The purpose of this section is to compare and contrast case study and quasi-experiment research designs. I will outline how they differ in their general purpose and goals, which in turn dictates their differences in approaching sampling concerns, the type of data collection methods they employ, and the data analysis techniques they employ. For example purposes, I will be utilizing Dorothy Winsor’s Engineering Writing/Writing Engineering to exemplify case studies and Barry Kroll’s Explaining How to Play a Game to exemplify quasi-experiments. Case studies are qualitative descriptive studies, whereas quasi-experiments are quantitative studies. Therefore, while the main purpose of case studies is to merely “discover [and identify] variables” within …show more content…
However, since the two differ in their overall goal, their primary interests and methods of receiving a non-random sample differ. In case studies, emphasis is placed on obtaining a representative sample. As MacNealy states, “if several subjects are [being] studied, then the researcher may want to consider how to best achieve a representative sample” (201). A representative sample is key within case studies, because case studies are designed to help build upon preexisting theories and help generate new ones, so it is important that the subjects providing insight actually have some relevance to the study. MacNealy makes this clear when she states, “a researcher will want to select a subject who is typical of some area of interest to begin to collect insights which, when combined with other insights from other empirical projects, could be used to build a general theory” (201). For example, in Engineering Writing/Writing Engineering, Winsor chose her subject, John Phillips, because he is an Engineer, and therefore relevant to her study; her case study can help frame future research within the scope of engineering and writing only because Phillips represents the sample of people within this field. However, in case studies, researchers cannot generalize beyond their representative sample. On the other hand, in quasi-experiments, pretests are of high importance and “research design hypotheses,” in which researchers make generalizations in order to “account for ineffective treatments and threats to internal validity” are crucial (179). Lauer and Asher state that the “quasi-experiment must have at least one pretest or prior set of observations on the subjects in order to determine whether the groups are initially equal or unequal on specific variables tested in the pretest” (179). This practice is seen in Kroll’s Explaining How to Play a Game,”
What is a case study? A case study is a process or record of research in which detailed consideration is given to the development of a particular person, group, or situation over a period of time. There is many different types of cases; rape, robbery, arson, kidnapping and finally murder. Case studies lead to trials;a formal examination of evidence before a judge, and typically before a jury, in order to decide guilt in a case of criminal or civil proceedings. One famous case study that went to trial was Jodi Arias Trial. Her case was her getting convicted of brutally murdering her ex-boyfriend, Travis Alexander.
Quasi-experimental designs are experimental designs that do not provide for the full control of extraneous variables. Primarily, the absence of control in this design is due to the lack of random assignment to groups. Quasi-experimental research designs are used in the study of cause and effect by manipulating the independent variable.
According to our book “anecdotes are first- or secondhand reports of personal experiences. They can include specific information about measures of learning, such as the number of errors made, but they are more often less specific” (Chance, 2014). And case study “examines a particular individual in considerable detail” (Chance, 2014). Last is experimental study “ is a study in which a researcher manipulates one or more variables (literally, things that vary) and measures the effects of this manipulation on one or more other variables” (Chance, 2014). The pros of experiment study is “control over variables, easy determination of cause and effect relationship, better results” (2014, Advantage and Disadvantage of Experimental Research). And the cons of experiment study is “failure to do experiement, creates artificial situations and subject to human error. (2014, Advantage and Disadvantage of Experimental Research). And the kind of experiment that statistical analysis is least likely to be necessary is anecdotes because they are personal experience and personal experience can be made up or not
According to Jimenez-Buedo (2011), it is difficult to make a valid reference that there is a causal relationship when conducting an experiment in a laboratory-style setting. Jimenez-Buedo (2011) also states that both internal and external validity are being inferred without adequate evidence to support the claims being made in many cases. Jimenez-Buedo (2011) also states that generalization of results in the case of external validity should not be taken lightly. In other words, it appears that she feels that neither internal nor external validity should be inferred in many cases associated with experiments that are done in a laboratory setting versus the real world. This appears to mean that in all circumstances Jimenez-Buedo (2011) favors conducting experiments that are as representative as possible of the real world in order to be able to validate the results and in order to infer a causal or generalizable relationship.
According to Smith (1983) quantitative research is to explain, predict and develop laws that can be universally applied and Qualitative research is the interpretation and understanding of what people give to their situation. The researchers clearly stated the purpose of their studies, aim, objectiv...
An important part of an experiment is random assignment. If the participants for the study are randomly assigned to create two groups, and the researcher has enough participants in the study to have the desired “probabilistic equivalence” (Trochim & Donnelly, 2008, p. 187) then the researcher will feel a sense of confidence that the study will have internal validity in order to assess whether or not the treatment caused the outcome hypothesized. Well-c...
The father of quantitative analysis, Rene Descartes, thought that in order to know and understand something, you have to measure it (Kover, 2008). Quantitative research has two main types of sampling used, probabilistic and purposive. Probabilistic sampling is when there is equal chance of anyone within the studied population to be included. Purposive sampling is used when some benchmarks are used to replace the discrepancy among errors. The primary collection of data is from tests or standardized questionnaires, structured interviews, and closed-ended observational protocols. The secondary means for data collection includes official documents. In this study, the data is analyzed to test one or more expressed hypotheses. Descriptive and inferential analyses are the two types of data analysis used and advance from descriptive to inferential. The next step in the process is data interpretation, and the goal is to give meaning to the results in regards to the hypothesis the theory was derived from. Data interpretation techniques used are generalization, theory-driven, and interpretation of theory (Gelo, Braakmann, Benetka, 2008). The discussion should bring together findings and put them into context of the framework, guiding the study (Black, Gray, Airasain, Hector, Hopkins, Nenty, Ouyang, n.d.). The discussion should include an interpretation of the results; descriptions of themes, trends, and relationships; meanings of the results, and the limitations of the study. In the conclusion, one wants to end the study by providing a synopsis and final comments. It should include a summary of findings, recommendations, and future research (Black, Gray, Airasain, Hector, Hopkins, Nenty, Ouyang, n.d.). Deductive reasoning is used in studies...
A researcher uses an experiment to scientifically test out a hypothesis. In an experiment there are many different factors that are involved. There is the independent variable, which is the cause, it is the one that is being manipulated, and the dependent variable, which is the effect, is the response. When conducting a experiment it is important to make sure that the only thing than can affect the dependent variable is the independent variable. This is known as internal validity. Using random assignment to separate the participants into groups helps eliminate any outside factors, and creates an equal chance for all participants to be apart of the experimental conditions. There are many pros and cons to this type of method. The experimental method creates a strong control of the variables involved in the experiment, which allows an easier determination on cause and effect. If needed, it is fairly easy to replicate an experiment and is less time consuming than other research methods. However there are many downfalls as well. When conducting an experiment the setting of where the experiment is taking place is more artificial which may cause certain behaviors that wouldn’t occur in real life. This is known as external validity, which is the measure of how much the results of a study can be generalized and used in different situations, and people. To improve external validity cover stories are created when conducting experiments so the participants are not aware of what is really going on, or experiments are done in a natural setting as opposed to in a laboratory. However, this creates less control over confounding variables that can affect the experiment, which can create bias results (Aronson,
Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches (3rd ed.). Thousand Oaks, CA: Sage Publications.
Now within the rest of this paper you will be finding a few different things getting discussed. Staring it off we will be discussing the articles that we have found to make our arguments and hypotheses. After wrapping up the literature reviews we will be discussing the hypotheses thus continuing onto our variables and indicators. Once we discuss our hypotheses we will be moving onto the research design. The research design will have our general issues, sampling, and methods.
The nature of research instruments, the sampling plan and the type of data the research design constitutes the blueprint for the collection, the measurement and analysis of data. It aids the researcher in the allocation of his limited resources by posing crucial choices.
We believe it is clear that both qualitative and quantitative research have many benefits and many costs. In some situations the qualitative approach will be more appropriate; in other situations the quantitative approach will be more appropriate.
Qualitative and quantitative research methods take different approaches to gathering and analysing information. Whether it is a qualitative or quantitative study, the research study begins with a question or series of questions. Both use rigorously designed studies to get the most accurate, detailed and complete results. Qualitative studies common methods are interviews, surveys and observation. A qualitative study aims to provide a detailed description of the study results, often using pictures and written descriptions to describe what the research revealed. A qualitative study looks at the big picture, helping researchers to narrow in on points of interest that then can be followed up on in a quantitative study. While a quantitative study has a narrower focus, it attempts to provide a detailed explanation of the study focus, along with this using numbers and statistics. And the results from a quantitative study can reveal bigger questions that call for qualitative study. Or vice versa a qualitative study may reveal at analysis that a more focus and direct approach may be needed. With both methods analysis is a key part of any study whether qualitative or quantitative.
Case studies are a collection of data obtained using various methods gathered on an individual or group to record areas of interest in order to assist with analysis and provide recommendations. The study should include the name of the person, although this should be protected to provide anonymity where appropriate, and a brief description of the subject. The setting where the study is to be performed should be included. The aim of the observation must be presented along with a report of the findings. The type of method used will depend upon the subject and the area of interest. Data is gathered on the subject in this case observations were used to provide the data. An interpretation of the study will be made in order to provide a conclusion and recommendations made if applicable. Freud famously used the case studies that he carried out on his patients to develop his Psychoanalytic Theory.
The key to good research is preparation, preparation, and preparation. Hence, the key to making good sampling choices is preparation. Trochim (2008) defines sampling as the drawing of a sample (a subset) from a population (the full set). In our everyday lives we all draw samples without realising it. For instance, when one decides to taste some unfamiliar food or drink that is some form of sampling. Williams (2003 74) posits that “Sampling is a search for typicality). On the other hand, (Clark: 2006 87) defines sampling as “a process of drawing a number of individual cases from a larger population”. According to (Chiromo: 2006 16), “a sample is a smaller group or subset of the population”.