[on behalf of Hassan Khosravi]
Dear All,
The School of Information Technology and Electrical Engineering (ITEE) at
The University of Queensland (UQ) would like to invite applications for a
PhD position in Educational Data Mining. The project is financed through a
UQ Alliance PhD stipend together with the Technical University of
Denmark (DTU). Ranked in the world's top 50, UQ is one of Australia's
leading research and teaching institutions. UQ's School of ITEE is at the
leading-edge of information and communications technology. With a
reputation for teaching excellence and expert research, our students,
graduates, teachers and researchers are revolutionising technology to solve
the world's greatest challenges.
*Project Description*Adaptive learning is one of the most prominent
techniques for providing an efficient, effective, and customised learning
experience for students. Adaptive learning platforms dynamically adjust the
level or type of instruction based on individual student abilities or
preferences. Adaptive learning platforms commonly model learners solely
based on their knowledge state, ignoring the cognitive and emotional state
of leaners, which have been proven to have a critical role in learning.
This is mostly due to limitations in current learning technologies as they
have no direct way to assess learners’ cognitive and emotional state.
In recent years, neuro-physiological methods and tools have been used for
measurement of user’s cognitive load and emotional processes. For example,
eye tracking technologies or heart rate variability devices have been used
for detection of a variety of reactions and emotions such as
satisfaction, sadness, mind wandering, stress and frustration.
Neuro-physiological tools are increasingly becoming more reliable, portable
and affordable, thus providing a potential avenue for adoption in many new
domains and applications, offering new research opportunities. In this
project, we seek to utilise neuro-physiological tools for development of a
neuro-adaptive learning platform.
* The project aims to:*
- develop neuro-enhanced learner models for use in adaptive learning
platforms that can simultaneously capture the knowledge state and cognitive
state of learners.
- develop recommender systems that can use neuro-enhanced learner models
for recommending learning activities best tailored to the needs of each
learner.
*Requirements*Students with a strong background in computer science or
information systems with a desire to work in transdisciplinary teams will
be best suited for the project. Preference will be given to candidates who
can provide evidence of the following:
- Experience in designing and conducting quantitative, qualitative or
mixed-method studies.
- Familiarity with one or more of the following areas:
- educational theory, instructional design, learning sciences
- machine learning, data mining, learning analytics, recommendation
systems
- cognitive science, psychology, human computer interaction (HCI),
user-centred design
As part of this project the PhD candidate will closely collaborate with the
PhD candidate recruited at DTU. A research stay of 6 month at the partner
university is planned for the PhD candidates both at DTU and UQ resulting
in a period of co-location of at least 12 months.
*Remuneration*
The stipend is equivalent to the APA rate, $ 27,082 per annum (2018 rate,
indexed annually). The scholarship will be for three (3) years with the
possibility of a six (6)- month extension. Continuation of the scholarship
is dependent on the candidate remaining in good standing according to the
UQ PhD program rules. The scholarship is available to both domestic and
international students. For the candidates who have been successful in
obtaining any government-funded scholarship or UQ-funded scholarship or any
other external scholarship, a top-up scholarship may be awarded.
*Application*To apply for the position please visit http://jobs.uq.edu.au/
caw/en/job/504522/phd-scholarship-in-data-science-
and-educational-data-mining
To discuss this role and for further information, please contact Dr Hassan
Khosravi (h.khosravi@xxxxxxxxx) and Professor Shazia Sadiq (
shazia@xxxxxxxxxxxxxx).
Thanks,
Hassan
------------------------------------
Dr Hassan Khosravi, SFHEA
Senior Lecturer in Learning Analytics
Institute for Teaching and Learning Innovation and
School of Information Technology and Electrical Engineering
Room 315, Building #17 | The University of Queensland | QLD 4072 | Australia
telephone: +61 7 3346 0774 | email: h.khosravi@xxxxxxxxx | web:
hassan-khosravi.net