Quantitative Literacy
Assessment
At Kennedy King College
Fall 2013
Prepared by Robert Rollings, spring 2014
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Quantitative Literacy Assessment
In fall 2013, 567 KKC students participated in an assessment of success in the following objectives:
1. Demonstrate understanding of mathematical processes by applying to real
world phenomenon through engage in critical literacy
2. Apply mathematical exposition, including descriptions of algorithms and
derivations of formulas, presented either orally or in writing
3. Determine whether a theorem or definition applies to a given situation, and use
it appropriately if it applies
4. Analyze mathematical models in written language, in symbolic form, in graphic
form, and interpret the solutions
The assessment consisted of 11 questions concerning a student’s math history and demographics, 4 questions
concerning attitudes toward math, and 10 math problems designed to test the above learning outcomes.
Following a presentation of raw survey results, this report
will examine correlations to determine which variables (if
any) best predict student performance.
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Demographics
Survey respondents were reasonably representative of the student body as a
whole, except for a disproportionate inclusion of full-time students.
# of Respondents by Credit Hours Completed
170
180
# of Respondents by
Enrollment Status
# of Respondents by
Gender
456
365
160
202
143
111
140
120
Male
Part-Time
Female
Full-Time
100
77
80
Have you ever had to repeat a math course?
64
63
50
60
No
40
20
464
Yes
103
0
12 or less
13-25
26-38
39-51
52-64
0
65 or more
100
510
162
122
150
300
100
200
50
100
0
2
1
22
15
15
1
0
500
250
200
400
400
276
300
500
300
# of Respondents by Age Category
# of Respondents by Race/Ethnicity
600
200
4
3
17 or less
18-26
27-40
41-60
61 or more
0
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# Respondents by Math Enrollment
or Eligibility
252
300
Attitudes
toward
Math
229
200
84
100
0
Dev Ed
Math 118-140 Math 141-299
239
400
309
176
200
82
0
0
I need a good understanding of math to
achieve my career goals.
300
# Respondents by Math Courses
already Completed
1 to 2
3+
Solving some mathematical problems involves
knowing different strategies to try.
260
400
294
300
200
252
200
100
14
54
100
Strongly Disagree
Disagree
Agree
Strongly Agree
15
Strongly Disagree
Disagree
299
300
172
200
82
176
200
106
100
14
22
0
Strongly Disagree
Strongly Agree
263
300
400
Agree
Mathematics has been an important tool to
help me learn other subjects.
Mathematical thinking helps me make intelligent
decisions about my life.
100
6
0
0
Disagree
Agree
Strongly Agree
0
Strongly Disagree
Students broadly agreed with the value of math, but they did not
agree as strongly with its value for life decisions or for learning in
other subjects as they agreed with its necessity for their careers.
Disagree
Agree
Strongly Agree
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Assessment Results
Students overall appear to have found the math assessment quite challenging. The top score of all 567
respondents was a 93%, and the average overall score was 36%
The ten math problems addressed a varying set of the four SLOs, with all questions addressing SLO 1.
Average scores on the math assessment, divided by learning objectives, are as follows:
Standard Deviation
in Percentage Points
Average Success according to SLO
SLO 1: Demonstrate understanding of mathematical
processes by applying to real world phenomenon through
engage in critical literacy
17%
36%
SLO 2: Apply mathematical exposition, including
descriptions of algorithms and derivations of formulas,
presented either orally or in writing
25%
17%
SLO 3: Determine whether a theorem or definition applies
to a given situation, and use it appropriately if it applies
41%
SLO 4: Analyze mathematical models in written language, in
symbolic form, in graphic form, and interpret the solutions
19%
31%
0%
5%
10%
15%
20%
25%
30%
These low-sounding numbers do not necessarily mean that students
perform poorly at these skills; such an assessment is impossible
without some manner of benchmark for comparison. However, we
can say that our students on the whole performed better at applying
theorems to a given situation than at mathematical exposition.
35%
15%
40%
45%
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With which variables did student success correlate?
Women slightly outperformed men (with 37% versus 35% average success).
Older students slightly outperformed younger students.
Students in math-heavy majors (measured roughly on a scale of 1-10) outperformed
students in less math-heavy majors.
Students who believed that math helps them make intelligent decisions in life
outperformed students who did not—and by a more significant margin than agreement
with the questions concerning careers, learning, or problem strategies (p<.0002).
The best predictor of a high score was math enrollment or eligibility; the direct
correlation had a p<.0000004 and an R of .043 in a linear regression.
In other words, students enrolled or eligible in higher math classes scored better on the
assessment.
This obvious-sounding point becomes more telling in light of what is not correlated:
number of credit hours and number of math classes taken at KKC.
No statistically significant relationship exists between having taken classes (or math
classes specifically) at KKC and succeeding on this assessment.
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This presentation is currently a work in progress.
How can Kennedy King and its math classes teach the practical reasoning skills
relevant to this assessment?
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