10 October 2022
About the research project
Higher Education is transforming with advancement of internet technologies and globalisation. Students are becoming more diverse, heterogeneous and large. The traditional way of university teaching which one teaching material for all cannot work and currently making several students dissatisfied. Due to increase in the competition from online courses such as MooCs, it is becoming more and more important for higher education institutions to provide their students a good learning experience. They need to increase student retention and make them engaged. Moreover, they have to deal with limited resources and thus making personalised education which an individual student will look for an impossiblity.
Due to these challenges, big data analytics have been seen as a solution. We have technology and access to more data about each student than before. Thus, if one can process this large data and generate insights, the education personalisation is not an unreachable goal. The sentimental analysis, data mining, machine learning and recommendation systems are already helping in areas such as Medical care system. The aim of this project is to investigate BigData analytical models and techniques for personalised learning among students and improve education processes to support it.
Primary SupervisorMeet Dr Saurabh Garg
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.
Applicants should review the Higher Degree by Research minimum entry requirements.
Additional eligibility criteria specific to this project/scholarship:
- Applicants must be able to undertake the project on-campus
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:
- The applicant should be good in data analytics, machine learning and programming
Additional desirable selection criteria specific to this project:
- Have some education research background
There is a three-step application process:
- Select your project, and check you meet the eligibility and selection criteria;
- Contact the Primary Supervisor, Dr Saurabh Garg to discuss your suitability and the project's requirements; and
- 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.