Building on a Base:
tools, practices, and implications from
physics education research (PER)
S.J. Pollock
N.D. Finkelstein
Physics Department
Thanks for support from:
Pew/Carnegie CASTL,
NSF CCLI
NSF STEM-TP
APS: 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...)
Building on a base
Classroom practice
Curricular reforms
Data
Student concepts and engagement
Theoretical frames
What’s our goal?
Novice
Pieces
structure
Formulas &
“plug ‘n chug”
content
By Authority
learning
Expert
Coherence
Concepts &
Problem Solving
Independent
(experiment)
think about science like a scientist
COGNITION AND INSTRUCTION (physics), David Hammer
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
CLASS
CURRIC
DATA
STUDENT
THEORY
Interviews/open questions
(e.g. Arons, McDermott, ...)
• Prior knowledge
• Basis for surveys and curriculum reform
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.
CLASS
CURRIC
DATA
STUDENT
THEORY
Sample question
FCI I
Force Concept Inventory (FCI)
traditional lecture
<g> = post-pre
100-pre
R. Hake, ”…A six-thousand-student survey…” AJP 66, 64-74 (‘98).
CLASS
CURRIC
DATA
STUDENT
THEORY
Trad’l Model of Education
Individual
Instruction via
transmission
Content (E/M)
CLASS
CURRIC
DATA
STUDENT
THEORY
Where does this come from?
• Our classes
F
C
I
II
Force Concept Inventory (FCI)
red = trad, blue = interactive engagement
<g> = post-pre
100-pre
R. Hake, ”…A six-thousand-student survey…” AJP 66, 64-74 (‘98).
CLASS
CURRIC
DATA
STUDENT
THEORY
PER Theoretic Background
Individual
Individual
Prior knowledge
Instruction
via transmission
Construction
constructivist
Content (E/M)
Content (E/M)
J. Piaget - Swiss psychologist (1896-1980)
Students: are active in the educational process
construct understanding based on prior knowledge
learn through individual development
CLASS
CURRIC
DATA
STUDENT
THEORY
Value of FCI
•
•
•
•
CLASS
CURRIC
DATA
STUDENT
THEORY
Based on research
Refocus on concepts
Quantitative basis for comparing curricula
Wake up call
F
C
I
at
C
U
Force Concept Inventory (FCI)
red = trad, blue = interactive engagement
<g> = post-pre
100-pre
Fa98
Fa03/Sp04
R. Hake, ”…A six-thousand-student survey…” AJP 66, 64-74 (‘98).
CLASS
CURRIC
DATA
STUDENT
THEORY
CLASS
CURRIC
DATA
STUDENT
THEORY
Next steps
Conceptual survey development
www.flaguide.org
Attitudes/student epistemology
Research on student understanding
-> guide to curricular reforms
-> incorporate cognitive theories
Attitudes and Beliefs
CLASS
CURRIC
DATA
STUDENT
THEORY
VASS, MPEX, CLASS, ... (e.g. Saul, Redish, PER@C,...)
Assessing the “hidden curriculum”
Examples:
“I study physics to learn knowledge that will be
useful in life.”
“To learn physics, I only need to memorize
solutions to sample problems”
(Typical) attitude shifts
CLASS pre/post
100
Favorable
80
60
40
20
0
0
20
40
60
Unfavorable
80
100
Overall Pre
Indep. Pre
Coher. Pre
Conc. Pre
R. App. Pre
R. Care. Pre
Math Pre
Effort Pre
Skept. Pre
Overall Post
Indep. Post
Coher. Post
Conc. Post
R. App. Post
R. Care Post
Math Post
Effort Post
Skept. Post
W. Adams 2003, replicating Redish, Steinberg, Saul AJP 66 p. 212 (‘98)
(Typical) attitude shifts
CLASS pre/post
100
Favorable
80Reality
60
Concepts
40
20
0
0
20
40
60
Unfavorable
80
100
Overall Pre
Indep. Pre
Coher. Pre
Conc. Pre
R. App. Pre
R. Care. Pre
Math Pre
Effort Pre
Skept. Pre
Overall Post
Indep. Post
Coher. Post
Conc. Post
R. App. Post
R. Care Post
Math Post
Effort Post
Skept. Post
W. Adams 2003, replicating Redish, Steinberg, Saul AJP 66 p. 212 (‘98)
CLASS categories
•
•
•
•
•
•
•
•
CLASS
CURRIC
DATA
STUDENT
THEORY
Shift (%) (“reformed” class)
Real world connect... -6
Personal interest........ -8
Engineers: -12
Sensemaking/effort... -12
Conceptual................ -11
Math understanding... -10
Problem Solving........ -7
Phys Male: +1
Confidence................ -17
Phys Female: -16
Nature of science....... +5
(All ±2%)
But it’s possible to do better
CLASS
CURRIC
DATA
STUDENT
THEORY
Data from instructor attending (somewhat) to “hidden curriculum”)
75
% Favorable
Conceptual Understanding
65
55
45
35
g<=.25
0.25<g<=0.5 0.5<g<=0.75 0.75<g<=0.9
0.9<g<=1
Learning Gains
Low learning gain <---------> high learning gain
Blue= pre
Red= post
% of group within gain bin
Expectations/Beliefs matter
60
g<=0.3
0.3<g<=0.8
CLASS
CURRIC
DATA
STUDENT
THEORY
g>0.8
50
40
30
20
10
0
0-40 (N=24) 40-60 (N=74)
60-80
(N=189)
pre CLASSPre-Overall
(overall) Favorable Score
low
80-100
(N=44)
<--------------------------------------> high
Curriculum reform
ConcepTests (Mazur)
Tutorials (McDermott)
Workshop physics (Laws)
CLASS
CURRIC
DATA
STUDENT
THEORY
(easy to implement)
(modest infrastructure)
(resource intensive)
And many more - can’t do justice!
Interactive Lect Demos (Thornton, Sokoloff)
Problem solving (Van Heuvelen, Heller,...)
Based on empirical research
Next generation: cognitive theory as well.
Reproducibility
Primary/secondary implementation of “Tutorials”
Topic
Newton’s law & tension
U. Wash. U. Wash.
no tutorial with tutorial
25%
50%
CLASS
CURRIC
DATA
STUDENT
THEORY
CU
with tutorial
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%
UW data from McDermott, Shaffer, Somers, Am. J. Phys. 62(1), 46-55 (94)
Rounding all results to nearest 5%
Summary
•
•
•
•
•
CLASS
CURRIC
DATA
STUDENT
THEORY
State of PER: beyond “reflective teaching”
Data driven
Published/publishable results
Reproducible across institutions
Changing culture of departments (?!)
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.org
per.colorado.edu
www2.physics.umd.edu/~redish/Book/
Impact of peer instruction
CU reformed course Fa 03
FCI scores
Phys 1110 Fa '03
70
60
# of students
50
40
FCI Pre
FCI Post
30
20
10
0
0
7
13
20
27
33
40
47
53
Score (%)
60
67
73
80
87
93
100
%gain vs
%pretest
Traditional vs. Interactive Engagement
(From Hake, see earlier ref, AJP 66, 64-74 (‘98)
Impact of tutorials
Correlating rest of course score to tut hw
(Sp04: N=513, r=.65)
80
70
Remaining grade
(85 max)
60
50
40
30
20
10
0
0
20
40
60
80
Tutorial HW score
g known (N=383, r=.58)
g unknown (N=130, r=.65)
100