Research Design for Chapter 2 for research purposes

research design for chapter 2

1. METHODS OF RESEARCH

2. Parts of a Research Paper Chapter 1- The Problem and Review of Related Literature Review of Related Literature and Studies Conceptual/Theoretical Framework of the Study Statement of the Problem Significance of the Study Scope and Limitation of the Study Definition of Terms

3. Parts of a Research Paper CHAPTER 2 – METHODOLOGY Research Design Participants of the Study Instrumentation Data Gathering Procedure Data Analysis CHAPTER 3 – RESULT AND DISCUSSION [Headings are based on Research Questions] CHAPTER 4 – CONCLUSIONS AND RECOMMENDATIONS Summary of Findings Conclusions Recommendations

4. OBJECTIVES At the end of the session, the learner is expected to: choose appropriate quantitative research design ; differentiate between : Research method and research design; Population and sample; Probability and non-probability sampling; present with accuracy written research methodology ; and describe sampling procedure and the sample .

5. DEEPENING IDEAS Differences between: Research design and Research method, Population and Sample, and Random and Non-random sampling

6. Research Methods Content Area Researchable Questions Research Design Measurement Methods Sampling Data Collection Statistical Analysis Report Writing ?

7. Research Method ( Labay , 2016) the generalized and established approach in tackling the research problem focus on the step-by-step procedure of every research process and how data will be gathered and analyzed answers the question “ how ” (it must to done? the data be gathered?)

8. Research Design The research design is the plan, structure, and strategy of investigations of answering the research question and is the overall plan or blueprint the researchers select to carry out their study.

9. Choosing RESEARCH DESIGNS

10. QUANTITATIVE METHODS OF RESEARCH

11. These are non-experimental designs that involve studying populations or universes based on the data gathered from a sample drawn from them. The data are often gathered using self-report methods, such as a questionnaire completed by the study subjects. Survey Research Designs

12. purpose is to describe existing conditions, opinions, attitudes, impressions, perceptions, and description trending. Descriptive Survey

13. Population census studies Public Opinion surveys Documentary Analysis Test Score Analysis Examples

14. Corporate Social Responsibility of Saint Paul University Philippines Example

15. there is a possibility of low returns of questionnaire or other instruments floated to generate data there is a possibility that their assertions in the questionnaire are not true or correct there is a possibility that the instrument prepared by the researcher maybe inadequate or insufficient to gather data for the study. Disadvantages of survey researches

16. uses standardized instruments like mental ability test, stress and personality questionnaire, morale and job satisfaction standardized questionnaires and they have some established norms. Descriptive normative survey

17. It is designed to discover the direction and magnitude of relationships among variables in a particular population of subjects. concerned with determining the extent of relationship existing between variables the extent of relationship is determined by the magnitude of coefficients Pearson r Descriptive Correlational Survey Mathematics Anxiety and Academic Performance of Selected Freshmen Students of St. Paul University, School Year 2016 – 2017. Example

18. It judges the goodness of an existing program It is directed to whether or not a program achieved its goal Its purpose is to find out whether set criterion were met or not; to provide ongoing feedback to people who are responsible for carrying out a plan or a program or to evaluate the effectiveness of the outcome of the plan or program. Descriptive Evaluative

19. Example The Implementation of Spiral Approach in the Mathematics Curriculum The Implementation of 4 P’s in Enrile , Cagayan 19

20. It is used to compare or contrast representative samples from two or more groups of subjects in relation to certain designated variables. compares the characteristics of groups according to some selected variables since the main purpose is to determine the difference without determining the cause Descriptive Comparative A national survey of attitudes towards “professionalism” among graduates of baccalaureate and associate degree programs. Example

21. I. Ex – Post facto Research Studies - Same as causal comparative design. a ttempts to determine the possible reason or cause for existing differences in the behavior of groups or individuals Falls under the category of comparative research. 21

22. Examples Differences in hearing among smokers and nonsmokers. 22

23. used to project the demands that will be made in the future regression equations are formed and the probable behavior of a variable can be projected Trends and Projective Studies Forecasting Sales of Beverages in Tuguegarao City Determining Housing Projects by the Year 2019 Examples

24. Experimental Methods of Research

25. A method that uses the single-variable approach in problem-solving, whether the experiment is carried on in the laboratory, classroom or field, i.e., all other factors are kept constant except a single factor called the variable, which is manipulated in various ways in order to determine the results of its functions. Experimental Method

26. person – to – person matching - people are selected on the basis of similar or identical personal characteristics matching groups – groups are paired on a variable (ex. sex, age, etc) ranking method – subjects for study are ranked in some selected variables (ex. achievement, socio – economic variables, etc) Matching Methods in an Experimental Design

27. 1. PRE TEST – POST TEST CONTROL GROUP DESIGN Experimental group experimental treatment Pre test Post test Control group Pre test Post test

28. PRE TEST – POST TEST CONTROL GROUP DESIGN In this design, subjects have been designed randomly to the experimental or control group The experimental treatment is given only to those in the experimental group, and the pre tests and post tests are those measurements of the dependent variables that are made before and after the experimental treatment is performed. All true experimental designs have subjects randomly assigned groups, have an experimental treatment introduced to some of the subjects and have the effects of the treatment observed.

29. 2. AFTER / POST TEST ONLY CONTROL GROUP DESIGN Experimental group experimental treatment Post test Control group Post test

30. 2. AFTER / POST TEST ONLY CONTROL GROUP DESIGN This design is sometimes called after only control group design. This is composed on two randomly assigned groups, but neither of which is pretested or premeasured in “the before” period of time. The independent variable is introduced into the experimental group and withheld from the control group.

31. 3. SOLOMON FOUR GROUP DESIGN Experimental group I experimental treatment Pre test Post test Control group I Pre test Post test Experimental group II experimental treatment Post test Control group II Post test

32. SOLOMON FOUR GROUP DESIGN This design employs two experimental groups and two control groups. Initially, the investigator randomly assigns subjects to the four groups. Those in the experimental group 1 are pretested and are tested again after the treatment. Those in the experimental group 2 also receive the treatment but are observed only after the treatment, but not before. Those in control group 1 are observed, on occasions 1 and 2, but they are not given the experimental treatment. Those in control group 2 are observed only on the second occasion without previous observation or treatment.

33. Pre – Experimental Design Pre-experimental designs are so named because they follow basic experimental steps but fail to include a control group. In other words, a single group is often studied but no comparison between an equivalent non-treatment group is made. 33

34. Pre – Experimental Design Subdivisions: One shot case study/ single case study One group pretest – posttest design Static group comparison design 34

35. One shot case study/ single case study In single case study, that studies at once, following a treatment or an agent presumed to cause change. Because the study design has a total absence of control, it is considered to be little value as an experiment. 35

36. One group pretest – posttest design Only one group is observed before and after the independent variable is introduced. 36

37. Static group comparison design The static group that has experienced the independent variable is compared with one that has not. Here the experimental group receives the independent variable, but control group does not. 37

38. 38

39. Quasi – Experimental Research

40. QUASI EXPERIMENTAL DESIGN It is one with full experimental control, usually randomization, is not possible. Subdivisions: Non equivalent control group design or the four celled design without use of randomization The time series quasi experimental design The multiple time series design

41. 1. Non equivalent control group design or the four celled design without use of randomization Experimental group ( not randomly selected) experimental treatment Pre test Post test Control group ( not randomly selected) Pre test Post test

42. 2. Time series experimental design experimental treatment Pre test 1 2 3 4 5 6 6 5 4 3 2 post test 1 The time series experiment design, a single group experiment comprises of series of observations in the before time period to establish a baseline. The experimental variable is then introduced, followed by another series of observation to examine the effect of the independent variable.

43. 3. Multiple time series design Experimental group experimental matter Pre test 1 2 3 4 5 6 6 5 4 3 2 post test 1 Control group Pre test 1 2 3 4 5 6 6 5 4 3 2 post test 1

44. Case Analysis [What’s my research design?] A researcher wants to know why individuals in Community A have a higher rate of a rare form of cancer when compared to those living in Community B. To find out the reasons or causes for the differences in cancer rates in these two communities, the investigator surveyed residents about their lifestyle, noted the types of businesses that were present in the community and searched medical records.

45. Case Analysis [What’s my research design?] An investigator wants to evaluate whether a new technique to teach math to elementary school students is more effective than the standard teaching method. the investigator divides the class randomly (by chance) into two groups and calls them "Group A" and "Group B." The students cannot choose their own group. The random assignment process results in two groups that should share equal characteristics at the beginning of the experiment. In Group A, the teacher uses a new teaching method to teach the math lesson. In Group B, the teacher uses a standard teaching method to teach the math lesson. The investigator compares test scores at the end of the semester to evaluate the success of the new teaching method compared to the standard teaching method.

46. Case Analysis [What’s my research design?] A fitness instructor wants to test the effectiveness of a performance-enhancing herbal supplement on students in her exercise class. To create experimental groups that are similar at the beginning of the study, the students are assigned into two groups at random (they can not choose which group they are in). Students in both groups are given a pill to take every day, but they do not know whether the pill is a placebo (sugar pill) or the herbal supplement. The instructor gives Group A the herbal supplement and Group B receives the placebo (sugar pill). The students' fitness level is compared before and after six weeks of consuming the supplement or the sugar pill.

47. Population and Sample [ Talisayon , 2017] Sample – a group from which you collect data; representative or typical of a population Population – group to which sample results will be generalized

48. BASIC CONCEPTS IN SAMPLING AND SAMPLING TECHNIQUES

49. SAMPLING TECHNIQUE The process which involves taking a part of a population, making observation on this representatives and the generalizing the findings to the bigger population ( Zulueta and Costales , 2003).

50. Session 3. 50 TEACHING BASIC STATISTICS …. Sampling Process Sample Data Universe Inferences/Generalization (Subject to Uncertainty) INFERENTIAL STATISTICS

51. Session 3. 51 TEACHING BASIC STATISTICS …. WHY DO WE USE SAMPLES? 1. Reduced Cost 2. Greater Speed or Timeliness 3. Greater Scope 4. Convenience

52. Session 3. 52 TEACHING BASIC STATISTICS …. TWO TYPES OF SAMPLES 1. Probability sample 2. Non-probability sample

53. Probability sampling – A method of sampling that utilizes some form of random selection. In order to have a random selection method, you must set up some process or procedure that assures that the different units in your population have equal probabilities of being chosen.

54. Session 3. 54 TEACHING BASIC STATISTICS …. Samples are obtained using some objective chance mechanism, thus involving randomization. They require the use of a sampling frame (a list/map of all the sampling units in the population). PROBABILITY SAMPLES

55. Session 3. 55 TEACHING BASIC STATISTICS …. The probabilities of selection are known. They are generally referred to as a random sample from a finite population. They allow drawing of (valid) generalizations about the universe/population whose sampling error can be ascertained. PROBABILITY SAMPLES

56. Non – Probability sampling – A sampling technique where the samples are gathered in a process that does not give all the individuals in the population equal chances of being selected.

57. Session 3. 57 TEACHING BASIC STATISTICS …. Samples are obtained haphazardly, selected purposively or are taken as volunteers. The probabilities of selection are unknown. NON-PROBABILITY SAMPLES

58. Session 3. 58 TEACHING BASIC STATISTICS …. BASIC SAMPLING TECHNIQUES Simple Random Sampling Stratified Random Sampling Systematic Random Sampling Cluster Sampling Multi – Stage Sampling Slide No. 3.20

59. Session 3. 59 TEACHING BASIC STATISTICS …. SIMPLE RANDOM SAMPLING Most basic method of drawing a probability sample Assigns equal probabilities of selection to each possible sample

60. – the best-known and most widely used probability sample. It is a method of selecting a sample from a universe such that each member of the population has an equal chance of being included in the sample. Lottery method Fish – bowl technique table of random numbers Simple Random Sampling Probability Sampling

61. Session 3. 61 TEACHING BASIC STATISTICS …. STRATIFIED RANDOM SAMPLING The universe is divided into L mutually exclusive sub-universes called strata . Independent simple random samples are obtained from each stratum.

62. A stratum is defined as a sub – population and a strata consists of two or more homogeneous population. Steps: construct the population of the participants and determine the relevant strata. Select the number using either proportional or equal allocation Choose the participants within each category according to simple random sampling methods Stratified Random Sampling Probability Sampling

63. Session 3. 63 TEACHING BASIC STATISTICS …. ILLUSTRATION C D B A B Slide No. 3.13

64. Determining Adequate Sample Size

65. Sampling Formula (Slovin’s) N n = ----------- 1 + e 2 N Where n = sample size N = population size e = margin of error

66. Example for Slovin’s Formula If N = 3000 and e = .05, then n is 3000 n = ------------------- 1 + (.05) 2 (3000) n = 3000/8.5 = 352.94 = 353

67. Strata/Department Number of respondents Number of samples Surgery 800 94 Medical 500 59 Pedia 1000 118 Obygyney 700 82 Total 3000 353

68. Session 3. 68 TEACHING BASIC STATISTICS …. Advantages of Stratification 1. It gives a better cross-section of the population . 2. It simplifies the administration of the survey/data gathering. 3. It allows one to draw inferences for various subdivisions of the population.

69. Session 3. 69 TEACHING BASIC STATISTICS …. SYSTEMATIC SAMPLING Adopts a skipping pattern in the selection of sample units Gives a better cross-section if the listing is linear in trend but has high risk of bias if there is periodicity in the listing of units in the sampling frame Allows the simultaneous listing and selection of samples in one operation

70. Session 3. 70 TEACHING BASIC STATISTICS …. Population Systematic Sample ILLUSTRATION

71. used when large scale – survey is undertaken. Groups are chosen and not individuals. Homogeneity is considered. Cluster Sampling Probability Sampling

72. Session 3. 72 TEACHING BASIC STATISTICS …. CLUSTER SAMPLING It considers a universe divided into N mutually exclusive sub-groups called clusters . A random sample of n clusters is selected and their elements are completely enumerated. It has simpler frame requirements. It is administratively convenient to implement. Slide No. 3.19 Slide No. 3.11

73. Session 3. 73 TEACHING BASIC STATISTICS …. ILLUSTRATION Population Cluster Sample Slide No. 3.18

74. – a method which is rarely used because of the complexity of its strategy and it incurs a lot of effort, time and expense. Multi – Stage Sampling Probability Sampling

75. Session 3. 75 TEACHING BASIC STATISTICS …. MULTI - STAGE SAMPLING In the first stage, the units are grouped into N sub-groups, called primary sampling units (psu’s) and a simple random sample of n psu’s are selected. Illustration: A PRIMARY SAMPLING UNIT

76. Session 3. 76 TEACHING BASIC STATISTICS …. In the second stage, from each of the n psu’s selected with M i elements, simple random sample of m i units, called secondary sampling units ssu’s, will be obtained. Illustration: A SECONDARY SAMPLING UNIT SAMPLE

77. Types Non - Probability Sampling Convenience sampling -used based on the convenience of the researcher. This strategy allows the use of any available group for the research activity Example: To investigate the most popular noon time TV program using telephone interview. 77

78. Purposive/ judgemental sampling –sometimes called deliberate sampling.The researcher relies on his judgment as the criterion for the selection and does not use the rules governing sampling techniques . Example. To investigate the history of a certain place. To investigate the effectiveness of a certain shampoo. 78

79. Quota sampling – used for infinite population frames and therefore, the researcher cannot get a random sample. Like purposive sample, this is not a representative sample. Example: To investigate the DIP learning in SPUP. The researcher will select say 50 participants in each school/department as a quota. 79

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