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Role of PER in a Thriving Physics Department Viewing Learning through the Lens of Physics
Our PER group
2 faculty – 1 physics + 1 education
1 post doc
3 graduate students
1 teacher-in-residence
Visiting scholars
Etc.
Ken Heller
School of Physics and Astronomy
University of Minnesota
20 year continuing effort to improve undergraduate education with contributions by:
Many faculty and graduate students of U of M Physics Department
In collaboration with U of M Physics Education Group
Details at http://groups.physics.umn.edu/physed/
Supported in part by Department of Education (FIPSE), NSF,
and the University of Minnesota
Outline for Discussion
• What can PER do for your department.
• Examples
Are we a “thriving” department?
• Number of majors increased from about 15/yr to about 50/yr
• We are maxed out
• Instructional budget is “protected” by the Dean through numerous budget cuts
• Adequate funding for undergraduate program improvements both internal
and external
• We have large improvements to make– we can do better.
• Improve the number of female majors
• Better measure of problem solving
• Modernize the curriculum
• More organized undergraduate research
All Physics Departments Teach The Same
Stable
Meta-stable
Stable
Better Implementation
Specific Changes
Systemic Changes
Departmental
Commitment
Research-based
Instructional System
Individual Effort
Large continuous effort
Easily returns to ground state
Small continuous effort
Stable against small changes
Can jump to ground state
Small continuous effort
Stable against change
Can decay to ground state
PER: Helps Initiate Change
• Don’t try to invent a perpetual motion machine.
– Good educational practice, like good science is often counter-intuitive
• Fundamental Principles (Causality, Unitarity, Lorentz Invariance)
• Theory (Electricity and Magnetism described by Maxwell’s equations)
• Empirical rules (Ohm’s law)
– Educational change has a long history
• Many things are known not to work
• We even know why they don’t work
• Learning is a biological process, teaching is the action that
helps people implement that process.
– Neural science and cognitive psychology set boundary conditions
– Teaching is the manipulation of the learning environment
• Assessing change
– What is an appropriate measure?
– Establishing a baseline
PER: Helps Implement Change
• Arrive at reasonable goals
– Getting information from stakeholders
– What changes are easy
– What changes are hard
• Identify minimum necessary changes
– Incremental or dive in
• Recognition that improvement takes time
performance
– Measurement and baseline data
– Change initially degrades performance
time
PER: Helps Sustain Change
• A Physics Department is not a closed system
– Inputs from Administration, Government, Parents, Students
• Initiatives to embrace
• Initiatives to ignore
• Initiatives to resist
– Finances are important – what to cut?
– Faculty time is important – effort balance
• Meaningful change is not initially popular
– Understand dynamics of natural human resistance
– To identify and tweak the parameters requires measurements
• Countering entropy increase requires an energy input
– Identify when system is degrading
– Initiate corrective action
PER Enriches the Intellectual Environment
• Research into learning from a physics point of view
–
–
–
–
Education
Cognitive psychology
Neural science
Measurement
• Quantitative – appropriate statistics
• Qualitative
– Question the “frozen” curriculum
• Awareness of the field
– Build on other people’s progress
• Research opportunities for students
• Opportunities for outside collaboration
• Opportunities for interdisciplinary collaboration
Pedagogy - Learning is a Biological Process
Phenomenological Learning Theory
Apprenticeship Works
Cognitive Apprenticeship
Learning in the environment of
expert practice
• Why it is important
• How it is used
• How is it related to a student’s
existing knowledge
Neurons that fire together, wire together
model
Simplification of Hebbian theory:
Hebb, D (1949). The organization of behavior.
New York: Wiley.
coach
Collins, Brown, & Newman (1990)
Brain MRI from Yale Medical School
Neuron image from Ecole Polytechnique Lausanne
fade
Pedagogy – Cooperative Group Problem Solving
LECTURES
RECITATION
SECTION
LABORATORY
TESTS
Four hours/week, sometimes with
informal cooperative groups. Model
constructing knowledge in response to
problems, model organized problem
solving framework.
One hour each Thursday – cooperative
groups practice using a problem-solving
framework to solve context-rich
problems. Peer coaching, TA coaching.
Two hours/week -- same cooperative groups
practice using a framework to solve
context-rich experimental problems. Same
TA. Peer coaching, TA coaching.
4 quizzes/semester on Friday -- problemsolving & conceptual questions (2
problems, 10 multiple choice) (1 group
problem in previous discussion section).
Scaffolding
Additional structure used to support the
construction of a complex structure.
Removed as the structure is built
Examples of Scaffolding in teaching Introductory Physics
• An explicit problem solving framework - continually modeled
• A worksheet that structures the framework – removed early in the course
• Cooperative group structure that encourages productive group interactions
• Limit use of formulas by giving an equation sheet (only allowed equations)
• Explicit grading rubric for problem solutions to encourage expert-like behavior
• Problems that discourage novice problem solving
• Explicit grading rubric for lab problems to encourage expert-like behavior
• TA education and support in pedagogy
Problem-solving Framework
G. Polya, 1945
Used by experts in all fields
STEP 1
Recognize the Problem
What's going on? Chi, M., Glaser, R., & Rees, E. (1982)
STEP 2
Describe the problem in terms of the field
What does this have to do with ...... ?
STEP 3
Plan a solution
How do I get out of this?
STEP 4
Execute the plan
Let's get an answer
STEP 5
Evaluate the solution
Can this be true?
Page 1
Problem Solving Worksheet used at the beginning of the course
Page 2
Individual Context- Rich Problem on an Exam
Your task is to design an artificial joint to replace arthritic elbow
joints in patients. After healing, the patient should be able to hold
at least a gallon of milk while the lower arm is horizontal. The
biceps muscle is attached to the bone at the distance 1/6 of the bone
length from the elbow joint, and makes an angle of 80o with the
horizontal bone. How strong should you design the artificial joint
if you assume the weight of the bone is negligible.
Gives a motivation – allows some students to access their mental connections.
Gives a realistic situation – allows some students to visualize the situation.
Does not give a picture – students must practice visualization.
Uses the character “you” – allows some students to visualize the situation.
Coaching With Cooperative Groups
Having Students Work Together in Structured Groups
Email 8/24/05
 Positive Interdependence
 Face-to-Face Interaction
 Individual Accountability
 Explicit Collaborative Skills
 Group Functioning Assessment
I was reading through your 'typical
objections'. Another good reason
for cooperative group methods: this
is how we solve all kinds of
problems in the real world - the
real academic world and the real
business world. I wish they'd had
this when I was in school. Keep up
the great work.
Rick Roesler Vice President,
Handhelds Hewlett Packard
Retention
Drop % Physics 1301
25%
Change from quarters to semesters
% Drop
20%
15%
10%
5%
quarters
semesters
0%
1997
1998
1999
2000
2001
2002
2003
Year
Dropout rate to 6%, F/D rate to 3% in all classes
2004
2005
2006
2007
Student Problem
Solutions
Initial State
Final State
AVERAGE FCI PRE-TEST & POST-TEST SCORES
CALCULUS-BASED PHYSICS FOR SCIENTISTS & ENGINEERS, FALL TERMS 1993-2008
PRE-TEST
FCI AVERAGE SCORE (%) +/STANDARD ERROR OF MEAN
100
POST-TEST
OLD FCI, 1993-1996
NEW FCI, 1997-2008
90
CHANGE FROM QUARTERS TO SEMESTERS F1999
80
70
60
50
40
30
20
10
93
94
95
96
97
98
99
00
01
02
03
04
05
06
07
08
A, F93
B, F93
C, F93
D, F94
E, F94
F, F94
G, F94
H, F94
bC, F94
I, F95
J, F95
K, F95
L, F95
D, F95
M, F96
G, F96
N, F96
G, F96
O, F96
P, F97
O, F97
K, F97
D, F97
N, F97
P, F98
G, F98
O, F98
G, F98
N, F98
M, F99
O, F99
K, F99
Q, F99
M, F00
R, F00
Q, F00
N, F00
S, F00
T, F00
K, F01
U, F01
N, F01
W, F01
Z, F01
aA, F02
U, F02
K, F02
I, F02
X, F02
V, F03
T, F03
Y, F03
X, F04
U, F04
Q, F04
Y, F04
aT, F05
aU, F05
aV, F05
aZ, F06
aU, F06
aT, F06
aP, F06
X, F07
aU, F07
aT, F07
bA, F07
bF, F08
aU, F08
bF, F08
bA, F08
0
INSTRUCTOR, TERM
Each letter represents a different professor (37 different ones)
• Incoming student scores are slowly rising (better high school preparation)
• Our standard course (CGPS) achieves average FCI ~70%
• Our “best practices” course achieves average FCI ~80%
• Not executing any cooperative group procedures achieves average FCI ~50%
AVERAGE FCI PRE-TEST SCORES BY GENDER & YEAR
CALCULUS-BASED PHYSICS FOR SCIENTISTS & ENGINEERS, FALL TERMS 1997-2007
MALES (N=4375)
FEMALES (N=1261)
100%
AVERAGE FCI PRE-TEST SCORE
90%
80%
70%
60%
y = 0.0084x - 16.4
R2 = 0.88
50%
40%
y = 0.0076x - 14.8
R2 = 0.88
30%
20%
Students are getting better from high school
10%
0%
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
FALL TERM
There is a gender gap in conceptual performance from high school
Males do better.
2007
MALES (N=4375)
FEMALES (N=1261)
100%
AVERAGE FCI SCORE
90%
PRE-TEST GENDER GAP 15.3±0.5%
POST-TEST GENDER GAP 13.4±0.6%
80%
70%
60%
50%
40%
71.2±0.3%
30%
57.8±0.5%
52.8±0.3%
20%
37.5±0.5%
10%
0%
PRE-TEST
POST-TEST
THE GENDER GAP PERSISTS AFTER INSTRUCTION
Percent of respondents for a category
Previous physics experience of males and females
(Have you taken a physics course before?)
% Males
% Females
100
90
80
70
60
50
40
30
20
10
0
No
Yes, regular
Yes,
Yes, college Yes, both
high school advanced
only
college and
only
placement
high school
high school
only
About 90% of males and 85% females have had at least high school physics
AVERAGE MATH PRE-TEST & POST-TEST SCORES BY GENDER
CALCULUS-BASED PHYSICS FOR SCIENTISTS & ENGINEERS, FALL TERMS 2005-2007
MALES (N=845)
FEMALES (N=266)
AVERAGE MATH DIAGNOSTIC SCORE
100
90
PRE-TEST GENDER GAP
-0.7±0.3 (-2.5±1.3%)
POST-TEST GENDER GAP
-0.2±0.3 (-0.7±1.1%)
80
70
60
50
40
30
16.3±0.2
(60.5±0.6%)
17.0±0.3
(63.3±1.1%)
19.0±0.1
(70.3±0.5%)
19.2±0.3
(71.0±1.0%)
20
10
0
PRE-TEST
POST-TEST
There is a slight gender gap in math skills from high school
Females do slightly better.
AVERAGE FCI PRE-TEST SCORES BY PREVIOUS PHYSICS
CALCULUS-BASED PHYSICS FOR SCIENTISTS & ENGINEERS, FALL TERMS 1997-2007
AVERAGE FCI SCORE (%)
100
MALES (N=4215)
90
80
70
Gap = 13.0  1.2 %
FEMALES (N=1217)
14.2  0.7 %
17.1  1.4 %
65% 62%
19% 17%
2% 3%
4% 4%
Advanced
placement high
school only
College only
Both college and
high school
14.5  3.1 %
10.1  3.6 %
60
50
40
30
20
9% 15%
10
0
No Previous Physics Regular high school
only
Gender gap is there no matter what high school physics preparation.
AVERAGE FCI POST-TEST SCORES BY PREVIOUS PHYSICS
CALCULUS-BASED PHYSICS FOR SCIENTISTS & ENGINEERS, FALL TERMS 1997-2007
AVERAGE FCI SCORE (%)
100
90
80
MALES (N=4215)
FEMALES (N=1217)
Gap = 13.0  1.7 %
12.6  0.8 %
13.8  1.5 %
9% 15%
65% 62%
19% 17%
13.3  3.5 %
11.8  3.4 %
70
60
50
40
30
20
2%
3%
4%
4%
10
0
No Previous Physics Regular high school
only
Advanced
placement high
school only
College only
Gender gap persists no matter what high school physics preparation.
Both college and
high school
FCI PRE-TEST BY QUESTION & GENDER
CALCULUS-BASED PHYSICS FOR SCIENTISTS & ENGINEERS, FALL TERMS 1997-2007
MALES (N=4375)
FEMALES (N=1261)
100%
#14: AIRPLANE
#21-24: ROCKET
PERCENT CORRECT
90%
80%
70%
60%
50%
40%
30%
20%
10%
#8-11: HOCKEY PUCK
0%
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
FCI QUESTION NUMBER
MALE FCI PRE-TEST & POST-TEST SCORES
CALCULUS-BASED PHYSICS FOR SCIENTISTS & ENGINEERS, FALL TERMS 1997-2007
MALES PRE-TEST
400
PRE-TEST MEDIAN (AVERAGE):
15 (15.9±0.1)
350
FREQUENCY (N=4375)
MALES POST-TEST
CEILING EFFECT
POST-TEST MEDIAN (AVERAGE):
22 (21.3±0.1)
300
250
200
150
100
50
0
0
1
2
3
4
5
6
7
8
FEMALES PRE-TEST
FCI SCORE
140
FREQUENCY (N=1261)
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
FEMALES POST-TEST
PRE-TEST MEDIAN (AVERAGE):
10 (11.3±0.1)
120
POST-TEST MEDIAN (AVERAGE):
17 (17.3±0.2)
100
80
60
40
20
0
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
FCI SCORE
FCI ABSOLUTE GAIN BY GENDER
CALCULUS-BASED PHYSICS FOR SCIENTISTS & ENGINEERS, FALL TERMS 1997-2007
MALES (N=4375)
FEMALES (N=1261)
12%
FEMALES MEDIAN (AVERAGE):
6 (6.1±0.2 points, 20.3±0.7%)
FREQUENCY (NORMALIZED)
10%
MALES MEDIAN (AVERAGE):
5 (5.5±0.1 points, 18.3±0.4%)
8%
6%
4%
2%
0%
-5
-4
-3
-2
-1
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
ABSOLUTE GAIN = FCI POST SCORE - FCI PRE SCORE
Males and females gain the same amount from the class.
COURSE GRADES BY GENDER
CALCULUS-BASED PHYSICS FOR SCIENTISTS & ENGINEERS, FALL TERMS 1997-2007
MALES (N=4375)
FEMALES (N=1261)
FREQUENCY (NORMALIZED)
7%
6%
MALES AVERAGE COURSE GRADE:
73.5±0.2%
5%
FEMALES AVERAGE COURSE GRADE:
72.0±0.3%
4%
3%
2%
1%
F
D: 40-49%
C: 50-67%
B: 68-82%
A: 83-100%
0%
36
40
44
48
52
56
60
64
68
72
76
80
COURSE GRADE (%)
Males and females do about as well in the course.
84
88
92
96
100
FINAL EXAM GRADES BY GENDER
CALCULUS-BASED PHYSICS FOR SCIENTISTS & ENGINEERS, FALL TERMS 1997-2007
FREQUENCY (NORMALIZED)
Males (N=4375)
5%
5%
4%
4%
3%
3%
2%
2%
1%
1%
0%
Females (N=1261)
MALES AVERAGE
61.0±0.3%
FEMALES AVERAGE
57.1±0.5%
12
18
24
30
36
42
48
54
60
66
72
78
FINAL EXAM GRADE (%)
Males do slightly better in the course final exam problems.
84
90
96
Identify Critical Failure Points
Fail Gracefully
Non-optimal implementation
gives some success
1. Inappropriate Tasks
Must engage all group members (not just one who
knows how to do it)
2. Inappropriate Grading
Must not penalize those who help others (no grading on
the curve)
Must reward for individual learning
3. Poor structure and management of Groups
Building A Course
• Teach Students an Organizational Framework
– Emphasize decisions using physics
– Rule-based mathematics
• Use Problems that Require
– An organized framework
– Physics conceptual knowledge
– Connection to existing knowledge
• Use Existing Course Structure
– Lectures and “handouts” MODELING
– Discussion Sections COACHING
– Labs COACHING
• Scaffolding to Support Problem Solving
Peer
Modeling
Coaching
Instructor
Fading
CGPS Propagates Through the Department
Goals: Calculus-based Course (88% engineering majors) 1993
4.5
Basic principles behind all physics
4.5
General qualitative problem solving skills
4.4
General quantitative problem solving skills
4.2
Apply physics topics covered to new situations
4.2
Use with confidence
Goals: Biology Majors Course 2003
4.9
Basic principles behind all physics
4.4
General qualitative problem solving skills
4.3
Use biological examples of physical principles
4.2
Overcome misconceptions about physical world
4.1
General quantitative problem solving skills
4.0
Real world application of mathematical concepts and techniques
Upper Division Physics Major Courses 2002
Analytic Mechanics
Electricity & Magnetism
Quantum Mechanics
Graduate Courses 2007
Quantum Mechanics
The End
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for more information:
http://groups.physics.umn.edu/physed/
The best is the enemy of the good.
"le mieux est l'ennemi du bien"
Voltaire