What is the true scope of learning analytics? Which part of the institution should be involved? How are they connected. A-LASI workshop co-presented with Phil Renner
APM Welcome, APM North West Network Conference, Synergies Across Sectors
Multidimensional Learning Analytics
1. Multidimensional Learning Analytics
Australian Learning Analytics Summer Institute
Macquarie University, 7 Dec 2013
Phil Renner. Counselling and Psychological Services
Abelardo Pardo. School of Elec. and Information Eng.
Slideshare.com/abelardo_pardo
4. Bridges
DATA
ACTIONS
F H Mira flickr.com
Observations
Reminders
Interviews
Counselling
Forms
SMS
Electronic Event
Academic
advise
Surveys
Associations
Attendance
Recommend
Enrollment
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6. Technology mediated activities
Technology mediated
activities
Collect events and evidence
Suitable for individual and
team activities
Correlates with engagement
See how they learn
Massive data collection
What to do with the data?
Unhindered by talent flickr.com
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7. Data-driven design of learning tasks
Learning tasks are
designed to collect data
Data is used to shape the
design of tasks
Students receive prompt
feedback
Tutors have a
comprehensive view of
the learning environment
Sustained refinement
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9. Example: Flipped classroom
Prepare class with online
material + tasks
(measure engagement)
Devote face-to-face time to
Interactive tasks
Cedrics pics flickr.com
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10. Engagement with previous tasks
Estimation of engagement
with previous tasks allows
tailoring face-2-face tasks
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11. Reactions within the course
New tasks
Special material
Extra readings
Gwen flickr.com
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12. Personal problems
Problems adapting to uni
Social integration
Poor time management
Coping with change
Handling pressure
Robert L Huffstutter flickr.com
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13. Refinement of academic structures
Skill coverage in a program
Unaddressed requirements between units
Scheduling conflicts
Infrastructure improvement (IT, spaces, etc.)
Optimal resource allocation
Target specific deficiencies
Accreditation
Quality control
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16. Challenges to Engaged Learning
Expectations
Institutional expectations
Students as autonomous
learners
Student expectations
›one-on-one attention
›rapid feedback
›comments on drafts
Staff challenges & expectations
›‘passive learners’
› time poor
› equity of treatment
17. Elements and bridges
strategies- eg
Flipped
learning
Bridges: not increasing
engagement?: REFER
Teaching
Instruction
Student
Support
Services eg
CAPS,LC
Explore & Address:
Other Possible Scaffolds
-eg Peer academic
mentoring
Academic
Structure
Academic skills deficits
Financial issues
Mental health concerns
Developmental lags
(autonomy and sense of
agency)
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21. Bridging : Peer academic mentoring?
Why Peer mentoring?
› Students expectations unlikely to
change with staff information (“yes
yes, yes, No!”)
› Student pay attention to other
student’s experience – role model
for adopting new strategies
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24. Learner: readiness/handicaps?
What factors make a good learner?
› Ability?
› Commitment to study (e.g. vs work) ?
› Time management skills?
› Accelerated learning and emotional development
?
› Emotional development - personal and social
competencies ?
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25. CAPS interventions - Learner Types?
• Bored, gifted
• Perfectionistic
• Capable but poor self-management
(eg need remedial time management skills, address
procrastination)
• Students needing to develop sense of agency and ownership of their
academic experience
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