1. Tools of Research Chapter 2

2. Introduction
Tool: A specific mechanism or strategy the researcher uses
Methodology: is the general approach (how to) that is taken to carry out research

3. 6 General Tools of Research
Library and its resources
Computer and its software
Techniques of measurement
Statistics
Human mind
Language

4. 1. Library and Its Resources
In the past: libraries were confined to walls
With technology came expansion in information and accessibility (Virtual)
Libraries must continue to evolve to keep up with patrons

5. Good Old Day Libraries Card catalogs with titles and descriptions
3 index cards per book
Involved lots of walking and searching
(Painful!!!!)

6. Two different Classification Systems
Classification system- the Dewey decimal: Shelved according to ten basic areas of human knowledge, each divided decimally
The Library of Congress System: Assigned to particular areas of human knowledge given special alphabetical categories.

7. Library of the Present Everything can be found online instead of cards
Much of the data is in online forms and can even be accessed from home
Convenience!
No boundaries…

8. Indexes and Abstracts. Libraries have print and electronic versions
Online databases include indexes and abstracts, encyclopedias, dictionaries, books, websites, newspapers, and online journals.

9. The Reference Librarian
Purpose is to help you and others to find needed information (they know a lot of media retrieval secrets!)
They can show you how to use the computer catalog, online databases, paper and cd rom indexes, and any other resource.
Can magically find “peer-reviewed” articles for very unique, new and rare topics

10. Second Tool of Research: Computers
The personal computer over the past few decades has been a useful tool of research.
Unfortunately, a computer is not a miracle worker.

11. Computers and Internet Devices
You can access to the internet in many ways to research information
(I-Phone and I-Touch)

12. 3. Measurement Strive for objectivity
Don’t be influenced by your biases
It is a systematic way of measuring phenomenon being studied

13. Two Types of Measurement: a) Substantial b) Insubstantial
“Nothing Exists that the Researcher Cannot Measure” (Some are just more defined)
Two Types of Measurement:
a) Substantial
b) Insubstantial

14. Substantial
Substantial measurements are things being measured that have an obvious basis in the physical world.
Using Quantities: (a number and a unit)
The table is 15 inches long
Unbiased

15. Insubstantial
Abstract data that exist only as concepts, ideas, opinions, or feelings.
Example: asking someone for their opinion of something by asking them their feelings on the subject.
Very subjective and biased

16. Example
Question: How is President Obama doing so far in his administration?
Insubstantial answers: opinionated phrases.
Substantial answer: rating on a scale of 1 to 10. Assign a number to a phrase Ex:
1- one of America’s worst President’s
10- one of America’s greatest Presidents

17. Measurement Defined (pg. 24)
“Limiting the data of any phenomenon-substantial or insubstantial-so that those data may be interpreted and ultimately compared to an acceptable qualitative or quantitative standard”

18. Goal for Researcher
Measurement and collection of data is to be as OBJECTIVE as possible.
If data that is measured is not concrete or substantial, then QUANTIFY abstract or insubstantial data

19. Interpretation of Data
(Measurement – Continued)

20. Data Analysis- Measurement
Measurement is ultimately a comparison.
Any form of measurement falls into one of four categories.

21. 4 Scales of Measurement
1. Nominal
2. Ordinal
3. Interval
4. Ratio

22. Nominal Scale You assign names to data in order to measure it Example
Measuring a group of children
Divide into 2 groups: Girls and Boys
Each subgroup is thereby measured by a girl’s name or a boy’s name
Only a few statistics are appropriate for analyzing this kind of data: (frequencies, modes, % …Chi square)

23. Ordinal Scale
Compare pieces of data in terms of being greater > or less < than the others.
Example
Grades of proficiency
Skilled
Unskilled
Overskilled

24. Ordinal Scale Measurements are relative
Type of statistics used expands beyond nominal
Examples: Median, percentile rank; Spearman’ rank of Correlation

25. Interval Scale
Uses equal units of measurement
Its zero point is established arbitrarily
Example
Measuring temperature using Fahrenheit
Intervals between degrees reflect equal changes in temperature
The zero point is not a total absence of heat
Example: 0 degress Fahrenheit does not indicate absence of heat

26. Interval Scale
Uses any type of statistic using addition or subtraction because of the “equal “ interval
Uses means, standard deviations, Pearson Product Moment Correlation

27. Ratio Scale Equal measurement units
Absolute zero point: Absence of property
Can express values in terms of multiples or fractional parts
Example
Yardstick Kelvin Scale
3 feet = 1 yard Absolute Zero

28. Validity and Reliability of Measurement

29. Validity and Reliability
Validity and Reliability are the two terms most often used with measurement.

30. Validity
Validity is whether or not a tool of measurement has the ability to properly measure what it is suppose to measure.
Example: A test may be intended to measure a certain characteristic, and it may be called a measure of that characteristic, but these things don’t necessarily mean that the test actually measures what its authors say it does.
Example” Does an IQ test accurately measure all types of IQ’s? (academic IQ, social IQ, mechanical IQ, etc…

31. Reliability
When the conditions for measurement are consistent for each measurement.
Instruments used to measure insubstantial data are less reliable than substantial
Ex: On a teacher availability scale a student rates the same teacher a score of 60 one day when the teacher is less available and 95 a different day when the teacher is more available

32. Conclusion
Both reliability and validity reflect the degree to which we may have error in our measurements.
Validity errors are usually due to the instrument itself, and reliability errors are usually due to the use of the instrument.

33. 4. Statistics as a Tool of Research

34. Statistics as a Tool Often times statistics are used incorrectly
Ex. Not a large enough sample size to use parametric (Normal assumption)
When used correctly, they can help with data and research questions—can be misleading though when applied to other contexts

35. Statistics as a Tool (cont’d.)
Statistics are used in a variety of other fields (psychology, sociology, and education) but the data found in these subjects are primarily for numerical configurations (where they cluster, how broadly they spread, or how closely they are related)
Statistics give us info. about the data we find, but a continuous researcher is not satisfied until the meaning of the data is revealed.

36. The Lure of Statistics
For lots of new researchers, statistics have an elegant appeal, and subjecting data to statistical routines may lure these novices to believe they have made a substantial discovery when in fact they have really only calculated a few numbers.
Don’t be fooled by statistics—statistics are useful in helping to explain perhaps a particular aspect of what you are researching, but ultimately the entire body of data you have needs to be collected and analyzed.

37. Primary Functions of Statistics
2 principle functions of statistics:
Descriptive: helps the researcher describe data
Inferential: researcher makes inferences from the data

38. Primary Functions of Statistics
Descriptive statistics-summarize the general nature of the data obtained
Ex. How certain measured characteristics appear to be “on the average,” how much variability exists among different pieces of data, how closely 2+ characteristics are interrelated, etc.

39. Primary Functions of Statistics
Inferential statistics- help the researcher make decisions about the data
Ex. They help one decide whether the differences observed between 2 groups in an experiment are large enough to be attributed to experimental intervention rather than a once-in-a-blue-moon fluke

40. 5. The Human Mind as a Tool of Research
Deductive Logic
Inductive Logic
The Scientific Method
Critical Thinking
Collaboration with Others

41. Deductive Logic Begins with two or more premises
Premises are statements or assumptions that are self-evident and widely accepted “truths”
Premise1: All roses are plants
Premise 2: Plants produce energy through photosynthesis
Therefore, roses produce energy through photosynthesis

42. Inductive Logic Begins with an observation Then other observations
It uses many specific instances or observations to draw one GENERAL CONCLUSION
Example: If a survey was conducted for the Senior class on planning events and some wanted Prom, Sadie Hawkins Dance, Gala….it could be concluded that the Senior class likes dances.

43. The Scientific Method Observations or Searching Topics of Study
Identifying Problem and breaking down into sub problems
State Hypothesis/(es) for each subproblem
Propose a Plan for the Research Investigation
Gather Data (Surveys, interviews, research articles, experiments…)
Analyze Data: Involves Deductive and Deductive Reasoning
Support or Not Support Hypothesis
Conclusions

44. Critical Thinking Evaluating Information
Verbal Reasoning in oral and written language
Argument Analysis
Decision Making
Using Bloom’s Taxonomy (Knowledge, comprehension, application, synthesis, evaluation)
Dagget’s Model (Application)

45. Collaboration with Others
Two heads are better than one
Bring in colleagues or professionals in the field of study
Interviewing Professionals

46. 6. Language as a Tool

47. Meaning of Language (Oral & Written)
Language helps people represent their thoughts
Choose words carefully
Enhances the power of thought
Speaking 2 or more languages opens more opportunities

48. The Importance of Writing
The basic requirement for writing is the ability to use language in a clear, coherent manner.
Writing helps to record and organize thoughts.