Practical Research 2 Reviewer PDF

PRACTICAL RESEARCH 2 REVIEWER Theoretical Framework –theories that serve as the building blocks or skeleton for the foundation or bases of the study. Theoretical framework strengthens your study. Conceptual Framework a. Illustrates what the researcher expects to find in the research; it guide...

PRACTICAL RESEARCH 2 REVIEWER Theoretical Framework –theories that serve as the building blocks or skeleton for the foundation or bases of the study. Theoretical framework strengthens your study. Conceptual Framework a. Illustrates what the researcher expects to find in the research; it guides the researcher by giving clear directions to the research. b. It explains the major variables in the study. It is a diagram representing the relationship or connections of variables. Hypothesis - It states your predictions about what your research will find. Review of Related Literature - It is a detailed review of existing literature related to the topic of a thesis or dissertation. Research design is defined as the rational and coherent overall strategy that the researcher uses to incorporate all the vital components of the research study. TYPES OF QUANTITATIVE RESEARCH DESIGN 1. Descriptive Research. When little is known about the research problem, then it is appropriate to use descriptive research design. It is a design that is exploratory in nature. The purpose of descriptive research is basically to answer questions such as who, what, where, when, and how much. So, this design is best used when the main objective of the study is just to observe and report a certain phenomenon as it is happening.  2. Correlational Research. The main goal of this design is to determine if variable increases or decreases as another variable increases or decreases. This design seeks to establish an association between variables. It does not seek cause and effect relationship like descriptive research; it measures variables as it occurs. It has two major purposes: (a) to clarify the relationship between variables and (b) predict the magnitude of the association. However, the extent of the purpose of correlational research depends on the scope and delimitation of the study. 3. Ex Post Facto. If the objective of the study is to measure a cause from a pre-existing effect, then Ex Post Facto research design is more appropriate to use. In this design, the researcher has no control over the variables in the research study. Thus, one cannot conclude that the changes measured happen during the actual conduct of the study. 4. Quasi-Experimental. The term means partly, partially, or almost – pronounced as kwahz-eye. This research design aims to measure the causal relationship between variables. The effect measured is considered to have occurred during the conduct of the current study. The partiality of quasi- experimental design comes from assigning subjects, participants, or respondents into their groups. The groups are known to be already established before the study, such as age educational background and nationality. Since the assignment of subjects, participants, or respondents are not randomly assigned into an experimental or control groups, the conclusion of results is limited. 5. Experimental Research. This research design is based on the scientific method called experiment with a procedure of gathering data under a controlled or manipulated environment. It is also known as true experimental design since it applies treatment and manipulation more extensively compared to quasi-experimental design. Random assignment of subjects or participants into treatment and control group is done increasing the validity of the study. Experimental research, therefore, attempts to affect a certain variable by directly manipulating the independent variable. SAMPLING PROCEDURE AND THE SAMPLE THE POPULATION AND SAMPLE The population is the totality of all the objects, elements, persons, and characteristics under consideration. It is understood that this population possesses common characteristics about which the research aims to explore. Sampling pertains to the systematic process of selecting the group to be analyzed in the research study. The goal is to get information from a group that represents the target population. Once a good sample is obtained, the generalizability and applicability of findings increases. The representative subset of the population refers to the sample. PROBABILITY SAMPLING IN QUANTITATIVE RESEARCH 1. Simple Random Sampling. It is a way of choosing individuals in which all members of the accessible population are given an equal chance to be selected. 2. Stratified Random Sampling. The same with simple random sampling, stratified random sampling also gives an equal chance to all members of the population to be chosen. However, the population is first divided into strata or groups before selecting the samples. 3. Cluster Sampling. This procedure is usually applied in large-scale studies, geographical spread out of the population is a challenge, and gathering information will be very time-consuming. 4. Systematic Sampling. This procedure is as simple as selecting samples every nth (example every 2nd, 5th) of the chosen population until arriving at a desired total number of sample size. RESEARCH INSTRUMENT VALIDITY AND RELIABILITY Research Instruments are basic tools researchers used to gather data for specific research problems. CHARACTERISTICS OF A GOOD RESEARCH INSTRUMENT 1. Concise. 2. Sequential. 3. Valid and reliable. 4. Easily tabulated. COMMON SCALES USED IN QUANTITATIVE RESEARCH 1. Likert Scale. This is the most common scale used in quantitative research. Respondents were asked to rate or rank statements according to the scale provided. TYPES OF VALIDITY OF INSTRUMENT 1. Face Validity. 2. Content Validity. 3. Construct Validity. 1. Concurrent Validity. It is a detailed review of existing literature related to the topic of a thesis or dissertation. 4. RESEARCH INTERVENTION STEPS IN DESCRIBING THE RESEARCH INTERVENTION PROCESS 1. Write the Background Information. 2. Describe the Differences and Similarities between the Experimental and Control Group. 3. Describe the Procedures of the Intervention. 4. Explain the Basis of Procedures. PLANNING DATA COLLECTION Generally, data are any pieces of information or facts that people have known. Once these data answer the research problem, it becomes helpful to research. When research data appears to be measurable in the numerical form, it is considered quantitative data. TECHNIQUES IN COLLECTING QUANTITATIVE DATA 1. Observation. It is gathering information about a certain condition by using senses. The researcher records the observation as seen and heard. This is done by direct observation or indirect observation using gadgets or apparatus. An observation checklist aids the researcher in recording the data gathered. 2. Survey. Data gathering is done through interview or questionnaire. By means of questionnaire you use series of questions or statements that respondents will have to answer. Basically, respondents write or choose their answer from given choices. On the other hand, interview is when you ask respondents orally to tell you the responses. Since you are doing quantitative research, it is expected that responses have numerical value either it is nominal or ordinal in form.  3. Experiment. When your study is an experimental design, it was already discussed in the previous lesson that it would use treatment or intervention. After the chosen subjects, participants, or respondents undergone the intervention, the effects of such treatment will be measured. DATA ANALYSIS Data analysis in research is a process in which gathered information are summarized in such a manner that it will yield answers to the research questions. The statistical treatment makes explicit the different statistical methods and formulas needed to analyze the research data. PLANNING YOUR DATA ANALYSIS Descriptive Statistical Technique provides a summary of the ordered or sequenced data from your research sample. Examples of these tools are frequency distribution, measure of central tendencies (mean, median, mode), and standard deviation. You also must identify types of statistical analysis of variable in your quantitative research. A univariate analysis means analysis of one variable. Analysis of two variables such as independent and dependent variables refer to bivariate analysis while the multivariate analysis involves analysis of the multiple relations between multiple variables.