1 Week 5: Quantitative Analysis Assignment Instructions: Quantitative Analysis Assignment For the Week 5 quantitative analysis assignment, you will need to conduct basic descriptive analyses about the frequency of patient safety incidents during one month on two medical units in a major urban teaching hospital. To complete this assignment, you will need the following three documents: (a) Excel Spreadsheet: Quantitative Patient Safety Data, (b) Codebook: Quantitative Patient Safety Data, and (c) Summary Data Analysis Form. Below is a description of each of these documents: (a) Excel Spreadsheet: Quantitative Patient Safety Data: The quantitative data for this assignment has been entered into an Excel spreadsheet which can be accessed using the Excel software that is part of the Microsoft Office suite of applications. This type of spreadsheet is called a rectangular file because it is arranged in columns and rows. Each column is a different variable in the data set. For example, Column A (ID) is the identification number variable for patients, and Column B (AGE) is the variable on patient age in years. Each row has data (or information) for each individual patient for each of the variables in the columns. To clarify this, look at the date set for this assignment. You will see that the patient in row 2 has an ID number 001 (Column A) and is 22 years old (Column B). The patient in row 44 has an ID number 43 is 75 years old. (b) Codebook: Quantitative Patient Safety Data: A codebook is used in quantitative research to define the variables (or columns) in a data set and the response categories for each of these variable. Looking at the codebook for this assignment, you will see that the second column in the codebook is the name of variables in the data set. Usually the variable names are abbreviated (e.g., DX stands for primary diagnosis upon admission). Next to each variable name is its description and its response categories. As an example, look at the variable called FALLS. Next to this variable is its description which is defined as whether or not a patient had an accidental fall during the hospitalization. The response categories for the variable FALLS is either “0” which means the patient did not fall or “1” which means the patient did fall. To further clarify this, take a look at Column G on your Excel spreadsheet which is labelled as FALLS. The term “falls” can mean many different things, such as a person accidentally falling at home or a waterfall (e.g., Snoqualmie Falls). The codebook for a quantitative data set gives the specific definition of a variable. In this assignment, the variable FALLS means a patient fall that is reported during a hospitalization. Now look at the numbers in the column underneath FALLS. You will only see the numbers “0” or 2 “1”. In the codebook, these are the response categories for the variable ...

1. 1
Week 5: Quantitative Analysis Assignment
Instructions: Quantitative Analysis Assignment
For the Week 5 quantitative analysis assignment, you will need
to conduct basic
descriptive analyses about the frequency of patient safety
incidents during one month
on two medical units in a major urban teaching hospital. To
complete this assignment,
you will need the following three documents: (a) Excel
Spreadsheet: Quantitative
Patient Safety Data, (b) Codebook: Quantitative Patient Safety
Data, and (c) Summary
Data Analysis Form. Below is a description of each of these
documents:
(a) Excel Spreadsheet: Quantitative Patient Safety Data: The
quantitative data for this
assignment has been entered into an Excel spreadsheet which
can be accessed using

2. the Excel software that is part of the Microsoft Office suite of
applications. This type of
spreadsheet is called a rectangular file because it is arranged in
columns and rows.
Each column is a different variable in the data set. For
example, Column A (ID) is the
identification number variable for patients, and Column B
(AGE) is the variable on
patient age in years. Each row has data (or information) for
each individual patient for
each of the variables in the columns.
To clarify this, look at the date set for this assignment. You
will see that the patient in
row 2 has an ID number 001 (Column A) and is 22 years old
(Column B). The patient in
row 44 has an ID number 43 is 75 years old.
(b) Codebook: Quantitative Patient Safety Data: A codebook is
used in quantitative
research to define the variables (or columns) in a data set and
the response categories
for each of these variable. Looking at the codebook for this
assignment, you will see
that the second column in the codebook is the name of variables

3. in the data set.
Usually the variable names are abbreviated (e.g., DX stands for
primary diagnosis upon
admission). Next to each variable name is its description and
its response categories.
As an example, look at the variable called FALLS. Next to this
variable is its description
which is defined as whether or not a patient had an accidental
fall during the
hospitalization. The response categories for the variable
FALLS is either “0” which
means the patient did not fall or “1” which means the patient
did fall.
To further clarify this, take a look at Column G on your Excel
spreadsheet which is
labelled as FALLS. The term “falls” can mean many different
things, such as a person
accidentally falling at home or a waterfall (e.g., Snoqualmie
Falls). The codebook for a
quantitative data set gives the specific definition of a variable.
In this assignment, the
variable FALLS means a patient fall that is reported during a
hospitalization. Now look
at the numbers in the column underneath FALLS. You will only

4. see the numbers “0” or
2
“1”. In the codebook, these are the response categories for the
variable FALLS with 0 =
no fall and 1 = fall occurred.
Now that you know about the rows and columns of a rectangular
data set, you are ready
to conduct some basic analyses that summarize (or aggregate)
information about the 50
patients in the patient safety data.
(c) Summary Data Analysis Form: This form provides
guidelines on how to conduct the
required quantitative analyses for this assignment and how to
report your findings.
When you complete your analyses, you need to submit this
completed form using the
Week 5 platform for submitting assignments.
2

5. Title of the Paper in Full Goes Here
Student’s Full Name
School
Course Number, Section, and Title
Month, Day, Year
(enter the date submitted to instructor)
Week 5: Quantitative Analysis Assignment
Summary Data Analysis Form
This is the form you need to use to describe the findings (or
results) of your quantitative analyses of the patient safety data
set. For each finding, you are given specific instructions on how
to use the Excel program to analyze the data that will give you
the results you need for this Assignment. When you have
completed the analyses and described your findings on this
form, you then need to submit it using the Week 5 platform for
assignments.

6. Analysis 1:
What is the mean age of patients in the patient safety data set?
_____ years
Instructions:
a) Open up your patient safety data set using the Microsoft
Excel program.
b) At the top of your screen, click on “Formulas.”
c) Highlight Column B, starting at line 2 and ending at line 52.
d) Click on “Autosum,” and then click on “Average.”
e) You will find the mean age of patients in the data set on line
52 for Column B.
Analysis 2:
What percentage of patients were reported to have fallen during
their hospitalization?
_____ %
Instructions:
a) Open up your patient safety data set using the Microsoft
Excel program.
b) At the top of your screen, click on “Formulas.”
c) Highlight Column G, starting at line 2 and ending at line 52.
d) Click on “Sum.”
e) The number of patients in the data set who had reported falls
during their hospitalization is now given on line 52 for Column
G.
f) To calculate the percentage of patients who fell during their
hospitalization, divide the number of falls by the total number
of patients in the data set (n = 50).
Analysis 3:
What percentage of patients reported catheter-associated urinary
tract infections (CAUTIs) during their hospitalization?
_____ %
Instructions:

7. a) Open up your patient safety data set using the Microsoft
Excel program.
b) At the top of your screen, click on “Formulas.”
c) Highlight Column H, starting at line 2 and ending at line 52.
d) Click on “Sum.”
e) The number of patients in the data set who reported CAUTIs
during their hospitalization is now given on line 52 for Column
H.
f) To calculate the percentage of patients with CAUTIs during
their hospitalization, divide the number of CAUTIs by the total
number of patients in the data set (n = 50).
Analysis 4:
What percentage of patients reported medication errors during
their hospitalization?
_____ %
Instructions:
a) Open up your patient safety data set using the Microsoft
Excel program.
b) At the top of your screen, click on “Formulas.”
c) Highlight Column I, starting at line 2 and ending at line 52.
d) Click on “Sum.”
e) The number of patients in the data set who reported
medication errors during their hospitalization is now given on
line 52 for Column I.
f) To calculate the percentage of patients with reported
medication errors during their hospitalization, divide the
number of errors by the total number of patients in the data set
(n = 50).
Analysis 5:
What percentage of patients reported methicillin-resistant
Staphylococcus aureus (MRSA) infections when first admitted
to the medical unit?
_____ %

8. Instructions:
a) Open up your patient safety data set using the Microsoft
Excel program.
b) At the top of your screen, click on “Formulas.”
c) Highlight Column J, starting at line 2 and ending at line 52.
d) Click on “Sum.”
e) The number of patients in the data set who reported MRSA
infections at the beginning of their hospitalization is now given
on line 52 for Column J.
f) To calculate the percentage of patients with MRSA, divide
the number of errors by the total number of patients in the data
set (n = 50).
Data Analysis
Summarize the findings from your analyses about these patient
safety events that occurred in 1 month on the two medical units
at this major urban hospital. What additional information would
you need to help develop a plan to decrease the occurrence of
these events? The summary should consist of a minimum of 350
words and should be two to three paragraphs.

9. Reference
Gray, J. R, Grove, S. K., & Sutherland, S. (2017). The practice
of nursing research: Appraisal,
synthesis, and generation of evidence (8th ed.). St. Louis, MO:
Elsevier.
Week 5: Quantitative Analysis Assignment
Code Book: Quantitative Patient Safety Data
Column
Variable
Name
Description

10. Response Categories
A ID Unique patient identification number
B AGE Age of patient in years
C GENDER Sex of patient 1 = female; 2 = male
D EDUC Educational level of patient Education in years
completed
E UNIT Inpatient hospital unit 1 = medical unit 1
2 = medical unit 2
F DX Primary diagnosis of patient when
admitted to medical unit
1 = congestive heart failure
2 = pneumonia
3 = chronic obstructive
pulmonary disease
4 = diabetes
5 = R/O myocardial
infarction
6 = other
G FALLS Reported fall during hospitalization 0 = no fall
1 = fell
H CAUTI Reported catheter-associated
urinary tract infection
0 = no CAUTI
1 = CAUTI

11. I RXERR Reported medication error during
hospitalization
0 = no medication error
1 = medication error
J MRSA Reported methicillin-resistant
Staphylococcus aureus (MRSA)
infection
0 = no MRSA
1 = MRSA infection
Week 5: Qualitative Analysis Assignment
Student Narrative Text on Course Pet Peeves
001 Professors who “don’t allow” students to disagree with
their opinions. |
Professors who grade based on the placement of commas and
the number of
spaces typed between words rather than on the ideas and
thoughts developed. |
Professors who give me reason to feel about 2 inches tall when I
give an
incorrect answer to a question.

12. 002 Ridiculous amounts of reading to be done in a short period
of time. |
Not having an opportunity to discuss different
viewpoints or different facets of a
topic-issue.
003 I get frustrated with instructors that behave as though
we have nothing else
going on in our lives except their class and their assignments.
004 I don’t like to read material that doesn’t have a practical
benefit. I want to leave
here with a marketable skill, not a head filled with historical
facts or scientific
jargon.
005 Students who use the classroom to show how smart they are
and to build
themselves up. |
Those who rattle their candy and gum wrapper or chip bag.
006 When required readings are not available. |
When instructors put-down students. |
When assignments are too difficult.
007 Professor who believe their view is the only one acceptable.
|
Disorganized classes. |

13. Dry readings.
008 Professors who are condescending toward students. |
Test questions that come out of the blue.
009 People make noise – opening snacks, chewing loud
(pretzels). |
When people monopolize class.
010 Allowing personal bias to dictate evaluations of students
work. (i.e. if you
disagree then you’re wrong.) |
When expectations are unclear for grades.
Week 5: Qualitative Analysis Assignment
Instructions: Content Coding of Student Pet Peeves
Content coding is one way to identify the themes or patterns
found in the narrative text of qualitative research studies. The
qualitative research assignment for Week 5 requires you to
content code the narrative pet peeves of 10 nursing and social
work students taking courses in a “brick and mortar” university.
These students were asked to anonymously describe the
problems (or “pet peeves”) they experienced in previous courses
that detracted from their learning experience.
To complete this assignment, you need the three documents: the
student narrative text on pet peeves, the code scheme, and the
code sheet. Below is a description of each of these documents.
Student Narrative Text on Course Pet Peeves (Page 3): You will

14. see the narrative text written by each of the 10 students in this
document. Each student has a unique identification (ID)
number. For example, 001 is the ID number of the first student
and 010 is number for the last student. Some students only
wrote about one pet peeve, whereas others listed up to two or
more pet peeves. If a student listed two or more pet peeves, a
“vertical bar” | is used to separate each them. Take a look at
the student whose ID number is 002. This student’s first pet
peeve about course readings is separated from the second one by
a vertical bar ( | ).
Coding Scheme: Student Pet Peeve Data (Page 4): A code
scheme has unique numbers linked to different types of content
or themes found in narrative text. For this assignment, you will
see a unique number for each different type of pet peeve. For
example, a pet peeve on not being able to locate required
readings is assigned the number “01”. Sometimes the content of
narrative text cannot be categorized, because it is unclear or
doesn’t make sense. For this assignment, this type of narrative
text is given the code number “99”. If narrative text is not a pet
peeve, it is given the code number “97”.
Code Sheet: Student Pet Peeve Data (Page 5): This is the form
that you use to enter the code scheme number for each pet peeve
in a student’s narrative text. The first column of the code sheet
lists the student’s unique ID number. The next column (Code 1)
is used to write the number from the code scheme that best
describes the content of the first pet peeve listed by the student.
The second column (Code 2) is for the second pet peeve, and
the third column (Code 3) is for the last one.
Example
Here is an example of how to code the narrative text on course
pet peeves. In this example, the student described the following
pet peeves in courses she had taken in the past:

15. 186 Assignments that are just “busy work” with no
perceived value. |
Lack of feedback.
ID
First, the number “186” is the unique ID number for this
student. When you code this student’s pet peeves, you need to
write them on the line for this ID number.
Codes
Next you will see a vertical bar | in the narrative text on page 3
which means there are more than one pet peeve listed by the
student.
Code Sheet Example (Refer to Coding Scheme page 5)
The first pet peeve is about assignments that are considered to
be “busy work”. When you review the code scheme for student
pet peeves, it looks like the number “08” (Assignments not
geared to learning [e.g., busy work]) best describes this
student’s pet peeve. You then enter the number “08” into the
second column (Code 1) of the code sheet (see below).
In the next pet peeve, the student writes about “lack of
feedback”. While her response is not very specific, it is most
likely to related to code number “13” (Assignments returned
without comments or feedback). You then enter “13” in the
third column of the code sheet. Because this student did not list
a third pet peeve, you then leave the fourth column (Code 3)
blank.
Code Sheet: Student Pet Peeve Data
ID #
Code 1
Code 2
Code 3
186
08
13
You are now ready to start content coding the narrative text of

16. pet peeves for the 10 students in this assignment on page 3.
When you are finished, you need to submit your completed code
sheet on page 7 to the submission link in Week 5.
Week 5: Qualitative Analysis Assignment
Student Narrative Text on Course Pet Peeves
001 Professors who “don’t allow” students to disagree with
their opinions. |
Professors who grade based on the placement of commas and
the number of spaces typed between words rather than on the
ideas and thoughts developed. |
Professors who give me reason to feel about 2 inches tall when I
give an incorrect answer to a question.
002 Ridiculous amounts of reading to be done in a short period
of time. |
Not having an opportunity to discuss different viewpoints or
different facets of a topic-issue.
003 I get frustrated with instructors that behave as though we
have nothing else going on in our lives except their class and
their assignments.
004 I don’t like to read material that doesn’t have a practical
benefit. I want to leave here with a marketable skill, not a head
filled with historical facts or scientific jargon.
005 Students who use the classroom to show how smart they
are and to build themselves up. |
Those who rattle their candy and gum wrappers or chip bags.
006 When required readings are not available. |
When instructors put-down students. |
When assignments are too difficult.

17. 007 Professor who believe their view is the only one
acceptable. |
Disorganized classes. |
Dry readings.
008 Professors who are condescending toward students. |
Test questions that come out of the blue.
009 People make noise – opening snacks, chewing loud
(pretzels). |
When people monopolize class.
010 Allowing personal bias to dictate evaluations of students
work. (e.g., If you disagree, then you’re wrong.) |
When expectations for grades are unclear.
Week 5: Qualitative Analysis Assignment
Coding Scheme: Student Pet Peeve Data
Course Requirements
01 = Can’t locate required readings
02 = Unclear expectations of students
03 = Unrealistic expectations of students (e.g., too many
readings, assignments too difficult)
04 = Working in groups (e.g., too much, meaningless)
05 = Course doesn’t follow syllabus
Course Content
06 = Content of required readings (e.g., irrelevant,
inappropriate, boring, dry)
07 = No clinical, policy or real-life application of course
content
08 = Assignments not geared to learning (e.g., busy work)
09 = Too little time spent on the most important topics

18. Teacher - Student Relationship
10 = Teacher doesn’t encourage students to voice opinions that
are different from their own
11 = Teacher talks down to students (e.g., condescending,
makes students feel stupid)
12 = Teacher has low expectations of students (e.g.,
intelligence, experience, ability to complete assignments)
Teaching Behavior
13 = Assignments returned without comments or feedback (e.g.,
papers)
14 = Personality of teacher (e.g., opinionated, egotistical,
arrogant, thinks their approach is the only way)
15 = Unfair or inappropriate grading (e.g., papers, exams, final
grades)
16 = Poor facilitator of class discussions
Student Behavior
17 = Students who monopolize class time
18 = Irrelevant comments or discussions by other students (e.g.,
personal stories)
19 = Limited or no development of peer relationships with
classmates
20 = Overbearing, intimidating, and/or opinionated students
21 = Students making noises in class (e.g., rattling papers,
unwrapping food)
98 = Other: Student’s written response not a pet peeve or
doesn’t fit coding scheme
99 = Unable to decipher meaning of student response
Week 5: Qualitative Analysis Assignment
Code Sheet: Student Pet Peeve Data

19. Qualitative Analyses: The analytic method you will use to
analyze the narrative data for this Assignment is called content
analysis. It requires you to read each student’s narrative and
then code its content using the thematic categories on page 4
(Coding Scheme: Student Pet Peeve Data). Once you have
completed the coding, you will need to describe the most
common types of “pet peeves” that students have about their
courses.
ID #
CODE 1
CODE 2
CODE 3
001
002
003
004
005
006

20. 007
008
009
010
After you complete the code sheet, summarize the major themes
or most common pet peeves described by the 10 students in
their previous courses:
© 2016 Laureate Education, Inc. Page 5 of 5
Week 5: Qualitative Analysis Assignment
Instructions: Content Coding of Student Pet Peeves
Content coding is one way to identify the themes or patterns
found in the narrative text of qualitative research studies. The
qualitative research assignment for Week 5 requires you to
content code the narrative pet peeves of 10 nursing and social
work students taking courses in a “brick and mortar” university.
These students were asked to anonymously describe the
problems (or “pet peeves”) they experienced in previous courses
that detracted from their learning experience.

21. To complete this assignment, you need the three documents: the
student narrative text on pet peeves, the code scheme, and the
code sheet. Below is a description of each of these documents.
Student Narrative Text on Course Pet Peeves (Page 3): You will
see the narrative text written by each of the 10 students in this
document. Each student has a unique identification (ID)
number. For example, 001 is the ID number of the first student
and 010 is number for the last student. Some students only
wrote about one pet peeve, whereas others listed up to two or
more pet peeves. If a student listed two or more pet peeves, a
“vertical bar” | is used to separate each them. Take a look at
the student whose ID number is 002. This student’s first pet
peeve about course readings is separated from the second one by
a vertical bar ( | ).
Coding Scheme: Student Pet Peeve Data (Page 4): A code
scheme has unique numbers linked to different types of content
or themes found in narrative text. For this assignment, you will
see a unique number for each different type of pet peeve. For
example, a pet peeve on not being able to locate required
readings is assigned the number “01”. Sometimes the content of
narrative text cannot be categorized, because it is unclear or
doesn’t make sense. For this assignment, this type of narrative
text is given the code number “99”. If narrative text is not a pet
peeve, it is given the code number “97”.
Code Sheet: Student Pet Peeve Data (Page 5): This is the form
that you use to enter the code scheme number for each pet peeve
in a student’s narrative text. The first column of the code sheet
lists the student’s unique ID number. The next column (Code 1)
is used to write the number from the code scheme that best
describes the content of the first pet peeve listed by the student.
The second column (Code 2) is for the second pet peeve, and
the third column (Code 3) is for the last one.

22. Example
Here is an example of how to code the narrative text on course
pet peeves. In this example, the student described the following
pet peeves in courses she had taken in the past:
186 Assignments that are just “busy work” with no
perceived value. |
Lack of feedback.
ID
First, the number “186” is the unique ID number for this
student. When you code this student’s pet peeves, you need to
write them on the line for this ID number.
Codes
Next you will see a vertical bar | in the narrative text on page 3
which means there are more than one pet peeve listed by the
student.
Code Sheet Example (Refer to Coding Scheme page 5)
The first pet peeve is about assignments that are considered to
be “busy work”. When you review the code scheme for student
pet peeves, it looks like the number “08” (Assignments not
geared to learning [e.g., busy work]) best describes this
student’s pet peeve. You then enter the number “08” into the
second column (Code 1) of the code sheet (see below).
In the next pet peeve, the student writes about “lack of
feedback”. While her response is not very specific, it is most
likely to related to code number “13” (Assignments returned
without comments or feedback). You then enter “13” in the
third column of the code sheet. Because this student did not list
a third pet peeve, you then leave the fourth column (Code 3)
blank.
Code Sheet: Student Pet Peeve Data
ID #
Code 1
Code 2
Code 3

23. 186
08
13
You are now ready to start content coding the narrative text of
pet peeves for the 10 students in this assignment on page 3.
When you are finished, you need to submit your completed code
sheet on page 7 to the submission link in Week 5.
Week 5: Qualitative Analysis Assignment
Student Narrative Text on Course Pet Peeves
001 Professors who “don’t allow” students to disagree with
their opinions. |
Professors who grade based on the placement of commas and
the number of spaces typed between words rather than on the
ideas and thoughts developed. |
Professors who give me reason to feel about 2 inches tall when I
give an incorrect answer to a question.
002 Ridiculous amounts of reading to be done in a short period
of time. |
Not having an opportunity to discuss different viewpoints or
different facets of a topic-issue.
003 I get frustrated with instructors that behave as though we
have nothing else going on in our lives except their class and
their assignments.
004 I don’t like to read material that doesn’t have a practical
benefit. I want to leave here with a marketable skill, not a head
filled with historical facts or scientific jargon.
005 Students who use the classroom to show how smart they

24. are and to build themselves up. |
Those who rattle their candy and gum wrappers or chip bags.
006 When required readings are not available. |
When instructors put-down students. |
When assignments are too difficult.
007 Professor who believe their view is the only one
acceptable. |
Disorganized classes. |
Dry readings.
008 Professors who are condescending toward students. |
Test questions that come out of the blue.
009 People make noise – opening snacks, chewing loud
(pretzels). |
When people monopolize class.
010 Allowing personal bias to dictate evaluations of students
work. (e.g., If you disagree, then you’re wrong.) |
When expectations for grades are unclear.
Week 5: Qualitative Analysis Assignment
Coding Scheme: Student Pet Peeve Data
Course Requirements
01 = Can’t locate required readings
02 = Unclear expectations of students
03 = Unrealistic expectations of students (e.g., too many
readings, assignments too difficult)
04 = Working in groups (e.g., too much, meaningless)
05 = Course doesn’t follow syllabus
Course Content

25. 06 = Content of required readings (e.g., irrelevant,
inappropriate, boring, dry)
07 = No clinical, policy or real-life application of course
content
08 = Assignments not geared to learning (e.g., busy work)
09 = Too little time spent on the most important topics
Teacher - Student Relationship
10 = Teacher doesn’t encourage students to voice opinions that
are different from their own
11 = Teacher talks down to students (e.g., condescending,
makes students feel stupid)
12 = Teacher has low expectations of students (e.g.,
intelligence, experience, ability to complete assignments)
Teaching Behavior
13 = Assignments returned without comments or feedback (e.g.,
papers)
14 = Personality of teacher (e.g., opinionated, egotistical,
arrogant, thinks their approach is the only way)
15 = Unfair or inappropriate grading (e.g., papers, exams, final
grades)
16 = Poor facilitator of class discussions
Student Behavior
17 = Students who monopolize class time
18 = Irrelevant comments or discussions by other students (e.g.,
personal stories)
19 = Limited or no development of peer relationships with
classmates
20 = Overbearing, intimidating, and/or opinionated students
21 = Students making noises in class (e.g., rattling papers,
unwrapping food)
98 = Other: Student’s written response not a pet peeve or
doesn’t fit coding scheme

26. 99 = Unable to decipher meaning of student response
Week 5: Qualitative Analysis Assignment
Code Sheet: Student Pet Peeve Data
Qualitative Analyses: The analytic method you will use to
analyze the narrative data for this Assignment is called content
analysis. It requires you to read each student’s narrative and
then code its content using the thematic categories on page 4
(Coding Scheme: Student Pet Peeve Data). Once you have
completed the coding, you will need to describe the most
common types of “pet peeves” that students have about their
courses.
ID #
CODE 1
CODE 2
CODE 3
001
002
003
004
005

27. 006
007
008
009
010
After you complete the code sheet, summarize the major themes
or most common pet peeves described by the 10 students in
their previous courses:
© 2016 Laureate Education, Inc. Page 1 of 5
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010054.8
Sheet2
Sheet3