Major Issues in Sociology - Coursework Example

SOCIOLOGY First set FM Method of generating data on how doctoral spend their time at their residences Datacollection or generation requires the use of efficient tools that in addition to being reliable, also give consistent and rationally deductive results. Given the target group in this case study, the method adopted should be capable of giving an insight into the private lives of students, a course that may not be easy by any ordinary means. This paper attempts to analyze certain qualitative approaches that when effectively employed, have the potential of delivering quality data that is reflective of the general behavior of doctoral students in their residences. The data of interest in this case study is behavioral, and therefore adoption of a research methodology that involves field data collection through such means as observation and recording of behavior as they occur in their natural setting. This means that the researcher has to be in touch with the element under study and make observation and/ recording as it happens. While the theoretical explanation of this approach may appear complicated and tasking, it is worth noting that humans engage in qualitative data collection practices in almost all the daily interactions that we encounter. As noted by Giddens and Sutton (2010), participant observation is important in qualitative data collection as it allows the researcher to immerse into a system that in most circumstances is alien to the researcher, which could also limit the chances of biasness. In order to be able to collect data on student behavior, the following approaches can be adopted: I. Conduction of in-depth interviews In this case, the researcher conducts the interview on a one-on-one basis, and follows a general plan of inquiry. While citing Oakley, Jamshed (2014) notes that the framework of qualitative interview is such that in addition to recording the practices and standards, the researcher is also able to achieve greater coherence, challenge the respondent as well as reinforce the objective. Through this approach, the researcher is capable of interacting with every sample within the population. It is worth noting that the method allows the researcher to obtain adequate information while maintaining its confidentiality, since participation is voluntary. II. The second qualitative approach feasible for this type of research is immersion. In this case, the researcher plunges into the lifestyle of the students by living among them for a given period as may be convenient. However, this has the challenge that if the researcher is not of their age group, he/she may find it difficult to intermingle with them in order to be able to obtain adequate information. FM 2. How my gender, age, ethnicity and experience can enable me become a competent researcher. To begin within, the success of research work, especially those involving direct interviews as the major mode of data collection, relies heavily on the perception of the respondent towards the researcher, which again is influenced by such aspects as age, sex and to an extent ethnic background and experience of the researcher. For instance, the target groups in my case study are college students’ majority of who are in their youthful age. This puts me in a similar category with them, hence making it highly likely that any approach, whether immersion or direct interview will receive a warm reception. Furthermore, since immersion requires complete interaction with the students in order to learn their behavior, the fact that I also belong to the same age bracket will allow me to freely mingle with them. While sex also plays a role research context, with such behavior as male respondents being more receptive to female interviewers, the contrary being true as well, its impact is more prominent in one-on-one interviews, and significantly absent in immersion approach. Nonetheless, the researcher can opt to apply direct interview approach in the event that immersion fails due to gender biasness. My education background has enabled me to acquire research skills that are good enough not only to be able to conduct an interview successfully, but to make an interview successful by avoiding such obstacles as biasness due to difference in ethnic background. Furthermore, since my case study involves a target with which conversation can be effectively carried out in English, the chances of encountering ethnic inclination are almost zero. Finally, being socially interactive individual who is witty implies that I am capable of entice even notorious survey dissidents to take part in the survey. Secondly, my extensive charm will allow me to interact with students and be part of them in the event that prevailing conditions necessitate the need to employ immersion in data collection. FM 3. A critical evaluation of validity and reliability maximization methods employed by Sithic and Balasubramanian (2013) Any sound assessment of research methodology used must be free from distortion and bias. To measure the level of these two aspects, reliability and validity concepts are integral. While reliability determines the extent to which the assessment is consistent, validity deduces the level of accuracy of the said assessment. A study by the above-mentioned individuals employs two different methods in a bid to maximize the validity and reliability of their approaches in data mining in the motor insurance industry with an objective of detecting fraud. To begin with, the two individuals adopt clustering as a means of data mining. This method bases its procedure on partitioning the available objects into distinct and unique groups, with subjects in one cluster having similar traits, but which are different from those of subjects in a different cluster. The method then groups all the claims with similar characteristics into small subsets, a practice that allows the researcher to flag populations that with extreme traits and subjects the elements to further investigation. The validity and reliability of this approach relies on the high probability of detecting elements with unusual traits. To maximize this approach, the method utilizes the notion that outliers are actually possessing unusual traits. However, this may not be the case. The presence of outliers could actually signify the opposite. The presence of an outlier may arise from variability in the measurement or due to an error in the collection process. Additionally, such an observation could be indicative of the fact that the data has a heavy tailed distribution. Secondly, the two researchers espouse that prediction as a data mining technique can also be efficient under certain circumstances. The method utilizes the idea that future estimates may follow a given pattern similar to the currently observed and past trends. To maximize the validity and reliability of this method, the two advances for the application of the method with data that is continuous-valued as opposed to those that are categorical. It is worth noting that most insurance claims data are categorical, and hence validity and reliability maximization might fail in the latter, since the availability of data in the latter form implies a stalemate in the execution process. Maximizing validity and reliability fosters the applicability of the results obtained from a given research. Validity addresses the accuracy of the measurement instruments, the maximization of which makes them more acceptable as it translates to presentation of accurate data. On the other hand, reliability provides consistency of the instruments of measurement used, and whose consistency implies that performance of similar measurement would give almost similar results and similar conditions. However, it is worth noting that achieving maximum reliability does not imply maximum validity, and vice versa. Second set FM 1. Method of generating data on how doctoral students spend their time at their residences Sociologists, just like statistician make use of different data collection procedures. Of great importance to data collection procedure is the objective of the study. To this effect, researchers have categorized research approaches into two different categories, qualitative and quantitative approaches. Qualitative methods generally attempt to avail information regarding specific cases, but fail to provide empirical support to propositions. In order to avail such support, researchers do resort to quantitative methods of data collection by exploring the situation in totality. In line with this aspect, this paper analyzes the importance of employing quantitative data collection procedures in establishing the behavior of doctoral students in their residences. Quantitative research employs scientific methods in collection of data and uses mathematical formulas to carry out analysis on the data collected. Some of these scientific methods include survey research, correlational research, causal-comparative research and experimental research. Of these, only two are capable of providing adequate data and desirable results regarding behavior of doctoral students in their residences. The first method that can provide a researcher in this context is survey research. This involves the collection of data through interviews, questionnaires and sampling points. Klazema (2014) note that this approach is robust since it allows the researcher to observe and make informed judgment about a given set of behavior and subsequently present the result in an accurate way. Additionally, it entails random sampling of the population under study thereby availing data that covers a broader spectrum. Applying the same knowledge in the given case thus involves either conducting direct interviews or supplying questionnaires to the students at random, after which the data collected is analyzed to make informed deductions. Apart from survey research, the researcher can also adopt a causal-comparative methodology. Through this method, the researcher develops a hypothesis that for instance makes a given claim on a certain behavior, and proposing that it could be due to the level of their engagement with class work. In this endeavor, the researcher will have to perform the same study using a control group, most probably a student group that takes less demanding course. The key aspect of this approach is that it involves comparison, thus necessitating the existence of two groups to be studied. Simply put, quantitative methodology involves carrying out a keen observation on a given phenomenon and providing an explanation on the same, collecting the information using appropriate means, then analyzing the data collected to draw conclusions. Depending on the goals of the research, the researcher has to prepare a research question, termed hypothesis, for which the research procedure aims to prove or disapprove. FM 2. How my gender, age, ethnicity and experience can enable me become a competent researcher. Unlike qualitative research methodology, quantitative research methods are partially immune to the effects of gender, age and ethnicity. For instance, the obstacles relating to conducting direct interviews can be overcome by dropping questionnaires that the respondents fill at their convenient time. However, this has the disadvantage that respondents may fail to fill the questionnaire completely, or might fail to return them in good time. That notwithstanding, quantitative data collection involves extensive interaction with the respondent or the subject under study. In the case of our case study, interacting with students might prove to be a complicated task, though achievable. Case in point is the event that an age difference between the researcher and the respondent is so large to an extent that the respondent perceives the interviewer as either having fun time with students or merely trying to waste their time. While this appears easy to overcome, the general perception of a student after the maiden interaction with the researcher may be carried along in the manner in which the said student responds to the questions, even when a different person conducts the interview. Experience of the researcher, in the other hand, is critical to the success of the collection procedure. For instance, a researcher who employs causal-comparative approach ought to be highly efficient in not only running two surveys concurrently or successively, but also able to handle the resulting data with great care and competency. To this end, I have extensive experience in research, having studied research methodologies and even conducted a similar survey in the recent past. Furthermore, the survey I recently conducted gave me an opportunity to learn how to handle emergent issues in a similar setup. Secondly, choosing appropriate research methodology requires an in-depth understanding of the hypothesis under study as well as the projected outcome of the study. To this effect, the researcher in the case example will have to formulate a hypothesis that is in agreement with the objective of the research. This means that through the hypothesis, the researcher should be able to deduce the overall behavior trend among the students, in relation to the say the level of the student engagement in their academic work. Finally, while many people tend to believe that quantitative research is prone to subjectivity, experience in this field confirms otherwise. To avoid such an occurrence, Tohen et al. (2015) observes that the use of mixed method approach in trials, especially experimental trials, increases the chances of the researcher detecting meaningful patterns regarding the subject under investigation. This ability counters the potentiality of making misinterpretations or biasness originating from the observer’s side. FM 3. A critical evaluation of validity and reliability maximization methods employed by Sangra, Guardia and Girona (2002) Research generally involves tools the use of such as questionnaires and scale measurements in collection of data. These tools as well as other methods have to be reliable and valid. Reliability can be said to be the extent to which a research method gives stable and consistent finding. On the other hand, validity is the ability of a tool to accurately determine its intended measure. Such aspects cannot be overlooked while designing research tools for general types of research and to be more specifically in this instance, case studies. In the case study report, Benchmarking of Virtual Campuses, Sangra et al (2001), explore and analyze data from selected universities across European countries. The authors selected more than one university in Europe to validate its findings over a range of countries. However, this falls short in the manner that they fail to address the population and the time at which the establishments have been existent. The researchers further fail the internal consistence reliability test. The test failed to yield meaningful results when administered to the Spanish University. Secondly, though the researchers sampled different universities to come up with a benchmarked assessment test, this method fails to address learning backgrounds and thus failed to address parallel consistency. Furthermore, this method does not take into account the essence of giving more information or contrast with the physical mode of learning. Three of the countries come from the same region having been members of the former USSR. The scale used further gives plenty of qualitative data to which interpretation remain relative. To maximize reliability and validity, the researchers should have refined the tools and questions to a more specific local area and make the tool immune to susceptibility and hence dependent on self-report. They should further chosen the scale of measurement depending on factors under consideration. Testing validity for string characters is harder as compared to numeric. On the other hand, testing for accuracy and precision are a little more complex for continuous variables vis-a-vis categorical variables. Maximizing validity and reliability in any research methodology is critical to the acceptability of the data and hence conclusion established. In order to achieve this, researchers usually attempt to avail efficient maximization procedures. However, circumstances arise when achieving such an objective is impossible, an example of which has been broached earlier. In such a situation, the researcher has no option but to adopt the mechanism as it occurs, regardless of the extent of discomfort it may result to among readers. It is therefore imperative that research methodologies be maximized to avoid such petty confusions. References First set references Giddens, A., & Sutton, P. W. (2010). Sociology: Introductory readings. Cambridge: Polity. Jamshed, S. (2014). Qualitative research method- interviewing and observation. Journal of Basic Clin Pharm, 5(4). Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4194943/ Sithic, H. L. & Balasubramanian, T. (2013). Survey of insurance fraud detection using data mining techniques. International Journal of Innovative Technology and Exploring Engineering, 2(3). Second set references Klazema, A. (2014). Types of quantitative research for students and researchers. Retrieved from https://blog.udemy.com/types-of-quantitative-research/ Tohen, M., In Bowden, C. L., In Nierenberg, A. A., & In Geddes, J. R. (2015). Clinical Trial Design Challenges in Mood Disorders. Sangra, A., Guardia, L. & Girona, C. (2002). Benchmarking of virtual campuses. Spain, Universitat Oberta de Catalunya. Read More