tandem, an Online Assessment and Learning Tool
    Link:
    https://peer.asee.org/supporting-equitable-team-experiences-using-tandem-an-online-assessment-and-learning-tool
     
  • Team Development Tools
    Link:
    https://caen.engin.umich.edu/tools/team-development-tools/

Required knowledge

It's a team project. The students should have the following background:

- Strong programming skills (Python required; ML frameworks like PyTorch, TensorFlow, scikit-learn).
- Experience with machine learning, NLP, and ideally LLMs.
- System development skills such as backend/API development, pipeline building, and database design.
- Front-end/dashboard development experience.
- An interest in UI/UX or willingness to learn basic human-centred design.
- Prior research experience is a bonus but not essential.