Learning Gains, Student Attitudes, and impacts on LA’s in Phys 1110 (Sp ‘03)
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Learning Gains,Student Attitudes,
and impacts on LA’sin Phys 1110 (Sp ‘03)
S. Pollock
With NSF/STEM-TP support
Class structure/reforms
Conceptual emphasis: clickers in lecture
Tutorials: based on U Wash materials, with use of LA’S (Average attendance: 85%)
(Modest) explicit attention to “the hidden curriculum”:
thinking about thinking
reality link
coherence“Propaganda”: the value of collaboration, discussion.
Role/training of LA’sLA/TA training: Mon 5-6:30 every week
Roles: cover 3 (50 min) tutorials/wk
Partner with TA, but no recitation grading
1-2 help room hours/week
Help grade 1-2 midterms (long answer q’s)
Data CollectionFCI pre/post tutorial pre/post [clicker and exam]Detailed grade informationRegular student online surveysSALG surveyIn class anonymous surveysVASS/CLASS pre/post (Wendy Adams)
Danielle Harlow’s observationsLA/TA self reflections
Students
LA’s
Force Concept Inventory (FCI)
Phys 1110 Fa ‘03
R. Hake, ”…A six-thousand-student survey…” AJP 66, 64-74 (‘98).
Force Concept Inventory (FCI)
Phys 1110 Fa ‘03
R. Hake, ”…A six-thousand-student survey…” AJP 66, 64-74 (‘98).
FCI gains
N=394 (of 562)Average = .62Median = .67
Normalized Gain
0
5
10
15
20
25
30
35
40
-0.5 -0.4 -0.2 -0.1 0 0.12 0.24 0.36 0.48 0.6 0.72 0.84 0.96
%
# of students
Phys 1110 Fa ‘03 pre-post
Force Concept Inventory
0
10
20
30
40
50
60
70
0 6.67 13.3 20 26.7 33.3 40 46.7 53.3 60 66.7 73.3 80 86.7 93.3 100
Score (%)
# of students
Pretest
Average pretest: 53%(N=507)
Force Concept Inventory
0
10
20
30
40
50
60
70
0 6.67 13.3 20 26.7 33.3 40 46.7 53.3 60 66.7 73.3 80 86.7 93.3 100
Score (%)
# of students
Pretest
Posttest
Average posttest: 81%(N=445)352 had post ≥ 70%
CLASS pre/post
0
20
40
60
80
100
0 20 40 60 80 100
Unfavorable
Favorable
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
CLASS results
Correlation of course grade (not including tutorial hw) to tut hw
Correlating course grade (except tut hw) with tut hw score (N=562) r=.73
51525354555657585
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0
tutorial hw
Course score (85 max)
g known (N=394) r=.68 g unknown (N=168) r=.73
Skip more corr’s.
Correlate clicker with gradeCorrelate clicker score with grade
(N=555) r=.56
0.0
20.0
40.0
60.0
80.0
100.0
0.0 20.0 40.0 60.0 80.0 100.0
Clicker score (drop worst) (%)
Course grade (%)
g known (N=389) r=.30 g unknown (N=166) r=.53
Average class attendance: 80%
Correlate class attend with gradeCorrelate class attend with grade
(N=555) r=.50
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0
Lecture attendance (%)
Course grade (%)
g known (N=389) r=.30 g unknown (N=166) r=.53
Correlation of fci gain to tut hw
Correlate fci gain with clicker score(N=389) r=.26
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
0.0 20.0 40.0 60.0 80.0 100.0
Clicker score (drop worst) (%)
fci gain (%)
pretest 0-15 (N=204) r=.23 pretest 16-27 (N=185) r=.27
Correlating FCI gain with tutorial hw(N=394) r=.25
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
0 20 40 60 80 100
Tutorial hw (%)
g = (f-i)/(100%-i)
FCI Pre 0-15 (N=206) r=.25 FCI pre 16-27 (N=188) r=.20
Attitude about tutorialOnline midterm. N=464 (of 562)
Pos Neg
Tut. useful 57 21
Like tut. 21 44
Groups useful 72 8
Like groups 59 14
Anonymous question end of semester N=351
67 14
35 41
Online question end of semester, N=461
21.3% “Neg all along” 8.7%“more neg in the end”15.8% “positive all along” 54.2% “more pos in the end”
11
SALG end of sem, N=250
10
Learning value of class activities
Learning value of class activities
0
10
20
30
40
50
60
No help Little help ModerateHelp
Much Help Very muchhelp
NA
%
Class presentationsincluding lect.
Concept tests
Peer discussions
Whole classdiscussions
Demos
Tutorials
Learning value of resources
Learning value of resources
0
10
20
30
40
50
60
No help Little help ModerateHelp
Much Help Very muchhelp
NA
%
Tutorial Homework
Long Answerhomework .CAPA
HRW textbook
Thinkwell
Web page
Help room
Value of individ support
Value of individual support
0
10
20
30
40
50
60
No help Little help ModerateHelp
Much Help Very muchhelp
NA
%
Quality of contactwith teacher
Quality of contactwith TA
Qualtiy of contactwith LA
Working w. peersoutside class
Perceived gainsPerceived gains of students
0
10
20
30
40
50
60
Nothing A little Somewhat A lot A greatdeal
NA
%
Solving Problems
Discussing/arguingabout scienceWorking with others
Understanding physicsconceptsUnderst. relationshipbetw. conceptsUnderst. relevance toreal worldAppreciating the field
Skip gains
Q13: How do you feel about the subject of physics, compared to the first day of class?
B) slightly more positive
41%
A) much more positive
22%
E) much more negative
2%D) slightly more negative
7%
C) neutral, no change28%
Feelings...
End of semester anonymous survey
Learning gains on tutorial topics(prelim!)
Topic
Pre(%)
Post (click)
g Post(exam/final)
g
1d accel
(a at top )
(accel constant)
22
44
60 .5 67/76
77
.6
.6
2d accel
Direction (circ/
curve)
Magnitude
32
5
39
62 .6
90
85
85
.9
.8
.75
Learning gains on tutorial topics-ii
Topic
Pre(%)
Post (click)
g Post(exam/final)
g
Newton
Free body diag.
Hard, rel motion
N-III
54
22
68 87 .6
78/96
41
90
.5/.9
.24
.7
Relative motion*
(speed up in diff frames)
26 41 .2 67 .55
* This topic was not covered in lecture or reading.
Learning gains on tutorial topics-iii
Topic
Pre(%)
Post (click)
g Post(exam/final)
g
Newton II
extended body 9-20 33* .2-
.3
54 .5
Conserve p
Collision/cons
One object very massive
26
16
77
89 (74 silent)
.7
.9 (.7)
74 .65
* This is consistent, actually higher, than UW has measured. They've since modified this tutorial.
Gender differences
Women (25%): self reported hours/week 5.5Men (75%): self reported hours/week 4.6
Pretest, post, and course grade
0.57
0.39
0.840.740.76 0.75
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
Men (75%) Women (25%)
Score (%)
Pre
Post
Course
Other effects
TA/LA: None on grade, or FCI gain Possible (slight) impact on attitude about tutorials.
Room: None on grade, or FCI gain Possible (slight) impact on attitude about tutorials. (appears to be independent of TA)
LA comments
Some (high) correlations
.91: my predicted grade after 2nd midterm with final grade
.75: long answer exam q’s with multiple choice exam q’s
.67: CAPA homework with tutorial hw
.46: self-reported calculus grade with course grade
.59: course grade with tutorial attendance
.40: their prediction of 1st exam score with 1st exam score
Research questions
Impacts of modified instruction
• Clickers/peer instruction• Tutorials• Other: Thinkwell (video text)
Use of LA’s Help Room…
on:(Measurable) learning gainsAffect/attitudes of studentsPedagogical content knowledge of LA’s
LA comments:
LA 1) "The tutorial setup was a great experience... I will be taking everything I've learned in this class with me for my future career as a teacher”
LA 2) "After teaching for a semester, I am very committed to teaching again at some point in my life. I am enrolling in the School of Ed, and I plan on teaching after graduating... I had never learned physics in any way resembling the tutorials, but now I will definitely try to model parts of my classrooms around cooperative learning".
more LA commentsLA 3) "As a result [of being an LA] my views on a career in teaching have changed. I have decided to become a high school physics teacher... I have learned so much about physics, teaching, learning, education, and collaborative learning from being [an LA]"
LA 4) "This experience of teaching tutorials has shown me different styles of learning, and allowed me to begin the process of understanding and helping all types of students. But the most valuable thing I have gained was the heads up to the fact that a good teacher will only come with time, and practice does make perfect".
Still to come:• Relation of CLASS data to learning gains (and tutorial attitude?)
• More detailed pre/post results on variety of topics
• Comparison of pre/post with UW students (?)
• LA development: impacts on them (Danielle)
• Early predictors of success/failure (Pat)
• What else? (There’s a lot of micro-data here!!)
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