Abelardo Pardo presented on increasing student engagement through personalized feedback. He discussed how simple information transfer is not effective for learning and that active learning techniques that engage students are better. Personalized feedback was identified as one of the most effective ways to improve student outcomes. If designed well, with frequent, timely, and targeted feedback, engagement and achievement can be increased. Pardo concluded that embracing instructional design principles, understanding student approaches, and using data to provide personalized situated feedback can strongly benefit learning.
Increasing Student Engagement with Personalised Feedback
1. Abelardo Pardo (@abelardopardo)
Faculty of Engineering and IT
slideshare.net/abelardo_pardo
Increasing Student Engagement
with Personalised Feedback
IkhlasulAmalflickr.com
Education Grand Rounds
Westmead Hospital Education Centre
8/May/2017
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Simple information transfer is not working
Mazur, E. (2009). Farewell, lecture. Science, 323(5910), 50-51.
Krugazorflickr.com
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Student
Engagement
and
Feedback
Design for
Engagement
Examples
theilrflickr.com
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Student
Engagement
and
Feedback
theilrflickr.com
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“… robust correlations between student
involvement in a subset of ‘educationally
purposive activities’, and positive outcomes of
student success and development, including
satisfaction, persistence, academic achievement
and social engagement”
Trowler, V. (2010). Student engagement literature review. York, UK: The Higher Education Academy.
shuaGandersonflickr.com
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Bonwell, C. C., & Eison, J. A. (1991). Active Learning: Creating Excitement in the Classroom ASHEERIC Higher Education Report No. 1.
Washington, DC, USA: George Washington University.
Active
Learning
Any instructional method
that engages students in the
learning process.
Active learning requires
students to do meaningful
learning activities and think
about what they are doing.
WolfVisionGmbHflickr.com
8. Abelardo Pardo Increasing Student Engagement With Personalised Feedback
If you could choose one…
• More than 500 meta-analyses
of student achievements
• 100 factors with potential
influence
• Feedback in top five
• (74 meta-analyses) Most
effective form: video, audio,
computer-assisted
instructional feedback, and/or
related goals
8
Hattie, J. (2008). Visible learning: A synthesis of over 800 meta-analyses related to achievement. New York: Routledge.
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Boud, D., & Molloy, E. (Eds.). (2013). Feedback in Higher and Professional Education: Understanding it and doing it well. London
and New York: Routledge.
FarukAteşflickr.com
“Feedback is a process whereby learners obtain information about
their work in order to appreciate the similarities and differences
between the appropriate standards for any given work, and the
qualities of the work itself, in order to generate improved work”
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Black, P., & Wiliam, D. (1998). Assessment and Classroom Learning. Assessment in Education: Principles, Policy & Practice, 5(1),
7-74. doi:10.1080/0969595980050102
GarethChristopherflickr.com
Innovations designed to strengthen the frequent
feedback that students receive about their
learning yield substantial learning gains
11. Abelardo Pardo Increasing Student Engagement With Personalised Feedback
Effective feedback…
1. encourages contact between student and
instructors
2. develops reciprocity and cooperation
among students
3. uses active learning techniques
4. is given promptly
5. emphasizes time on task
6. communicates high expectations
7. respects diverse talents and ways of
learning
11
Chickering, A. W., & Gamson, Z. F. (1987). Seven principles for good practice in undergraduate education. American Association
for Higher Education Bulletin, 39, 3-7.
Chickering, A. W., & Ehrmann, S. C. (1996). Implementing the seven principles: Technology as lever. American Association for
Higher Education Bulletin, 49, 3-6.
KevinO'Maraflickr.com
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Hattie, J., & Timperley, H. (2007). The Power of Feedback. Review of Educational Research, 77(1), 81-112.
doi:10.3102/003465430298487
Feedback Levels
1. Task Level (understanding, performance)
2. Process Level (what to do to understand, perform)
3. Self-regulation level (detecting and directing effort)
4. Self level (personal evaluation and affect)
FabienCAMBIflickr.com
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Hounsell, D. (2007). Toward more sustainable feedback to students. In D. Boud & N. Falchikov (Eds.), Rethinking Assessment in
Higher Education: Learning for the Longer Term. London and New York: Routledge.
Perceived as an administrative chore
instead of a pedagogical necessity
MarcinWicharyflickr.com
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Student
Engagement
and
Feedback
Design for
Engagement
theilrflickr.com
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“… teaching in higher education will
necessarily shift the balance of its efforts
towards a greater investment in design
as a way of coping with otherwise
intolerable pressures on staff and
resources.”
Goodyear, P. (2015). Teaching as Design. HERDSA Review of Higher Education, 2, 27-50.
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"There is no such thing as a neutral design"
JeremyBrooksflickr.com
Thaler, R. H., & Sunstein, C. R. (2008). Nudge. Great Britain: Yale University Press.
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Thaler, R. H., & Sunstein, C. R. (2008). Nudge. Great Britain: Yale University Press.
“People make good choices in contexts in
which they have experience, good
information, and prompt feedback"
DerekBruffflickr.com
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Bjork, R. A., Dunlosky, J., & Kornell, N. (2013). Self-regulated learning: beliefs, techniques, and illusions. Annu Rev Psychol, 64,
417-444. doi:10.1146/annurev-psych-113011-143823
ChristianWeidingerflickr.com
We, as learners…
• May not know how to promote
comprehension, retention, transfer.
• May not assess properly our own
learning
• May be biased when judging our
learning
• May rely too much on social beliefs
• Should become “adaptive learners”
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Students are less likely to
engage in pre-class activities if
they are not interactive, do not
provide formative feedback,
and not coherently linked with
the face-to-face activities
O'Flaherty, J., & Phillips, C. (2015). The use of flipped classrooms in higher education: A scoping review. The Internet and Higher
Education, 25, 85-95. doi:10.1016/j.iheduc.2015.02.002
DanKlimkeflickr.com
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Beware of technology pushing
learners away from rational thinking
JenRflickr.com
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“38 meta-analyses investigating 105 correlates of achievement, based on
3,330 effect sizes from almost 2 million students”
Schneider, M., & Preckel, F. (2017). Variables Associated With Achievement in Higher Education: A Systematic Review of Meta-
Analyses. Psychological Bulletin. doi:10.1037/bul0000098
• The effectivity of courses is strongly related to what teachers do.
• The effectivity of teaching methods depends on how are implemented
• Teachers can improve the instructional quality of their courses by
making a number of small changes
- providing detailed task-focused and improvement-oriented
feedback
• The combination of teacher-cantered and student-cantered
instructional elements is more effective than either form of instruction
alone
Variables associated with achievement
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SamAbrahamflickr.com
Blended Learning
Frontier between physical and virtual spaces is blurring
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1. Think in multiple spaces
Towards higher order skills
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2. Keep outcomes in mind while designing
After this lecture/week
students should
be able to …
CCSUNZ2013flickr.com
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trainingpahflickr.com
Bjork, R. A., Dunlosky, J., & Kornell, N. (2013). Self-regulated learning: beliefs, techniques, and illusions. Annu Rev Psychol, 64,
417-444. doi:10.1146/annurev-psych-113011-143823
3. Design preparation activities
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hijukalflickr.com
Think outside of the box
4. Design face-to-face activities
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PNNLPacificNorthwestflickr.com
• Collect data about how students
participate in a learning experience
• Translate observations into actions
• Take into account the instructional
design
• Expertise of the instructor
• Create and deploy personalised
support actions
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Student
Engagement
and
Feedback
Design for
Engagement
Examples
theilrflickr.com
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Simple intuitive structure to find resources
Available: bit.ly/elec1601 (Only Australian Universities)
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You should take a more
careful look at how symbols
are encoded in the video.
Would you be able to encode/
decode UAL symbols without
looking at the video?
Good initial work. However,
did you understand the trick
to handle encoding with a
variable number of bits?
Would you be able to provide
an example?
Good work. Would you be
able to come up with your
own machine language and
your encoding scheme?
Remember that it has to be
unambiguous.
Thorough work with the task
about machine language
encoding. Give it a quick
review before the midterm.
Q1 Q2 Q3 Q4
Instructor
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Effect size (Cohen’s d) = 0.49.
Medium positive effect
Effect size (Cohen’s d) = 0.21.
Small positive effect
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Liu, D. Y.-T., Bartimote-Aufflick, K., Pardo, A., & Bridgeman, A. J. (2016). Data-driven Personalization of Student Learning Support in
Higher Education. In A. Peña-Ayala (Ed.), Learning analytics: Fundaments, applications, and trends: A view of the current state of the
art. In preparation: Springer.
Student Relationship Engagement System (SRES)
Instructors define simple rules to create
personalised emails from multiple data sources
Notsomuchflickr.com
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IF [video 3.9.5 not watched] THEN “…."
ontasklearning.org
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• Support instructors to
create personalised
feedback
• Simple rule-base
knowledge encoding
• Provide appropriate
view of data sources
• Scale to large and highly
diverse cohorts
• Open-source project
• First pilots in Q1/2 2017
• Tutorial in LAK 2017
• Contact us if interested
ontasklearning.org
45. Abelardo Pardo Increasing Student Engagement With Personalised Feedback
Conclusions
45
BetsyWeberflickr.com
• Strong evidence connects student engagement
and feedback with academic attainment
• (Good) Feedback can have a strong positive effect
• Embrace design in a complex environment
• Acknowledge student approaches to learning
• Collect data and provide frequent, personalised,
situated feedback
46. Abelardo Pardo (@abelardopardo)
Faculty of Engineering and IT
slideshare.net/abelardo_pardo
Increasing Student Engagement
with Personalised Feedback
IkhlasulAmalflickr.com
Education Grand Rounds
Westmead Hospital Education Centre
8/May/2017