Historical Research
Historical research is the process of systematically examining past events to give an account of what has happened in the past.
 It is not a mere accumulation of facts and dates or even a description of past
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 events.
It is a flowing, dynamic account of past events which involves an interpretation of the these events in an attempt to recapture the nuances, personalities, and ideas that influenced these events.
One of the goals of historical research is to communicate an understanding of past events.
Significance of Historical Research
1. To uncover the unknown
2. To answer questions
3. To identify the relationship that the past has to the present
4. To record and evaluate the accomplishments of individuals, agencies, or institutions.
5. To assist in understanding the culture in which we live
Historical Research Methodology
1. Identification of the research topic and formulation of the research problem or question.
2. Data collection or literature review.
3. Evaluation of materials.
4. Data synthesis.
5. Report preparation or preparation of the narrative exposition.
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Strengths
1. Provides a comprehensive picture of historical trends
2. Uses existing information
3. Provides evidence of ongoing trends and problems
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Limitations
1. Time-consuming
2. Resources may be hard to locate
3. Resources may be conflicting
4. May not identify cause of a problem
5. Information may be incomplete, obsolete, inconclusive, or inaccurate
6. Data restricted to what already exists

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. Examples include the following:
The One-Shot Case Study . In this arrangement, subjects are presented with some type of treatment, such as a semester of college work experience, and then the outcome measure is applied, such as college grades. Like all experimental designs, the goal is to determine if the treatment had any effect on the outcome. Without a comparison group, it is impossible to determine if the outcome scores are any higher than they would have been without the treatment. And, without any pre-test scores, it is impossible to determine if any change within the group itself has taken place.
One Group Pretest Posttest Study . A benefit of this design over the previously discussed design is the inclusion of a pretest to determine baseline scores. To use this design in our study of college performance, we could compare college grades prior to gaining the work experience to the grades after completing a semester of work experience. We can now at least state whether a change in the outcome or dependent variable has taken place. What we cannot say is if this change would have occurred even without the application of the treatment or independent variable. It is possible that mere maturation caused the change in grades and not the work experience itself.
The Static Group Comparison Study . This design attempts to make up for the lack of a control group but falls short in relation to showing if a change has occurred. In the static group comparison study, two groups are chosen, one of which receives the treatment and the other does not. A posttest score is then determined to measure the difference, after treatment, between the two groups. As you can see, this study does not include any pre-testing and therefore any difference between the two groups prior to the study are unknown.
Quasi-Experimental Design
Quasi designs fair better than pre-experimental studies in that they employ a means to compare groups. They fall short, however on one very important aspect of the experiment: randomization.
Pretest Posttest Nonequivalent Group . With this design, both a control group and an experimental group is compared, however, the groups are chosen and assigned out of

convenience rather than through randomization. This might be the method of choice for our study on work experience as it would be difficult to choose students in a college setting at random and place them in specific groups and classes. We might ask students to participate in a one-semester work experience program. We would then measure all of the student s’ grades prior to the start of the program and then again after the program. Those students who participated would be our treatment group; those who did not would be our control group.
Time Series Designs . Tim series designs refer to the pretesting and posttesting of one group of subjects at different intervals. The purpose might be to determine long term effect of treatment and therefore the number of pre- and posttests can vary from one each to many. Sometimes there is an interruption between tests in order to assess the strength of treatment over an extended time period. When such a design is employed, the posttest is referred to as follow-up.
Nonequivalent Before-After Design . This design is used when we want to compare two groups that are likely to be different even before the study begins. In other words, if we want to see how a new treatment affects people with different psychological disorders, the disorders themselves would create two or more nonequivalent groups.
Once again, the number of pretests and posttests can vary from one each to many.
The obvious concern with all of the quasi-experimental designs results from the method of choosing subjects to participate in the experiment. While we could compare grades and determine if there was a difference between the two groups before and after the study, we could not state that this difference is related to the work experience itself or some other confounding variable. It is certainly possible that those who volunteered for the study were inherently different in terms of motivation from those who did not participate. Whenever subjects are chosen for groups based on convenience rather than randomization, the reason for inclusion in the study itself confounds our results.
True Experimental Design
True experimental design makes up for the shortcomings of the two designs previously discussed. They employ both a control group and a means to measure the change that occurs in both groups. In this sense, we attempt to control for all confounding variables, or at least consider their impact, while attempting to determine if the treatment is what truly caused the change. The true experiment is often thought of as the only research method that can adequately measure the cause and effect relationship. Below are some examples:
Posttest Equivalent Groups Study . Randomization and the comparison of both a control and an experimental group are utilized in this type of study. Each group, chosen

and assigned at random is presented with either the treatment or some type of control.
Posttests are then given to each subject to determine if a difference between the two groups exists. While this is approaching the best method, it falls short in its lack of a pretest measure. It is difficult to determine if the difference apparent at the end of the study is an actual change from the possible difference at the beginning of the study. In other words, randomization does well to mix subjects but it does not completely assure us that this mix is truly creating an equivalency between the two groups.
Pretest Posttest Equivalent Groups Study . Of those discussed, this method is the most effective in terms of demonstrating cause and effect but it is also the most difficult to perform. The pretest posttest equivalent groups design provides for both a control group and a measure of change but also adds a pretest to assess any differences between the groups prior to the study taking place. To apply this design to our work experience study, we would select students from the college at random and then place the chosen students into one of two groups using random assignment. We would then measure the previous semester’s grades for each group to get a mean grade point average. The treatment, or work experience would be applied to one group and a control would be applied to the other.
It is important that the two groups be treated in a similar manner to control for variables such as socialization, so we may allow our control group to participate in some activity such as a softball league while the other group is participating in the work experience program. At the end of the semester, the experiment would end and the next semester’s grades would be gathered and compared. If we found that the change in grades for the experimental group was significantly different than the change in the grades of our control group, we could reasonably argue that one semester of work experience compared to one semester of non-work related activity results in a significant difference in grades.
Correlational Research
• To find if the data has an observable relationship that can be further specified in terms of magnitude and/or an increase or decrease.
Ex post facto (‘from what is done afterwards’)
• Studies that investigate possible cause and effect relationships by observing an existing condition or state of affairs and searching back in time for plausible causal factors.
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Researcher takes the effect/dependent variable and examines it retrospectively
• Establishes causes, relationships or associations and their meanings.
• Researcher has little to no control over independent variables.

• Flexible by nature.
• You can use this where more powerful experimental designs are not possible; when you are unable to select, control and manipulate the factors necessary to study cause and effect relationships directly, or when control variables except a single independent variable may be unrealistic and artificial.
Special research design
1. Ethnography
According to Spradley (1979), ethnography is "the work of describing a culture" (p. 3).
The goal of ethnographic research is "to understand another way of life from the native point of view" (p. 3).
Although this approach is commonly used by anthropologists to study exotic cultures and primitive societies, Spradley suggests that it is a useful tool for "understanding how other people see their experience" (p. iv). He emphasizes, however, that "rather than studying people, enthnography means learning from people" (p. 3).
Ethnographic research has broad implications for many fields, including education.
Professional development evaluators and staff developers can use this approach to understand teachers' needs, experiences, viewpoints, and goals. Such information can enable them to design useful and worthwhile programs for teachers and ultimately improve student learning.
2. Biblical
Bibliology is the study of the Bible, the Word of God. The Bible is the inspired source of knowledge about God, Jesus Christ, salvation, and eternity. Without a proper view of the Bible, our views on these and other issues become clouded and distorted. Bibliology tells us what the Bible is.
Bible- source of data.
Biblical research design is a complex and critical kind of study since it deals with something beyond superficial
Correlation Study

What is a correlation study?
A correlational study is a scientific study in which a researcher investigates associations between variables.Correlational studies are used to look for relationships between variables. There are three possible results of a correlational study: a positive correlation, a negative correlation, and no correlation. The correlation coefficient is a measure of correlation strength and can range from
–1.00 to +1.00.
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Positive Correlations: Both variables increase or decrease at the same time. A correlation coefficient close to +1.00 indicates a strong positive correlation.
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Negative Correlations: Indicates that as the amount of one variable increases, the other decreases (and vice versa). A correlation coefficient close to -1.00 indicates a strong negative correlation.
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No Correlation: Indicates no relationship between the two variables. A correlation coefficient of 0 indicates no correlation.
• Limitations of Correlational Studies:
While correlational studies can suggest that there is a relationship between two variables, they cannot prove that one variable causes a change in another variable. In other words, correlation does not equal causation. For example, a correlational study might suggest that there is a relationship between academic success and self-esteem, but it cannot show if academic success increases or decreases self-esteem. Other variables might play a role, including social relationships, cognitive abilities, personality, socio-economic status, and a myriad of other factors.
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Types of Correlational Studies:
1. Naturalistic Observation
Naturalistic observation involves observing and recording the variables of interest in the natural environment without interference or manipulation by the experimenter.
Advantages of Naturalistic Observation:
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Gives the experimenter the opportunity to view the variable of interest in a natural setting.
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Can offer ideas for further research.
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May be the only option if lab experimentation is not possible.
Disadvantages of Naturalistic Observation:
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Can be time consuming and expensive.
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Does not allow for scientific control of variables.
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Experimenters cannot control extraneous variables.
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Subjects may be aware of the observer and may act differently as a result.
2. The Survey Method
Survey and questionnaires are one of the most common methods used in psychological research. In this method, a random sample of participants completes a survey, test, or questionnaire that relates to the variables of interest. Random sampling is a vital part of

ensuring the generalizability of the survey results.
Advantages of the Survey Method:
 It’s fast, cheap, and easy. Researchers can collect large amount of data in a relatively short amount of time.
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More flexible than some other methods.
Disadvantages of the Survey Method:
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Can be affected by an unrepresentative sample or poor survey questions.
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Participants can affect the outcome. Some participants try to please the researcher, lie to make themselves look better, or have mistaken memories.
3. Archival Research
Archival research is performed by analyzing studies conducted by other researchers or by looking at historical patient records. For example, researchers recently analyzed the records of soldiers who served in the Civil War to learn more about PTSD (
Advantages of Archival Research:
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The experimenter cannot introduce changes in participant behavior.
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Enormous amounts of data provide a better view of trends, relationships, and outcomes.
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Often less expensive than other study methods. Researchers can often access data through free archives or records databases.
Disadvantages of Archival Research:
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The researchers have not control over how data was collected.
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Important date may be missing from the records.
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Previous research may be unreliable.