2. Epistemological Journey
How can we collect data?
How can we interpret data?
How can we present data?
Have you ever considered
whether the data and the
evidence you collected is valid
and reliable?
How do you determine validity
and reliability in quantitative
research?
And what does it mean to have
trustworthy information in
qualitative research?

4. NOT EVERYTHING THAT CAN BE
COUNTED COUNTS,
AND NOT EVERYTHING THAT COUNTS
CAN BE COUNTED.
William Bruce Cameron

6. Lack of specificity Poorly Defined Research Problem
Significance
Relationshipbetweenstudyandexistingwork
Contribution to the Field Objective or Questions Poor Method
ProximitySampling
Instruments
StatisticalAnalysis
Vocabulary
Ethics
Limitations of Study

8. Research Protocol
1. Aims and Objectives
2. Background- Why is this interesting, relevant, etc.
3. Methods- How with detailed description of data,
including the setting, participants, analysis
4. Ethical issues- Human subjects, confidentiality
5. Resources- cost, skills, man-hours, computing time,
etc.
6. Time scale- each phase of the project
7. Dissemination- who will you target and how will you
disseminate

12. Criteria Qualitative Research Quantitative Research
Purpose To understand & interpret social interactions. To test hypotheses, look at cause & effect, &
make predictions.
Group Studied Smaller & not randomly selected. Larger & randomly selected.
Variables Study of the whole, not variables. Specific variables studied
Type of Data Collected Words, images, or objects. Numbers and statistics.
Form of Data Collected Qualitative data such as open- ended responses,
interviews, participant observations, field notes, &
reflections.
Quantitative data based on precise
measurements using structured & validated data-
collection instruments.
Type of Data Analysis Identify patterns, features, themes. Identify statistical relationships.
Objectivity and Subjectivity Subjectivity is expected. Objectivity is critical.
Role of Researcher Researcher & their biases may be known to
participants in the study, & participant
characteristics may be known to the researcher.
Researcher & their biases are not known to
participants in the study, & participant
characteristics are deliberately hidden from the
researcher (double blind studies).
Results Particular or specialized findings that is less
generalizable.
Generalizable findings that can be applied to
other populations.
Scientific Method Exploratory or bottom–up: the researcher
generates a new hypothesis and theory from the
data collected.
Confirmatory or top-down: the researcher tests
the hypothesis and theory with the data.
View of Human Behavior Dynamic, situational, social, & personal. Regular & predictable.
Most Common Research
Objectives
Explore, discover, & construct. Describe, explain, & predict.
Focus Wide-angle lens; examines the breadth & depth of
phenomena.
Narrow-angle lens; tests a specific hypotheses.
Nature of Observation Study behavior in a natural environment. Study behavior under controlled conditions;
isolate causal effects.
Nature of Reality Multiple realities; subjective. Single reality; objective.
Final Report Narrative report with contextual description &
direct quotations from research participants.
Statistical report with correlations, comparisons
of means, & statistical

13. How to choose
Quantitative
• Answer you want is numerical –
how many people use our library
• Numerical change- Are the
number of people using our
library rising or falling?
• Examine factors related to a
change- What factors are predict
the lifelong usage of the library
for a person?
• Testing of Hypotheses- Is there a
relationship between childhood
library visits and adult library
usage?
Qualitative
• Explore a problem in depth- how
does a certain community relate to
a certain library
• Develop a hypotheses-
identification of an issue that you
want to generalize- people want
libraries even if they don’t use
them
• Particularly complex issues-
multiple variables- how libraries are
funded in county governments
• Looking at the meaning of events
or circumstances- the effect of low
pay on the status and esteem of the
library profession

14. Qualitative Methods
Participant Observation
In-depth Interviews
Focus Groups
Group Interviews
Talk through
Direct observation
Unstructured
interviews
Case studies
Content Analysis
Cognitive Mapping

15. Quantitative Methods
Measurements
Modeling
Experiments
Quasi- Experiments
Questionnaires
Surveys
Usability testing
Archival and Meta-Analysis

17. Is this the best tool?

18. 1.Participant
Information Sheet
2.Informed Consent
3.Survey
4.End Page

20. The data ultimately produced from
a survey are only as good as the
questionnaire, sample and data
collection process that produced
them

22. 1. Failing to Avoid Leading Words / Questions
Subtle wording differences can produce great differences in results.
“Could,” “should,” and “might” all sound about the same, but may
produce a 20% difference in agreement to a question.

23. 2. Failing to Give Mutually Exclusive Choices
Multiple choice response options should be mutually exclusive so that respondents can make
clear choices. Don’t create ambiguity for respondents.
Review your survey and identify ways respondents could get stuck with either too many or no
correct answers.
Example:
What is your age?
0–10
10–20
20–30
30–40
40+

24. 3. Not Asking Direct Questions
Questions that are vague and do not communicate your intent can limit the usefulness
of your results. Make sure respondents know what you’re asking.
Example:
What suggestions do you have for improving Smallville Library Service?

25. 4. Forgetting to Add a
“Prefer Not to Answer”
Option
Example:
What is your race?
What is your age?
What is your annual
household income?
These questions should be
asked only when absolutely
necessary. In addition, they
should always include an
option to not answer. (e.g.
“Prefer Not to Answer”).

26. 5. Failing to Cover All Possible Answer Choices
Do you have all of the options covered? If
you are unsure, conduct a pretest using
“Other (please specify)” as an option.
If more than 10% of respondents (in a
pretest or otherwise) select “other,” you
are probably missing an answer.
Review the “Other” text your test
respondents have provided and add the
most frequently mentioned new options
to the list.
What do you drive?:
a. Car
b. Truck

27. 6. Asking Double- Barreled Questions- Questions which contain more
than one concept or purpose should be simplified
Example: Do you think speed limits should be lowered for cars and trucks?

28. 7. Using scales incorrectly- making sure the scale
represents all possible answers, and making sure they are
equal-distant in width.