MIDTERM AND FINAL EXAM Æ PERFORMANCE ASSESSMENT
CORRELATION1
JULE DEE SCARBOROUGH, PH.D. AND JERRY GILMER, PH.D.
Typically, traditional objective tests are only indicators of what students can do with the
knowledge being measured. Performing well on a traditional test should not lead to an
assumption of what a student can do with that knowledge (e.g., how well they can use the
knowledge). Traditional or objective tests usually measure what students know or know
about, while performance assessments engage students in performance tasks where they
use the knowledge in some way. It is sometimes perceived by performance assessment
advocates that performance assessments (if designed, developed, and well constructed)
are better evidence of what students are capable of doing with knowledge gained. That is
assuming that most traditional tests are written to measure memory for information,
concepts, theories, facts. If, however, tests have been written to include items that are
higher on Bloom’s Taxonomy and require more critical thinking or problem solving, then
those tests would provide evidence of something more than what students know about, as
the particular items engaging students in higher levels of critical thinking and problems
solving usually require that students provide evidence of what they know about by using
that knowledge to solve the problem. That is, if the problems are complex and well
constructed, use of the knowledge will provide evidence of learning.
Some prefer to use tests intentionally as indicators of what students know about and then
follow those tests with performance tasks requiring students to solve problems or engage
in projects that require critical thinking, the manipulation of facts, theories, concepts,
and/or information in a context where particular constraints and conditions as well as
tools, procedures, etc. are set. If this is the goal, then a test and performance task(s) may
be designed to include measurement of some of the same content while also measuring
some different content, as they are distinctly different types of measures with the
potential to accomplish different measurement goals as well as some of the same goals.
Therefore, we asked the professors to design and develop an objective midterm and final
examination as well as corresponding performance task(s) “and scoring rubrics
matching” the content where possible or desirable. The professors were also asked to
identify the objective test items they felt were also being measured on the corresponding
performance task(s).
A statistical correlation was run between the midterm exam and corresponding
performance assessment and the final exam and corresponding performance examination
for each professor’s students. The results should lead the professors to consider the
following:
1. Do they really feel that there is a segment of the objective tests and the
performance tasks where there is a content match? If so, in our program, no
external contentvalidation was required. We assumed the professors knew
1
Note: Correlations have been computed in two ways: 1) leaving zero scores in as zeros; 2) replacing
zero scores with blanks or taking them out, e.g. student was absent.
30
their content. However, it is key to note that it is important for professors
using any measurement procedure or tool to validate content, procedures, etc.
externally in the purest sense of measurement or student assessment. That,
however, takes more time to execute with a faculty learning community and,
in our opinion, would be part of a Stage II faculty development program. Our
focus was on test analysis, writing better objective tests as well as better and
higher level items to include problem solving items. In addition, our program
focused on introducing them to the design, development, and use of
performance tasks and rubrics as one type of learning measurement procedure
or tool.
2. How are professors using the tests and performance task(s)? In our case, we
encouraged them to design new tests with more items, a wider range of item
types, and items that offer the opportunity to perform at various levels of
Bloom’s learning (e.g., memory to synthesis). We then asked them to design
and develop corresponding performance tasks and rubrics to provide students
the opportunity to provide evidence of learning through performances.
a. Do they feel that the objective tests are indicators of what students
know and the performance tasks take the students to the next level
where they are positioned to more deeply or critically use the
knowledge measured on the objective tests?
b. Do they feel that they can better measure some types of knowledge
with objective tests and other types of knowledge through
performances?
c. Other considerations
3. What might the correlation scores mean? How can they be used?
a. The correlation scores might have no or little meaning.
b. The scores might provide insight about students.
c. The scores might stimulate diagnostic thoughts about student
assessment.
31
Table B.9.c.1:
Professor = Ibrahim Abdel-Motaleb
Correlations(b) -- Including Zero Scores
Midterm
Final
PA1
PA2
PA3
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Midterm
1
24
.(a)
.
0
0.263
0.238
22
.(a)
.
0
.(a)
.
0
Final
.(a)
.
0
.(a)
0
.(a)
.
0
.(a)
.
0
.(a)
.
0
PA1
0.263
0.238
22
.(a)
.
0
1
22
.(a)
.
0
.(a)
.
0
PA2
.(a)
.
0
.(a)
.
0
.(a)
.
0
.(a)
0
.(a)
.
0
PA3
.(a)
.
0
.(a)
.
0
.(a)
.
0
.(a)
.
0
.(a)
0
a. Cannot be computed because at least one of the variables is constant.
b. Professor = Ibrahim Abdel-Motaleb
Correlations(b) -- With Blanks Replacing Zeros
Midterm
Final
PA1
PA2
PA3
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Midterm
1
24
.(a)
.
0
0.263
0.238
22
.(a)
.
0
.(a)
.
0
Final
.(a)
.
0
.(a)
0
.(a)
.
0
.(a)
.
0
.(a)
.
0
PA1
0.263
0.238
22
.(a)
.
0
1
22
.(a)
.
0
.(a)
.
0
a. Cannot be computed because at least one of the variables is constant.
b. Professor = Ibrahim Abdel-Motaleb
32
PA2
.(a)
.
0
.(a)
.
0
.(a)
.
0
.(a)
0
.(a)
.
0
PA3
.(a)
.
0
.(a)
.
0
.(a)
.
0
.(a)
.
0
.(a)
0
Table B.9.c.2:
Professor = Abul Azad
Correlations(a) -- Including Zero Scores
Midterm
Final
PA1
PA2
PA3
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Midterm
1
15
0.388
0.153
15
.739(**)
0.002
15
0.509
0.053
15
.614(*)
0.015
15
Final
0.388
0.153
15
1.000
15
.592(*)
0.020
15
0.430
0.110
15
.604(*)
0.017
15
PA1
.739(**)
0.002
15
.592(*)
0.020
15
1
15
.526(*)
0.044
15
.922(**)
0.000
15
PA2
0.509
0.053
15
0.430
0.110
15
.526(*)
0.044
15
1.000
15
0.410
0.129
15
PA3
.614(*)
0.015
15
.604(*)
0.017
15
.922(**)
0.000
15
0.410
0.129
15
1.000
15
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
a. Professor = Abul Azad
Correlations(a) -- With Blanks Replacing Zeros
Midterm
Final
PA1
PA2
PA3
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Midterm
1
15
0.425
0.130
14
.739(**)
0.002
15
0.509
0.053
15
-0.114
0.698
14
Final
0.425
0.130
14
1.000
14
.759(**)
0.002
14
0.327
0.254
14
0.483
0.094
13
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
a. Professor = Abul Azad
33
PA1
.739(**)
0.002
15
.759(**)
0.002
14
1
15
.526(*)
0.044
15
0.202
0.489
14
PA2
0.509
0.053
15
0.327
0.254
14
.526(*)
0.044
15
1.000
15
0.061
0.835
14
PA3
-0.114
0.698
14
0.483
0.094
13
0.202
0.489
14
0.061
0.835
14
1.000
14
Table B.9.c.3:
Professor = Brianno Coller
Correlations(a) -- Including Zero Scores
Midterm
Final
PA1
PA2
PA3
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Midterm
1
78
.610(**)
0.000
78
.390(**)
0.000
78
0.159
0.165
78
.320(**)
0.004
78
Final
.610(**)
0.000
78
1.000
78
.414(**)
0.000
78
0.134
0.242
78
.805(**)
0.000
78
PA1
.390(**)
0.000
78
.414(**)
0.000
78
1
78
0.156
0.172
78
.330(**)
0.003
78
PA2
0.159
0.165
78
0.134
0.242
78
0.156
0.172
78
1.000
78
0.111
0.333
78
PA3
.320(**)
0.004
78
.805(**)
0.000
78
.330(**)
0.003
78
0.111
0.333
78
1.000
78
**. Correlation is significant at the 0.01 level (2-tailed).
a. Professor = Brianno Coller
Correlations(a) -- With Blanks Replacing Zeros
Midterm
Final
PA1
PA2
PA3
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Midterm
1
78
.711(**)
0.000
71
.371(**)
0.001
76
0.159
0.165
78
.257(*)
0.028
73
Final
.711(**)
0.000
71
1.000
71
.331(**)
0.005
70
0.075
0.536
71
0.168
0.161
71
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
a. Professor = Brianno Coller
34
PA1
.371(**)
0.001
76
.331(**)
0.005
70
1
76
0.135
0.245
76
.318(**)
0.006
72
PA2
0.159
0.165
78
0.075
0.536
71
0.135
0.245
76
1.000
78
0.131
0.270
73
PA3
.257(*)
0.028
73
0.168
0.161
71
.318(**)
0.006
72
0.131
0.270
73
1.000
73
Table B.9.c.4:
Professor = Abhijit Gupta
Correlations(a) -- Including Zero Scores
Midterm
Final
PA1
PA2
PA3
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Midterm
1
44
.544(**)
0.000
44
0.081
0.602
44
-0.056
0.716
44
-0.123
0.425
44
Final
.544(**)
0.000
44
1.000
44
.304(*)
0.045
44
0.045
0.773
44
0.076
0.626
44
PA1
0.081
0.602
44
.304(*)
0.045
44
1
44
-0.045
0.773
44
-0.073
0.638
44
PA2
-0.056
0.716
44
0.045
0.773
44
-0.045
0.773
44
1.000
44
-0.003
0.982
44
PA3
-0.123
0.425
44
0.076
0.626
44
-0.073
0.638
44
-0.003
0.982
44
1.000
44
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
a. Professor = Abhijit Gupta
Correlations(a) -- With Blanks Replacing Zeros
Midterm
Final
PA1
PA2
PA3
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Midterm
1
44
.544(**)
0.000
44
0.081
0.602
44
-0.056
0.716
44
-0.123
0.425
44
Final
.544(**)
0.000
44
1.000
44
.304(*)
0.045
44
0.045
0.773
44
0.076
0.626
44
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
a. Professor = Abhijit Gupta
35
PA1
0.081
0.602
44
.304(*)
0.045
44
1
44
-0.045
0.773
44
-0.073
0.638
44
PA2
-0.056
0.716
44
0.045
0.773
44
-0.045
0.773
44
1.000
44
-0.003
0.982
44
PA3
-0.123
0.425
44
0.076
0.626
44
-0.073
0.638
44
-0.003
0.982
44
1.000
44
Table B.9.c.5:
Professor = Reinaldo Moraga
Correlations(a) -- Including Zero Scores
Midterm
Final
PA1
PA2
PA3
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Midterm
1
18
.777(**)
0.000
18
.532(*)
0.023
18
0.178
0.479
18
0.130
0.608
18
Final
.777(**)
0.000
18
1.000
18
0.149
0.554
18
0.293
0.238
18
0.110
0.663
18
PA1
.532(*)
0.023
18
0.149
0.554
18
1
18
0.074
0.771
18
0.214
0.395
18
PA2
0.178
0.479
18
0.293
0.238
18
0.074
0.771
18
1.000
18
.874(**)
0.000
18
PA3
0.130
0.608
18
0.110
0.663
18
0.214
0.395
18
.874(**)
0.000
18
1.000
18
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
a. Professor = Reinaldo Moraga
Correlations(a) -- With Blanks Replacing Zeros
Midterm
Final
PA1
PA2
PA3
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Midterm
1
18
.777(**)
0.000
18
.532(*)
0.023
18
0.186
0.490
16
-0.331
0.194
17
Final
.777(**)
0.000
18
1.000
18
0.149
0.554
18
0.458
0.075
16
-0.241
0.352
17
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
a. Professor = Reinaldo Moraga
36
PA1
.532(*)
0.023
18
0.149
0.554
18
1
18
-0.177
0.511
16
-0.171
0.511
17
PA2
0.186
0.490
16
0.458
0.075
16
-0.177
0.511
16
1.000
16
0.254
0.343
16
PA3
-0.331
0.194
17
-0.241
0.352
17
-0.171
0.511
17
0.254
0.343
16
1.000
17
Table B.9.c.6:
Professor = Regina Rahn
Correlations(a) -- Including Zero Scores
Midterm
Final
PA1
PA2
PA3
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Midterm
1
14
.626(*)
0.017
14
0.510
0.062
14
.662(**)
0.010
14
.590(*)
0.026
14
Final
.626(*)
0.017
14
1.000
14
.575(*)
0.031
14
.637(*)
0.014
14
.560(*)
0.037
14
PA1
0.510
0.062
14
.575(*)
0.031
14
1
14
0.478
0.084
14
0.375
0.186
14
PA2
.662(**)
0.010
14
.637(*)
0.014
14
0.478
0.084
14
1.000
14
.785(**)
0.001
14
PA3
.590(*)
0.026
14
.560(*)
0.037
14
0.375
0.186
14
.785(**)
0.001
14
1.000
14
*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).
a. Professor = Regina Rahn
Correlations(a) -- With Blanks Replacing Zeros
Midterm
Final
PA1
PA2
PA3
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Midterm
1
14
.626(*)
0.017
14
0.510
0.062
14
.662(**)
0.010
14
.590(*)
0.026
14
Final
.626(*)
0.017
14
1.000
14
.575(*)
0.031
14
.637(*)
0.014
14
.560(*)
0.037
14
*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).
a. Professor = Regina Rahn
37
PA1
0.510
0.062
14
.575(*)
0.031
14
1
14
0.478
0.084
14
0.375
0.186
14
PA2
.662(**)
0.010
14
.637(*)
0.014
14
0.478
0.084
14
1.000
14
.785(**)
0.001
14
PA3
.590(*)
0.026
14
.560(*)
0.037
14
0.375
0.186
14
.785(**)
0.001
14
1.000
14
Table B.9.c.7:
Professor = Robert Tatara
Correlations(a) -- Including Zero Scores
Midterm
Final
PA1
PA2
PA3
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Midterm
1
28
.425(*)
0.024
28
-0.126
0.524
28
0.101
0.608
28
0.209
0.285
28
Final
.425(*)
0.024
28
1.000
28
-0.099
0.618
28
.543(**)
0.003
28
.620(**)
0.000
28
PA1
-0.126
0.524
28
-0.099
0.618
28
1
28
0.311
0.108
28
-0.003
0.987
28
PA2
0.101
0.608
28
.543(**)
0.003
28
0.311
0.108
28
1.000
28
0.310
0.109
28
PA3
0.209
0.285
28
.620(**)
0.000
28
-0.003
0.987
28
0.310
0.109
28
1.000
28
*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).
a. Professor = Robert Tatara
Correlations(a) -- With Blanks Replacing Zeros
Midterm
Final
PA1
PA2
PA3
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Midterm
1
28
.425(*)
0.024
28
-0.126
0.524
28
0.101
0.608
28
0.209
0.285
28
Final
.425(*)
0.024
28
1.000
28
-0.099
0.618
28
.543(**)
0.003
28
.620(**)
0.000
28
*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).
a. Professor = Robert Tatara
38
PA1
-0.126
0.524
28
-0.099
0.618
28
1
28
0.311
0.108
28
-0.003
0.987
28
PA2
0.101
0.608
28
.543(**)
0.003
28
0.311
0.108
28
1.000
28
0.310
0.109
28
PA3
0.209
0.285
28
.620(**)
0.000
28
-0.003
0.987
28
0.310
0.109
28
1.000
28