7 ResearchBased Principles For Learning & Teaching Adapted from ‘How Learning Works’
7 Research-‐Based Principles For Learning & Teaching
Adapted from ‘How Learning Works’
Overview
I. About PeerWise
II. Implemention
III. Engagement, Learning, Question Quality
• Course-‐based online MulGple Choice QuesGon repository built by students
• Students: – develop new questions with
associated explanations – answer existing questions and rate
them for quality and difficulty – take part in discussions – can follow other authors
peerwise.cs.auckland.ac.nz
>100,000 student contributors
>500,000 unique questions
>10,000,000 answers
5
As a question author…..
6
7
10
As a question answerer …..
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13
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Overview
I. About PeerWise
II. Implemention
III. Engagement, Learning, Question Quality
Implementation in PHAS 101 8 sections (4-3-1) N(total) ~1800 2012 W2 3 sections N ~750 All non majors. 2 PeerWise assignments
- scaffolded ahead of the first - support woven into 4 subsequent tutorials
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Assessment requirements As a minimum: • Write one question • Answer 5 • Comment on & rate 3 Contributed 2 x 2.5% to course assessment (mostly participation, small bonus for performance)
Student questions on midterm and final 17
We were deliberately hands off. • No moderation • No corrections • No interventions at all
But we did observe…..
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Scaffolding in tutorials
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Scaffolding in tutorials
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Overview
I. About PeerWise
II. Implemention
III. Engagement, Learning, Question Quality
• Phys 101 uptake graph showing midterm
Engagement
First assessment exercise: • 664 acGve students (85% of cohort) • 1340 Q, 11000 A, 5000 C • x1.75, x17, x7 minimum requirements
Engagement
Score
Examples
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Learning • Good engagement and parGcipaGon beyond the minimum requirements
• CorrelaGon between use and end-‐of-‐course outcome
• ReplicaGon study in 3 insGtuGons, 5 courses, 3 disciplines
1st year Physics N=172 University of Edinburgh
1st year Physics N=172 University of Edinburgh
1st year Chemistry N=172 University of Edinburgh
0%
5%
10%
15%
20%25%
30%
35%
40%
45%
50%
1 2 3 4 5 6
Taxonomic Category
Perc
enta
ge o
f Sub
mitt
ed Q
uest
ions
Learning
• QuesGon quality: mapped onto levels in cogniGve domain of Bloom’s taxonomy
• Surprisingly high overall quality, even from ‘novices’
First semester N = 350
Second semester N = 252
Acknowledgements
Physics 101 course team Georg Rieger Firas Moosvi Emily Altiere UBC CWSEI
[email protected] @simonpbates
Ross Galloway Judy Hardy Karon McBride Alison Kay Keith Brunton Jonathan Riise Danny Homer
Chemistry – Peter Kirsop Biology – Heather McQueen
Physics – Morag Casey
Comp Sci – Paul Denny
Resources -‐ PeerWise Site: http://peerwise.cs.auckland.ac.nz Community: http://www.PeerWise-Community.org JISC-funded multi institution study:
https://www.wiki.ed.ac.uk/display/SGC4L/Home UoE Physics Pilot Study: AIP Conf. Proc. 1413, 359
http://dx.doi.org/10.1063/1.3680069 RSC overview article http://www.rsc.org/Education/EiC/issues/2013January/
student-generated-assessment.asp UoE Physics scaffolding resources
http://www2.ph.ed.ac.uk/elearning/projects/peerwise/
Question quality analysis (1st year Physics University of Edinburgh)
Assessing the quality of a student-generated question repository, submitted to Phys
Rev, ST Phys Educ Res.
Multi-institution, multi-course study
Student-generated content: Enhancing learning through sharing multiple-choice
questions, submitted to International Journal of Science Education
Scaffolding Student Learning via Online Peer Learning, submitted to International
Journal of Science Education
Publications in preparation / review / press