Choosing Appropriate Quantitative Research Design PDF

CHOOSING APPROPRIATE QUANTITATIVE RESEARCH DESIGN PRACTICAL RESEARCH 2 Research Design Research Design – refers to the overall plan and scheme for conducting the study. Thus, the researcher may utilize a descriptive research design, experimental research design, or historical resear...

CHOOSING APPROPRIATE QUANTITATIVE RESEARCH DESIGN PRACTICAL RESEARCH 2 Research Design Research Design – refers to the overall plan and scheme for conducting the study. Thus, the researcher may utilize a descriptive research design, experimental research design, or historical research design. Types of Quantitative Research Design A. Descriptive Research Designs B. Experimental Research Designs C. Historical Research Designs Descriptive Research Design Descriptive Normative Survey Correlational Research Studies Descriptive Evaluative Studies Descriptive Comparative Studies Assessment/Evaluation Studies Experimental Research Design Pretest/Post-test Control Group Design Single Group Pre-test/Post-test Design Solomon Four Group Design Completely Randomized Design Randomized Completely Block Design Latin Square Design A. Descriptive Research Design - Descriptive research design is used to gather information on current situations and conditions. It helps provide answers to the questions of who, what, when, where and how of a particular research study. Descriptive Research Design - This design leads to logical conclusions and pertinent recommendations. However, the descriptive research design is dependent to a high degree on data collection instrumentation for the measurement of data and analysis. Descriptive Research Design - The purpose of this design is to describe the status of an identified variable such as events, people or subjects as they exist. - Descriptive research usually makes some type of comparison, contrasts, correlation and sometimes, in carefully planned and orchestrated descriptive researches, cause- effect relationships may be established to some extent. A. Descriptive Research Design Descriptive Normative Survey - Survey designs are procedures in quantitative research in which you administer a survey questionnaire to a small group of people (called the sample) to identify trends in attitudes, opinions, behaviors, or characteristics of a large group of people (called the population). Descriptive Normative Survey - The survey research design is usually used in securing opinions and trends through the use of questionnaires and interviews. A survey is used in gathering data from institutions, government and businesses to help in decision- making regarding change strategies, improving practices, analyzing views on choice of products or market research. Surveys can be conducted face-to-face or online. Descriptive Normative Survey - The descriptive-normative survey approach attempts to establish norms or standards based on a wide class of survey data. The survey data may be demographic data (age, sex, educational attainment, IQ, languages spoken, civil status, average family size) or they may include also data on “average perceptions” of a set of respondents. Descriptive Normative Survey - In order to make the presentation clear and more interactive, you should present both univariate tables (frequency counts for single variable) and multivariate tables (frequency for cross-classifications). For example a table, on sex distribution of the Principals or a two- way table representing the sex and education qualification of principals. A. Descriptive Research Design Correlational Research - Correlation research design is used for research studies aimed to determine the existence of a relationship. If you intend to estimate the extent to which different variables are related to one another in the population of interest, make use of correlational studies. - In this design you will have two or more quantitative variables from the same group of subjects. You will determine if there is a relationship (or covariation) between the 2 variables (a similarity between them, not a difference between their means). Correlational Research - Examples of correlational research involving two (2) quantitative variables that can be correlated are: mental ability and grade in math; gender and math performance; advertising costs and sales; income and expenses. - In correlation studies, you may make use of the results of the descriptive normative surveys. For example if it is desired to determine the extent of the relationship between managerial effectiveness and the variables age, educational attainment, and Correlational Research - Correlation does not mean causation. When two variables are correlated you can use the relationship to predict the value on one variable for a participant if you know that participant’s value on the other variable. Thus, correlation implies prediction not causation. A. Descriptive Research Design Descriptive Evaluative Studies - The purpose of the descriptive evaluative study is to judge the “goodness of criterion measure”. - Longitudinal studies establish the changes in that criterion measure over a long period of time. Thus, if one were to study the changes in the IQ levels of children 9-10 years over a five- year period. A. Descriptive Research Design Descriptive Comparative Studies - Descriptive-comparative studies endeavor to establish significant differences between two or more groups of subjects on the basis of a criterion measure. No attempts to control the effects of extraneous factors are made. For example, it may be desired to compare the managerial effectiveness of three groups of managers A, B, and C. Descriptive Comparative Studies - This type of research usually involves group comparisons. The groups in the study make up the values of the independent variable; for example, gender (male vs. female), pre-school attendance, or children with a working mother versus children without a working mother. - In comparative research the independent variable is not under the researchers’ control. That is, the researcher cannot randomly assign the participants to a gender classification (male or female) or socio- economic class. A. Descriptive Research Design Assessment/Evaluation Studies - Assessment evaluation studies attempt to determine the effectiveness or efficiency of certain practices or policies when applied to a group of respondents. - Assessment studies imply measurement of certain key indicators without attaching any judgement to them. Assessment/Evaluation Studies - Evaluation implies putting judgement and valuing to the measurements obtained and is therefore at a much deeper level than assessment. Evaluation research is conducted to elicit useful feedback from a variety of respondents from various fields to aid in decision making or policy formulation. Assessment/Evaluation Studies 1. Formative Evaluation It is used to determine the quality of implementation of a project, the efficiency and effectiveness of a program, assessment of organizational processes such as procedures, policies, guidelines, human resource development and the like. 2. Summative assessment Is done after the implementation of the program. It examines the outcomes, products or effects of the program. Formative Evaluation a. Needs Assessment. Evaluates the need for the program or project. For example, who needs the program? How great is the need for a remedial class in Mathematics? b. Process Evaluation. Evaluates the process of implementation of a program. For example, you may want to conduct a study on the implementation of the Student Information System (SIS) in you school. Formative Evaluation c. Implementation Evaluation. Evaluates the efficiency or effectiveness of a project or program. For example, how effective is the scholarship program in school? d. Program Monitoring. Evaluates the performance and implementation of an unfinished program. The evaluation is done prior to the completion of the program. It helps improve implementation and achieve best results. The initial implementation of the K-12 program is a very good topic for evaluation under this type of research design. Summative Assessment a. Secondary Data Analysis. You may examine existing data for analysis. For example, you may want to find out the influence of gender and mental ability in the results of the National Achievement Test (NAT) in your school or in your region. b. Impact Evaluation. This is used to evaluate the overall effect of the program in its entirety. For example, you may want to determine the effect of remedial classes on the performance of students in mathematics in your school. Summative Assessment c. Cost-Effectiveness Evaluation. This is done to determine if the program has caused useful effects based on target outcomes. For example, you may want to determine if a leadership training program for officers of student organizations of a certain public secondary school have enhanced the leadership skills of the participants. d. Cost-effectiveness Evaluation. Also called cost- benefit analysis, it compares the relative costs to the outcomes or results of some courses of action. For example, you may conduct a study on the value for money returns of a company brought about by an intensive training investment for employees in the Sales department. B. Experimental Research Design - Experimental studies are also known as longitudinal or repeated-measures studies, for obvious reasons. - Experimental research design uses the scientific method to establish the cause-effect relationship among a group of variables that make up a study. Experimental Research Design - The true experiment is often thought of as a laboratory study, but this not always the case; a laboratory setting has nothing to do with it. - A true experiment is any study where an effort is made to identify an impose control over all other variables except one. a. An independent variables is manipulated to determine the effects on the dependent variables. b. Subjects are randomly assigned to experimental treatments rather than identified in naturally occurring groups. Experimental Research Design - If the treatment effect is unlikely to wash out between measurements, a control group has to be used. In this designs, all subjects are measured, but only the experimental group receives the treatment. All subjects are then measured again, and the change in the experimental group is compared with the change in the control group. Experimental Research Design - A factor called treatment is introduced into the research investigation and the researcher attempts to isolate the effects of such treatment by means of control. - The whole point of all experimental designs is to make sure that the effects of the treatment is carefully isolated or measured. 1. Pre-test/Post-test Control Group Design - The design requires two groups of equivalent standing in terms of a criterion measure e.g. achievement or mental ability. The first group is designated as the control group while the second group is the experimental group. Pre-test/Post-test Control Group Design - Both groups are given the same pre-test. The control group is not subjected to a treatment while the experimental group is given the treatment factor. After the experimental period, both groups are again given the same post- test. The researcher may now conduct a comparison of the post-test results or gain in scores (posttest-pretest) between the experimental and control groups. Pre-test/Post-test Control Group Design - This design is threatened by certain factors: maturation (or the aging of the subjects from the pretest to the posttest period); test- wiseness (or memorizing the contents of the pretest to score high score on the posttest); and natural attrition (death of subjects or drop -outs from the experiment). 2. Single Group Pre-test/Post-test Design - In experimental conditions where a limited number of subjects are available, the single group pretest-posttest design may be used. - The group is first given a pretest followed by the usual treatment and then a posttest is administered. A new pretest is then administered to the group followed by the experimental treatment factor and a final posttest. Single Group Pre-test/Post-test Design - This design is very delicate because the researcher must see to it that situations are equivalent before and during the experimental factor is introduced. As one might suspect, this design is more open to threats to internal validity such as Hawthorne effect (or test- wiseness), maturation and attrition. 3. Solomon Four Group Design - The Solomon four group design makes use of four equivalent groups. The first two groups follow the pretest-posttest control group design. The third group is given no pretest with treatment and a posttest. The last group is given no pretest, no treatment but with posttest. - The design eliminates the Hawthorne effect, effects of maturation and attrition but has the main disadvantage of requiring a large number of respondents. Solomon Four Group Design - In this design the subjects are randomly assigned to two study groups and two control groups. Pretest measures are used for one of the study groups, and one of the control groups. Following exposure of the study groups to the intervention or experiment, posttest measures are collected on all four groups.  Solomon Four Group Design Time Period 1 (Pre) Treatment Period 2 (Post) Experimental Group 1 Random Assignment Observation 1 w/ treatment Observation 3 Control Group 1 Random Assignment Observation 2 w/o treatment Observation 4 Experimental Group 2 Random Assignment w/ treatment Observation 5 Control Group 2 Random Assignment w/o treatment Observation 6 Factors Affecting the Experimental Plan 1. History. Specific events which occur between the first and second measurement in addition to the experimental variable may affect the result of the experiment. Example: Researcher collects gross sales data before and after a 5- day 50% off sale. During the sale a super typhoon occurs and the results of the study may be affected because of the calamity, not the sale. 2. Maturation. The process of maturing either biological or physiological that takes place in the individuals (subjects) during the experiment regardless of event can affect experimental outcomes. An example of this is when subjects are tired after completing the training session and their responses on the post-test are affected. Factors Affecting the Experimental Plan 3. Testing. Subjects may be more aware of the contents of the posttest given to pretest. In other words, the pre- test becomes a form of post-test. Example: Subjects take a pretest and think about some of the items. On the post-test they change to answers they feel are more acceptable. So, the experimental group learns from the pretest. 4. Mortality. Subject may drop out of the experimental plan either voluntarily or involuntarily. The loss of subjects from comparison groups could greatly affect the comparison of unique characteristics of those subjects. Groups to be compared need to be the same before and after the experiment. Factors Affecting the Experimental Plan 5. Interaction effects. The interaction of the experimental variable and extraneous factors such as setting, time and conditions of the experimental set-up. Combination of these factors may interact especially in multiple group comparisons to produce erroneous measurements and interpretation that the treatment caused the effect. 6. Measuring instruments. Changes in instruments calibration of instruments, observers, or scorers may cause changes in the measurements. Example: Interviewers are very careful with their first two of three interviews but on the 4th, 5th and 6th interview becomes tiresome and boring thus, interviewers are less careful and make errors. Factors Affecting the Experimental Plan 7. Statistical regression. Because of extreme scores of measurements, groups are chosen. Those scores or measurements tend to move toward the mean with repeated measurements even without an experimental variable. 8. Differential selection. Different individuals or groups would have different previous knowledge or ability which would affect the final measurement if not taken into account. Example: A group of subjects who has viewed a TV programs is compared with a group which has not. There is no way of knowing that the groups would have been equivalent since they were not randomly assigned to view the TV program. Factors Affecting the Experimental Plan 9. John Henry effect. John Henry was a worker who outperformed a machine under an experimental setting because he was aware that his performance was compared with that of a machine. It is an experimental bias which pertains to the tendency of the subjects in the control group to perceive themselves at a disadvantage, thus working harder to outperform the experimental group. C. Historical Research Design - The purpose of historical research design is to collect, verify, and synthesize evidence from the past to establish facts that defend or refute your hypothesis. - It uses secondary sources and a variety of primary documentary evidence, such as logs, diaries, official records, reports, archives, and non-textual information like maps, pictures, audio and visual recordings. The limitation is that the sources must be both authentic and valid. Historical Research Design - Sometimes, quantitative history is called cliometrics by economic historians. These historians also called social scientist to make historical research and consciously examine the temporal nature of the social phenomena they explored. Historical Research Design - An example of this is the development of the field of ecological regression, particularly for analysis of electoral patterns. Political scientists can supplement analysis of election results with surveys of individual voters. Indeed the National Election Survey, conducted since 1948, has itself become a historical source of changing electoral behavior. But historians cannot go back and survey voters from the election of 1860, and thus must make use of the aggregate election results and the ecological characteristics of the voting units – e.g., precincts, districts or counties-that provided the vote. Major Process of Historical Research 1. Data collection. The historian collects data from the past through relics, fossils or documents found in the activities or through personal interviews with key informants. Old newspaper clippings, memoirs, diaries and the like are rich source of historical data. 2. Analysis of data. The historian brings together the data collected to the state of knowledge about the past event and use simple to complex statistical tools for analysis. 3. Report of findings. The historian reports his/her findings by carefully explaining discrepancies noted and the probable causes of such discrepancies.