Modeling Affective Learning Behaviours

A data driven learning analytics framework based on users' cognitive and affective learning behaviours

Degree type


Closing date

27 March 2023



Citizenship requirement


About the research project

Engagement can be influenced by different characteristics of individual learners and impacted by the design of the learning activities. This project aims to design and develop a model of student engagement with tertiary-education learning activities. This project focuses on the challenges of collecting, analysing, and interpreting data to improve learner engagement within tertiary subjects, particularly data available within a learning management system that students use throughout a course. A greater understanding of student behaviour with different learning activities may identify mechanisms to improve academic performance.

Engagement can be measured by considering the behavioural, emotional, and cognitive factors that impact the student learning process. This study will also explore the opportunities of advanced multimodal data collection (eg analysing facial expression and/or behaviour patterns during interactions with a learning activity) and the mechanisms to incorporate those collection methods within a learning management system.

This study will investigate what factors lead to learner disengagement with various learning activities and the identification of personalised intervention strategies to improve student performance.

Primary Supervisor

Meet Dr Soonja Yeom


Applicants will be considered for a Research Training Program (RTP) scholarship or Tasmania Graduate Research Scholarship (TGRS) which, if successful, provides:

  • a living allowance stipend of $31,500 per annum (2023 rate, indexed annually) for 3.5 years
  • a relocation allowance of up to $2,000
  • a tuition fees offset covering the cost of tuition fees for up to four years (domestic applicants only)

If successful, international applicants will receive a University of Tasmania Fees Offset for up to four years.

As part of the application process you may indicate if you do not wish to be considered for scholarship funding.


Applicants should review the Higher Degree by Research minimum entry requirements.

Additional eligibility criteria specific to this project/scholarship:

  • Applications are open to Domestic/ International/ Onshore applicants
  • Applications are open to applications from ICT discipline background only
  • English language score must be above minimum entry requirements for this project
  • Applicants must be able to undertake the project on-campus

Selection Criteria

The project is competitively assessed and awarded.  Selection is based on academic merit and suitability to the project as determined by the College.

Additional essential selection criteria specific to this project:

  • Demonstrated capacity in critical thinking
  • Background in subject areas relevant to the project (e.g., ICT, educational theory, AI theory)
  • Programming skills with understanding in data analytics and machine learning.
    Quantitative research skills

Additional desirable selection criteria specific to this project:

  • Good communication skills
  • Interest in learning analytics, tertiary education and online learning

Application process

There is a three-step application process:

  1. Select your project, and check you meet the eligibility and selection criteria;
  2. Contact the Primary Supervisor, Dr Soonja Yeom to discuss your suitability and the project's requirements; and
  3. Submit an application by the closing date listed above.
    • Copy and paste the title of the project from this advertisement into your application. If you don’t correctly do this your application may be rejected.
    • As part of your application, you will be required to submit a covering letter, a CV including 2 x referees and your project research proposal.

Following the application closing date applications will be assessed within the College. Applicants should expect to receive notification of the outcome by email by the advertised outcome date.

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