PLEASERESPOND AND ANSWER EACH OF THE FOLLOWING QUESTIONS OR POST STATEMENTS. MUST BE 150 WORDS (PLEASE), WRITE IN 3RD PERSON. ONLY ONE REFERENCE CAN BE USED FOR EACH ANSWER.
DQ 1. At this point you should be narrowing in on potential topics for your dissertation. The specifics may not be targeted but you should know the general area you wish to research. Using the topic area you are considering, explain how the measurement concepts discussed in the text and readings could be used in your research. Why is it important to know the variables within your research study? What type of measurement instrument might you use for your study? Explain the benefits and possible drawbacks.
DQ 2. In "The Practice of Social Research," Babbie (2013) suggest the following research question as a simple example: Are social sciences teachers, natural sciences teachers, or arts teachers more beloved among students on a college campus?
To answer the research question, you might observe throughout a semester the attendance rates for a key course in each of the groups; review end of course surveys and compare average instructor ratings among the groups; or compare the number of cards, letters, and gifts received by faculty members in each group at the end of a semester.
Which of these methods may be good choices and which may not bring about the desired results? Why? What does your consideration of these options tell you about operationalization? Why is that significant?
The Practice of Social Research
Lecture 5
Measurement Concepts
Introduction
A good place to start to understand the measurement concepts used within the context of a dissertation is the GCU DC Network. It is a good idea to review and become familiar with the content housed in the Research Resources tab.
People use measurement concepts on a daily basis - often without being mindful of the actual process. For example, one may take measurements to compare the cost of gas, or interpret the results of a sample during a political election process. All of these cases have measurement in common - and there is sometimes a cause and effect relationship that one will quantify in some way. Measurement concepts are part of the research process in regard to forming and testing hypotheses, developing a procedure to collect data to prove or disprove hypotheses, collecting the actual data, forming results, and drawing conclusions.
Doctoral learners may engage in their research in many different ways. Qualitative researchers may want to know, for example, what a focus group thinks of their prototype product or service. Of course, as manager of this focus group process, the researcher would also want to know if the study was reliable and valid. In this case, a researcher would be likely to use a Likert scale to determine the level of interest in the new product or service. Further, the researcher may also want to focus on some dimension of participant's opinion - such as their perceptions of the frequency at which they would make a purchase. On the other hand, quantitative researchers may want to design a study that measures the effect of drinking diet soda on one's weight. In the latter case, the scientific method requires that a sampling method is specified so that the results can potentially be generalized to a larger group of diet soda consumers. Given the measurement considerations that emerge from these relatively easy studies, one can see that measurement becomes very relevant for most researchers.
Measurement Process
The first step in the research process is to identify a research problem that would benefit from the use of the scientific method (Babbie, 2011). The variables must be defined, the measurement system must be described, as well as how the measurement will take place in regard to the needed data instrumentation. Therefore, the data collection instruments, as well as the data analysis method, are very important components of the measurement process - and will be part of the doctoral learner's research proposal and dissertation.
Description
Sometimes researchers just want to describe situations or events using nominal, interval, ratio, or ordinal levels of measurement to answer questions of what, how, when, and where in regard to the concepts being studied (Babbie, 2011). The researcher will choose the level of measurement according to the objective of his or her research. Of course, when one speaks of measurement, one naturally thinks of the accuracy of observations - and if others would be able to reliably reproduce the results if they were to attempt to replicate a measurement technique. Indeed, one may also reflect on whether or not measurements are a valid way of measuring the "real" concept that they are trying to determine. Often, these concepts conflict with each other. For example, a test may be very accurate, but not easily replicable. Conversely, one may accurately take a measure in a reliable way that allows other researchers to arrive at the same results, but miss measuring the actual event that needs to be measured - meaning the measurement is not valid.
Sampling
It is often too costly, time consuming, or practically impossible to take a measurement of everyone or everything in the entire population (Babbie, 2011). In these cases, sampling helps to make inferences about the population from a relatively small representative group. One of the most widely used examples of sampling is the census that is completed every 10 years by the U.S. government. Another example is the case of the "estimates" of popularity of a political candidate during an election cycle. It is much quicker and cost efficient to use a sampling method to poll just a few hundred people and to then make inferences about the larger population from the relatively small sample size. Of course, the margin of error can be calculated in these cases, as well as the level of confidence that we have that the real results fall within the margin of error. Sampling, therefore, hopefully provides the researcher with generalizable inferences about the larger population.
Cause and Effect Analysis
If one or more independent variables appear, at face validity, to affect one "dependent" variable in a linear and consistent manner, then a test can be done to determine if there is indeed correlation between the variables. Correlation does not necessarily mean causation - a root cause analysis must be done to determine actual causality. However, it can reveal interesting and relevant effects between the variables. For example, the ambient outdoor temperature during a marathon may correlate in a linear way with the number of liters of water consumed by the participating athletes.
Conclusion
In this lecture, the sampling, cause and effect analysis, sampling methods, and measurement systems used in descriptive statistics have been discussed. Researchers must be very intentional in regard to what they measure, and how they measure and interpret the concomitant results. Thus, when a researchable problem is defined using the concepts from the first lecture of this course, one must be very mindful of any potential measurement systems that will be used in the process. This can be done through reviewing similar research and literature that may guide our study in regard to this component of the research process. As a practitioner, one uses the scientific method to solve problems on a daily basis. However, doctoral learners will use concepts of measurement in the process as they conduct research to add to the current body of knowledge in the field. There are relevant ethical considerations whenever measurement is used; therefore, the researcher must also be mindful of maintaining an ethical mindset throughout the measurement process.
References:
Babbie, E. (2010). The practice of social research. Belmont, CA.: Wadsworth-Cengage Learning.