Learning analytics informed course design

Engagement and Retention: Embracing Learning Analytics to Inform Course Design in Australian Higher Education

Degree type

PhD

Closing date

18 July 2022

Campus

Launceston

Citizenship requirement

Domestic/International

About the research project

UTAS has long been catering for regional and remote students through online and blended courses. The current coronavirus (COVID-19) outbreak has seen an even greater development of such course offerings across Australia. However, overall universities have observed higher student attrition rates and disengagement among these student cohorts. There is an urgent need for universities to rethink their course design and support strategies to enhance student engagement and retention. To address this significant issue, this project will use an innovative and comprehensive response, by integrating Garrison, Anderson and Archer’s (2000) Community of Inquiry (CoI) framework and emerging data analytics techniques. It will seek to identify strategies that are currently used in online and blended courses/units to engage and retain students, and develop a support framework for best pedagogical practices to build and foster a Community of Inquiry (CoI), to maximise student engagement and retention.

Primary Supervisor

Meet Dr Frances Fan

Funding

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 $28,854 per annum (2022 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.

Eligibility

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

Additional eligibility criteria specific to this project/scholarship:

  • The applicant is required to have a clear understanding in mix-methods research methodology, skills in using statistical analysis software, e.g. R or Python, and skills in data visualisation

Applicants from the following disciplines are encouraged to apply:

  • Education
  • Computing and Information Technologies
  • Applicants from other disciplines who meet the eligible criteria are also eligible to apply

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.

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 Frances Fan 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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