2. Variables in Educational Research Most used term in research. Most used term in research. A variable is a label or name that represents a concept or characteristic. A variable is a label or name that represents a concept or characteristic. Concept—noun that stands for a class of objects, e.g., tree, house, teacher, desk, and school. Concept—noun that stands for a class of objects, e.g., tree, house, teacher, desk, and school. Characteristic—a trait we use to describe things, e.g., tall, male, creative, or average. Characteristic—a trait we use to describe things, e.g., tall, male, creative, or average.

3. Variables A variable--Any entity that may take one of two or more mutually exclusive values A variable--Any entity that may take one of two or more mutually exclusive values EXAMPLES: EXAMPLES:  Sex--any one of two mutually exclusive values: female & male  Day of the week--any one of seven mutually exclusive values  Age--a large number of mutually exclusive values.

4. Discrete and Continuous Variables A discrete variable--categorical and differ qualitatively, e.g. sex, day of the week. A discrete variable--categorical and differ qualitatively, e.g. sex, day of the week. A continuous variable--takes on an infinite number of values that differ from each other quantitatively, e.g. age. A continuous variable--takes on an infinite number of values that differ from each other quantitatively, e.g. age. Variable definition determines intent of research Variable definition determines intent of research

5. Two types of variable definition  Constitutive definition—uses words or concepts to describe variable, e.g., attitude—“a predisposition to respond favorably or unfavorably toward a person, object or event.”  Operational definition—indicates the operations that are performed to measure the variable--uses techniques that measure or produce the variable. Researchers use different ways of measuring or manipulating the same variable.Researchers use different ways of measuring or manipulating the same variable.

6. Variables as a set of values Institution Hospital School Public School Private School Nonsectarian School Parochial School

7. 3 Basic Ways of Examining Variables  To describe how the values associated with one or more variables are distributed among one or more groups of people-- DESCRIPTIVE RESEARCH  To determine the nature of the relationship between two or more variables among a single group of people--CORRELATIONAL STUDIES

8. 3 Basic Ways of Examining Variables (cont.)  To examine the extent to which two or more groups of people exhibit different values with respect to a single variable--GROUP COMPARISON STUDIES

9. Populations and Samples Populations are groups consisting all the people that researchers wish to apply their findings. Populations are groups consisting all the people that researchers wish to apply their findings. Samples are group of people representing subsets of populations. Samples are group of people representing subsets of populations.

10. Independent and Dependent Variables

11. What is Correlational Research?

12. Correlational Research Correlational research attempts to determine whether, and to what degree, a relationship exists between two or more quantifiable variables. Correlational research attempts to determine whether, and to what degree, a relationship exists between two or more quantifiable variables. The purpose of correlational study may be to establish relationship (or lack of it) or to use relationships in making predictions. The purpose of correlational study may be to establish relationship (or lack of it) or to use relationships in making predictions.

13. Examples of Correlational Studies 1. The relationship between intelligence and self-esteem. 1. The relationship between intelligence and self-esteem. 2. The relationship between anxiety and achievement. 2. The relationship between anxiety and achievement. 3. Use of an aptitude test to predict success in an algebra course. 3. Use of an aptitude test to predict success in an algebra course. –(Show how you will correlate the scores in each of the studies).

14. Group Comparison Studies Examines how the values associated with a single variable may be distributed differently among two or more groups of people. Examines how the values associated with a single variable may be distributed differently among two or more groups of people. –EXAMPLE: How do the self-concepts of special education children who have been mainstreamed differ from the self-concepts of special education children in self- contained classrooms? (Which is the variable and which are the two groups?)

15. GROUP WORK Give an example of group comparison studies. Identify the variable that can take on one of two values. Give an example of group comparison studies. Identify the variable that can take on one of two values.

16. Populations, Samples, and Subjects Populations are groups consisting of all people to whom researchers wish to apply their findings. Populations are groups consisting of all people to whom researchers wish to apply their findings. Samples are groups of people (representing subsets of populations) from whom data are collected. Samples are groups of people (representing subsets of populations) from whom data are collected. Subjects are individuals who participate in a research study or people from whom data are collected. Subjects are individuals who participate in a research study or people from whom data are collected.

17. The Target Population and the Accessible Population Target population--the population the researcher would like the results to be generalized. Target population--the population the researcher would like the results to be generalized. Accessible population--the population available from which the researcher can select. Accessible population--the population available from which the researcher can select.

18. GROUP WORK Choose a research question and identify (a) the target population and (b) accessible population. Choose a research question and identify (a) the target population and (b) accessible population.

19. List examples of research populations and samples  In the United States  Oregon  Washington County  In Forest Grove  In Pacific University  EDUC 601 class.

20. Purpose of Sampling The purpose of sampling is to obtain a group of subjects who will be representative of the larger population or will provide specific information needed. The purpose of sampling is to obtain a group of subjects who will be representative of the larger population or will provide specific information needed.

21. Sampling 1. Probability Sampling--selecting a sample that will adequately represent the true population. 1. Probability Sampling--selecting a sample that will adequately represent the true population. –(a) Random Sampling--each member of the population has the same probability of being selected.

22. Sampling (cont.) –(b) Systematic Sampling--every Nth member of the population is selected –(c) Stratified Sampling--subjects are selected from groups of the population –(c) Cluster Sampling--Naturally occuring groups are selected

23. Example of a Study using Probability Sampling What is the attitude of teachers in the North Country toward unions? What is the attitude of teachers in the North Country toward unions? 1. The population is 5,000 teachers. 1. The population is 5,000 teachers. 2. The desired sample size is 10% of the 5,000 teachers, or 500 teachers. 2. The desired sample size is 10% of the 5,000 teachers, or 500 teachers. 3. We have a directory which lists all teachers in the system. 3. We have a directory which lists all teachers in the system. RANDOM SAMPLING-- RANDOM SAMPLING--

24. Steps in SYSTEMATIC SAMPLING: Steps in SYSTEMATIC SAMPLING: 1. The population is all 5,000 teachers. 1. The population is all 5,000 teachers. 2. The desired sample is 500. 2. The desired sample is 500. 3. You have a directory which lists all the teachers in alphabetical order. 3. You have a directory which lists all the teachers in alphabetical order. 4. Nth is equal to the size of the population, 5,000 divided by the size of the sample. Thus Nth = (5,000 divided by 500) = 10. 4. Nth is equal to the size of the population, 5,000 divided by the size of the sample. Thus Nth = (5,000 divided by 500) = 10. 5. Select a random name at the top of the list of teachers. 5. Select a random name at the top of the list of teachers.

25. Steps in SYSTEMATIC SAMPLING: (cont.) 6. From that point, every following 10th name is in the sample. 6. From that point, every following 10th name is in the sample.

26. Steps in STRATIFIED SAMPLING 1. The population is all 5,000 teachers. 1. The population is all 5,000 teachers. 2. Desired sample size is 10% of the 5,000 teachers, or 500 teachers. 2. Desired sample size is 10% of the 5,000 teachers, or 500 teachers. 3. The variable of interest is teaching level and there are three subgroups--elementary, junior high, and senior high. 3. The variable of interest is teaching level and there are three subgroups--elementary, junior high, and senior high. 4. Randomly select 10% of each subgroup to represent each teaching group proportionally. 4. Randomly select 10% of each subgroup to represent each teaching group proportionally.

27. Steps in CLUSTER SAMPLING 1. The population is all 5,000 teacher. 1. The population is all 5,000 teacher. 2. The desired sample size is 500. 2. The desired sample size is 500. 3. A logical cluster is a school. 3. A logical cluster is a school. 4. You have a list of all the schools in the North Country; they are 100 schools. 4. You have a list of all the schools in the North Country; they are 100 schools. 5. There is an average of 50 teachers per school. 5. There is an average of 50 teachers per school.

28. Steps in CLUSTER SAMPLING (cont.) 6. The number of clusters (schools) needed equals the desired sample size, 500, divided by the average size of a cluster, 50. Thus, the number of schools needed is 500 divided by 50 = 10. 6. The number of clusters (schools) needed equals the desired sample size, 500, divided by the average size of a cluster, 50. Thus, the number of schools needed is 500 divided by 50 = 10. 7. Therefore, 10 of the schools are randomly selected. 7. Therefore, 10 of the schools are randomly selected. 8. All the teachers in each of the 10 schools are in the sample (10 schools, 50 teachers per school, equals the desired sample). 8. All the teachers in each of the 10 schools are in the sample (10 schools, 50 teachers per school, equals the desired sample).

29. Sampling (cont.) 2. Non-probability Sampling--probability of selection unknown. 2. Non-probability Sampling--probability of selection unknown. –(a) Convenience Sampling--a group of subjects selected because of availability –(b) Purposive Sampling--selection of particularly informative or useful subjects. –(c) Quota Sampling--nonrandom sampling representative of a target population.

30. Sampling (cont.) 3. Volunteer Samples--asking for volunteers. 3. Volunteer Samples--asking for volunteers.

31. Validity and Reliability of Educational Measures Validity—the degree to which a test measures what it is supposed to measure. Validity—the degree to which a test measures what it is supposed to measure. Was the research process a valid one for answering the research question? Was the research process a valid one for answering the research question? A test is not valid per se; it is valid for a particular purpose and for a particular group. A test is not valid per se; it is valid for a particular purpose and for a particular group. Content validity—the degree to which a test measures an intended content area. Content validity—the degree to which a test measures an intended content area. Construct validity—the degree to which a test measures an intended hypothetical construct, e.g. intelligence. Construct validity—the degree to which a test measures an intended hypothetical construct, e.g. intelligence.

32. Validity and Reliability of Educational Measures Validity—the degree to which a test measures what it is supposed to measure. Validity—the degree to which a test measures what it is supposed to measure. Was the research process a valid one for answering the research question? Was the research process a valid one for answering the research question? A test is not valid per se; it is valid for a particular purpose and for a particular group. A test is not valid per se; it is valid for a particular purpose and for a particular group. Content validity—the degree to which a test measures an intended content area. Content validity—the degree to which a test measures an intended content area. Construct validity—the degree to which a test measures an intended hypothetical construct, e.g. intelligence. Construct validity—the degree to which a test measures an intended hypothetical construct, e.g. intelligence.

33. Internal and External Validity Internal validity—refers to whether the research process yields a result that is valid in the research context. Internal validity—refers to whether the research process yields a result that is valid in the research context. –Is the answer to the research question valid for the people on whom the research was done, in the place the research was done?  External validity—refers to whether the answer to the research question is valid in a larger context—for other people at other times, in other places.

34. Validity and Reliability of Educational Measures Validity—the degree to which a test measures what it is supposed to measure. Validity—the degree to which a test measures what it is supposed to measure. Was the research process a valid one for answering the research question? Was the research process a valid one for answering the research question? A test is not valid per se; it is valid for a particular purpose and for a particular group. A test is not valid per se; it is valid for a particular purpose and for a particular group. Content validity—the degree to which a test measures an intended content area. Content validity—the degree to which a test measures an intended content area. Construct validity—the degree to which a test measures an intended hypothetical construct, e.g. intelligence. Construct validity—the degree to which a test measures an intended hypothetical construct, e.g. intelligence.

35. Internal and External Validity Internal validity—refers to whether the research process yields a result that is valid in the research context. Internal validity—refers to whether the research process yields a result that is valid in the research context. –Is the answer to the research question valid for the people on whom the research was done, in the place the research was done?  External validity—refers to whether the answer to the research question is valid in a larger context—for other people at other times, in other places.

36. Reliability Reliability—dependability, or trustworthiness. Reliability—dependability, or trustworthiness. The degree to which a test consistently measures whatever it measures. The degree to which a test consistently measures whatever it measures. Expressed numerically as a coefficient Expressed numerically as a coefficient Perfect reliability = 1.00 Perfect reliability = 1.00 Very good reliability = greater than.90 Very good reliability = greater than.90 Acceptable reliability = between.80 and.90 Acceptable reliability = between.80 and.90 Inadequate reliability = below.60 Inadequate reliability = below.60

37. Validity and Reliability of Educational Measures Validity—the degree to which a test measures what it is supposed to measure. Validity—the degree to which a test measures what it is supposed to measure. Was the research process a valid one for answering the research question? Was the research process a valid one for answering the research question? A test is not valid per se; it is valid for a particular purpose and for a particular group. A test is not valid per se; it is valid for a particular purpose and for a particular group. Content validity—the degree to which a test measures an intended content area. Content validity—the degree to which a test measures an intended content area. Construct validity—the degree to which a test measures an intended hypothetical construct, e.g. intelligence. Construct validity—the degree to which a test measures an intended hypothetical construct, e.g. intelligence.

38. Internal and External Validity Internal validity—refers to whether the research process yields a result that is valid in the research context. Internal validity—refers to whether the research process yields a result that is valid in the research context. –Is the answer to the research question valid for the people on whom the research was done, in the place the research was done?  External validity—refers to whether the answer to the research question is valid in a larger context—for other people at other times, in other places.

39. Reliability Reliability—dependability, or trustworthiness. Reliability—dependability, or trustworthiness. The degree to which a test consistently measures whatever it measures. The degree to which a test consistently measures whatever it measures. Expressed numerically as a coefficient Expressed numerically as a coefficient Perfect reliability = 1.00 Perfect reliability = 1.00 Very good reliability = greater than.90 Very good reliability = greater than.90 Acceptable reliability = between.80 and.90 Acceptable reliability = between.80 and.90 Inadequate reliability = below.60 Inadequate reliability = below.60

40. Validity vs. Reliability A valid test is always reliable but a reliable test is not necessarily valid. Discuss. A valid test is always reliable but a reliable test is not necessarily valid. Discuss.