building on a base:
DESCRIPTION
Building on a Base: . S.J. Pollock N.D. Finkelstein Physics Department Thanks for support from: Pew/Carnegie CASTL, NSF CCLI NSF STEM-TP APS: PhysTEC. tools, practices, and implications from physics education research (PER). Overview. Physics Education Research (PER) - PowerPoint PPT PresentationTRANSCRIPT
Building on a Base: tools, practices, and implications from
physics education research (PER)
S.J. PollockN.D. FinkelsteinPhysics Department
Thanks for support from: Pew/Carnegie CASTL,NSF CCLINSF STEM-TPAPS: PhysTEC
Overview• Physics Education Research (PER) Rapid growth, subfield of physics• A Physicist’s History: Research on student concepts (Arons, McDermott, ...)
Concept Inventories (Halloun, Hestenes , Hake, ...)
Curriculum (Washington, Maryland, Mazur, many...) Theoretical Frames (Redish, diSessa, many...)
Theoretical frames
Student concepts and engagement
Curricular reforms
Data
Classroom practice
Building on a base
structurePieces Coherence
By Authority Independent(experiment)
learning
COGNITION AND INSTRUCTION (physics), David Hammer
Novice Expert
Formulas & “plug ‘n chug”
Concepts & Problem Solving
content
think about science like a scientist
What’s our goal?
APS
In recent years, physics education research has emerged as a topic of
research within physics departments. ... The APS applauds
and supports the acceptance in physics departments of research in
physics education.
-The American Physical Society
Statement 99.2 Research in Physics Education (May 1999)
Professional recognition
• Journals (AJP, and Physical Review) • NSF funding • >50 institutions with PER groups
Data on student conceptions
Interviews/open questions (e.g. Arons, McDermott,
...)
• Prior knowledge• Basis for surveys and curriculum reform
CLASSCURRIC
STUDENTDATA
THEORY
A possible “tilting” development
• Force Concept Inventory (Hestenes, Wells, Swackhamer, Physics Teacher 20, (92) 141, Halloun and Hestenes)
• Multiple choice survey, (pre/post)• Experts (especially skeptics!) => necessary (not sufficient) indicator of
conceptual understanding.
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STUDENTDATA
THEORY
Sample question
Force Concept Inventory (FCI)
R. Hake, ”…A six-thousand-student survey…” AJP 66, 64-74 (‘98).
<g> = post-pre 100-pre
traditional lecture
FCI I CLASSCURRIC
STUDENTDATA
THEORY
Trad’l Model of EducationInstruction viatransmissionIndividual Content (E/M)transmissionist
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Where does this come from?
• Our classes
Force Concept Inventory (FCI)
R. Hake, ”…A six-thousand-student survey…” AJP 66, 64-74 (‘98).
<g> = post-pre 100-pre
red = trad, blue = interactive engagement
FCI II
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PER Theoretic Background
Instructionvia transmissionIndividual Content (E/M)transmissionist
Individual
Prior knowledge
Content (E/M)Constructionconstructivistbasic constructivist
J. Piaget - Swiss psychologist (1896-1980)Students: are active in the educational process
construct understanding based on prior knowledgelearn through individual development
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THEORY
Value of FCI
• Based on research• Refocus on concepts• Quantitative basis for comparing curricula• Wake up call
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STUDENTDATA
THEORY
Force Concept Inventory (FCI)
R. Hake, ”…A six-thousand-student survey…” AJP 66, 64-74 (‘98).
<g> = post-pre 100-pre
Fa03/Sp04Fa98
red = trad, blue = interactive engagement
FCI at CU
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Next steps
Conceptual survey development www.flaguide.org
Attitudes/student epistemology
Research on student understanding -> guide to curricular reforms -> incorporate cognitive theories
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THEORY
Attitudes and Beliefs
VASS, MPEX, CLASS, ... (e.g. Saul, Redish, PER@C,...)
Assessing the “hidden curriculum”
Examples:Examples: ““I study physics to learn knowledge that will be I study physics to learn knowledge that will be useful in life.”useful in life.”““TTo learn physics, I only need to memorize solutions to sample problems”
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STUDENTDATA
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CLASS pre/post
0
20
40
60
80
100
0 20 40 60 80 100
Unfavorable
Favorable
Overall PreIndep. PreCoher. PreConc. PreR. App. PreR. Care. PreMath PreEffort PreSkept. PreOverall PostIndep. PostCoher. PostConc. PostR. App. PostR. Care PostMath PostEffort PostSkept. Post
W. Adams 2003, replicating Redish, Steinberg, Saul AJP 66 p. 212 (‘98)
(Typical) attitude shifts
CLASS pre/post
0
20
40
60
80
100
0 20 40 60 80 100
Unfavorable
Favorable
Overall PreIndep. PreCoher. PreConc. PreR. App. PreR. Care. PreMath PreEffort PreSkept. PreOverall PostIndep. PostCoher. PostConc. PostR. App. PostR. Care PostMath PostEffort PostSkept. Post
Concepts
Reality
W. Adams 2003, replicating Redish, Steinberg, Saul AJP 66 p. 212 (‘98)
(Typical) attitude shifts
Shift (%) (“reformed” class)
-6-8-12-11-10-7-17+5(All ±2%)
CLASS categories
• Real world connect...• Personal interest........• Sensemaking/effort...• Conceptual................• Math understanding...• Problem Solving........• Confidence................• Nature of science.......
Engineers: -12
Phys Male: +1Phys Female: -16
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STUDENTDATA
THEORY
But it’s possible to do better
Conceptual Understanding
35
45
55
65
75
g<=.25 0.25<g<=0.5 0.5<g<=0.75 0.75<g<=0.9 0.9<g<=1
Learning GainsLow learning gain <---------> high learning gainBlue= preRed= post
Data from instructor attending (somewhat) to “hidden curriculum”)
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Expectations/Beliefs matter
0
10
20
30
40
50
60
0-40 (N=24) 40-60 (N=74) 60-80(N=189)
80-100(N=44)
Pre-Overall Favorable Score
g<=0.3 0.3<g<=0.8 g>0.8
low <--------------------------------------> highpre CLASS (overall)
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STUDENTDATA
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Curriculum reformConcepTests (Mazur) (easy to implement) Tutorials (McDermott) (modest infrastructure)Workshop physics (Laws) (resource intensive)
And many more - can’t do justice! Interactive Lect Demos (Thornton, Sokoloff) Problem solving (Van Heuvelen, Heller,...)
Based on empirical researchNext generation: cognitive theory as well.
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STUDENTDATA
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Topic U. Wash. no tutorial
U. Wash.with tutorial
CUwith tutorial
Newton’s law & tension 25% 50% 55%
Newton & constraints 45% 70% 45%/75%
Force diagrams 30% 90% 95%
Newton’s III law 15% 70% 70%
Combine Newton’s laws 35% 80% 80%
ReproducibilityPrimary/secondary implementation of “Tutorials”
Rounding all results to nearest 5%
UW data from McDermott, Shaffer, Somers, Am. J. Phys. 62(1), 46-55 (94)
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Summary
• State of PER: beyond “reflective teaching”• Data driven• Published/publishable results• Reproducible across institutions• Changing culture of departments (?!)
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Discussion!
• Starting ideas...– What sorts of practices occur in engineering /
based on what sort of research/theoretical framing?– What assessment tools are there?– How well codified is the discipline / goals of
instruction?
The end
See: www.flaguide.orgper.colorado.eduwww2.physics.umd.edu/~redish/Book/
Impact of peer instruction
FCI scoresPhys 1110 Fa '03
0
10
20
30
40
50
60
70
0 7 13 20 27 33 40 47 53 60 67 73 80 87 93 100Score (%)
# of students
FCI PreFCI Post
CU reformed course Fa 03
Traditional vs. Interactive Engagement(From Hake, see earlier ref, AJP 66, 64-74 (‘98)
%gain vs %pretest
Correlating rest of course score to tut hw (Sp04: N=513, r=.65)
01020304050607080
0 20 40 60 80 100Tutorial HW score
Remaining grade (85 max)
g known (N=383, r=.58)g unknown (N=130, r=.65)
Impact of tutorials