Transcript The Learning Genome Introduction - Wiki

The Learning Genome
Mauricio Marrone Burgoa, Jamie Gabriel, Maree Gosper, Gary Lau, Vanessa Warren
Innovation & Scholarship Program Grant
Introduction
Aims
Figure 1. Data Never Sleeps
Is there a Learning Genome?
•To empower and inform staff of the ways
to use smart-data to inform their teaching
Are there a set of factors we can point to
which are clear indicators of student
success?
•To illustrate the kinds of data that can be
made available to revolutionize teaching at
this university
Can these be found amongst the sea of data
we collect about our students?
•To empower students with knowledge
and information to make informed
decisions that will open opportunities and
maximise their learning
Can these be used to recommend customised
pathways of success for our students?
.
•Substantially improve the learning
opportunities and educational results of our
students at Macquarie
How can they be used to enhance learning
design, teaching and the student experience?
The purpose of this project is to apply
techniques and technologies to open
opportunities and enrich the learning of our
students. We want to find out if, based on
the data we have about our students, we can
make suggestions (or recommendations) as
to what actions the University should take
and students should do to become the best
they can be.
•Provide students, academics and academic
advisors with knowledge and information to
make informed decisions that will open
opportunities for students to maximise their
learning.
Figure 2. Companies that use Recommended Algorithms
Expected Outcomes/Progress
Approach
Technical
- to explore analytical
approaches, accessing and interrogating
both structured and unstructured datasets.
Working with MQ analytics to update
knowledge of state of the art techniques,
developing the skills and protocols to
aggregate and interrogate data and
undertaking data analysis are within this
stream.
Educational
interpretation
and
implication – to explore the possible
interpretations of the data, their application
and the short and long term issues and
implications that will emerge are the focus
of this stream. This will encompass a
literature review to identify current
practice, identification of ethical issues,
focus groups of stakeholders to review
findings and explore implications.
Establishment of a community of practice
– to develop networks within and outside
Macquarie. Learning analytics is attracting
enormous interest at the moment and it is
essential that we are part of the wider
community of practice.
• Identification of algorithms to achieve
associative and analytical outcomes
• An understanding of the issues and
implication (both technical and ethical)
related to the handling of large teaching
• An understanding of how the findings can
be used to open opportunities and
enhance the student experience
• Establishment of
practice within
Macquarie
a community
and external
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of
to
• Exploratory models for mining and
interpreting data which will be useful for
both MQ Analytics and the wider higher
education community
• Scholarly outputs in the form of
academic
papers
and
conference
presentations
• An ongoing agenda for the development
of learning analytics at Macquarie
Acknowledgements
This project is funded through the Innovation and
Scholarship Program, Macquarie University.
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www.mq.edu.au/educationstudio