Reply to students
Reply to other classmates’ threads, providing commentary, feedback, suggested reading, or questions for consideration. Reply must be 250 words and provide 1 reference in APA format.
Student 1 Response
Let’s say that you are researching a topic that concerns all fifth-grade students in the United States. Trying to gather data for every fifth-grade student in the United States is not a feasible task. A researcher would not even have access to that many students. A generalization will be concluded about the population that is being studied and that generalization will need an adequate sampling in order to be valid. “The sample is the group of elements or a single element, from which data are obtained” (McMillan, 1996, p. 86). Sampling allows for the study of a part that represents a whole of a population and techniques are needed to ensure that the sample will lead to a valid conclusion. “Sampling techniques tell us how to select cases that can lead to valid generalizations about a population, or the entire group you wish to learn about” Check & Schutt, 2012, p. 91). The sample must be an ideal representation of the population that is being studied. The sample must share the same characteristics of those of the total population (Check & Schutt, 2012).
Before determining the sample, it is important to have a detailed description of the population characteristics that is to form the focus of the study. There are a variety of methods in determining sampling for educational research and the caliber of representatives is based on the sampling procedures used (McMillan, 1996). Check and Schutt (2012) state that an important distinction about samples is whether they are based on a probability or a nonprobability sampling method. When using the probability sampling, the researcher knows in advance the likelihood the any element of a population will be selected for the study (Check & Schutt, 2012). “Probability sampling is a method of sampling in which the subjects are selected randomly in such a way that the researcher knows the probability of selecting each member of the population” (McMillan, 1996, p. 87). The random selection reduces the chance of having systematic bias in the selection elements. Sampling methods that do not let the researcher know in advance the likelihood of selection is called nonprobability sampling methods (Check & Schutt, 2012). “Nonprobability sampling methods can be useful when random sampling is not possible, when a research question does not concern a larger population, and when a preliminary exploratory study is appropriate” (Check & Schutt, 2012, p. 112).
Probability sampling methods are further broken down into types of random sampling. There are four types of random sampling: simple random sampling, systematic random sampling, cluster sampling, and stratified random sampling. Some examples of nonprobability sampling methods include availability sampling, quota sampling, purposive sampling, and snowball sampling (Check & Schutt, 2012). Sampling directly affect research; therefore, it is essential to know the characteristics of different sampling procedures (McMillan, 1996).
Researchers, according to McMillan (1996), “should first be able to identify the sampling procedure and then evaluate its adequacy in addressing the research problem and in supporting the conclusions” (p. 94). The research process is challenging for those charged with seeking answers, however in Proverbs 3:6 (English Standard Version) the Bible tells us that “in all your ways acknowledge him, and he will make straight your paths”. Staying the course and following the proper procedures can lead to valid results.
Check, J. & Schutt, R. (2012). Science, schooling and educational research. Research Methods in Education (pp. 2-20). 55 City Road, London: SAGE Publications, Inc. doi: 10.4135/9781544307725.
McMillan, J. H. (1996). Educational research: Fundamentals for the consumer. HarperCollins Publications, Inc.
Student 2 Response
In order to take a value sample in an educational setting, a researcher must follow a variety of steps. First of all, one step is knowing exactly what population a sample can represent when you select or evaluate sample components. Indeed, it is important to clearly define the population that the survey is attempting to describe. A distinction is usually required between the desired target population, or the population that one would wish to cover in the survey, and the defined population – a restriction on the desired population due to the practical difficulties in reaching certain elements. In fact, according to the reading, clear definition of such a population is difficult (as we saw in the previous chapter) but quite necessary. Anyone should be able to determine just what population was actually studied, so we would have to define clearly the concept of “at-risk students” and specify how we determined their status (Check & Schutt, 2012). Then, another step is to define clearly the population from which we will sample, we need to determine the scope of the generalizations we will make from our sample. Indeed, the writers (Check & Schutt, 2012) recommend focusing on three main questions to assess sample quality when you are planning or evaluating a study, and to ask yourself these questions:
· From what population were the cases selected?
· What method was used to select cases from this population?
· Do the cases that were studied represent, in the aggregate, the population from which they were selected?
Therefore, the goal is to select a sample that will adequately represent the population, so that what is described in the sample will also be true of the population. The best procedure for selecting such a sample is to use probability sampling, a method of sampling in which the subjects are selected randomly in such a way that the researcher knows the probability of selecting each member of the population.
Lastly, according to the reading, “generalizing from smaller samples to larger populations is important because frequently we lack both the time and the money to undertake surveys involving thousands or tens of thousands of people”. (Check &Schutt, 2012). Also, it is important for a researcher to carefully plan in order to develop a well-designed sample in order to advance knowledge about the population to be sampled, and adherence to systematic selection procedure so that the selection procedures are not biased.