Debating Structured vs. Unstructured Methods for Qualitative Research - Assignment Example

? RESEARCH Discussion Questions ………………………….. College ……………………………… ……………….. Assignment Week: 5, Discussion: 3 Debating Structured vs. Unstructured Methods for qualitative research Interviewing is perhaps one of the most effective data collection methods used in qualitative research as it allows the researcher to gain insights in to other’s perspectives regarding the phenomena which is under the research. There are basically two types of interviews, structures and unstructured (Shank, 2006, p. 50). Goodwin and Goodwin (1996, p. 136) categorized interview in to different four categories based on literatures. They identified structured, semi-structured, informal and retrospective interviews. Structured interview is one that uses preset and preplanned questions whereas unstructured interview is one that doesn’t use predetermined questions except at the very beginning. In qualitative study, structured interview focuses on open-ended questions on response categories that are probably more complex than worded-rating scales such as likert scale used in questionnaire method. Since each respondent is asked the same set of pre-set and pre-established questions in the same order in a structured interview, most researchers avoid this method because of that it tends to stifle the flexibility (Daymon and Holloway, 2010, p. 224). Researchers usually avoid structured interview in qualitative research because they find it most useful as a pilot tool for writing an effective survey instrument and surveys have the advantage of being easily distributed to several people at the same time (Shank, 2006, p. 50). Structured interview is more or less a kind of survey instrument and this is evident from Maxwell’s (2012, p. 88) point that structured interview is equated with quantitative research. He advocated that structured method is useful for comparing data across individuals, times, settings etc, but unstructured method is more preferable in qualitative research because of that it allows the researcher to focus on a particular phenomena that is under the research. Miles and Huberman (1994, p. 17) suggested structured interview for researchers who work with well-delineated constructs. They stressed that structure interviews provide clarity and focus for those researchers who are new in the field and are quite worried about diffusions or overload. Though both structured and unstructured have merits and demerits and are fit for certain various different research purposes, unstructured method is more equated to qualitative research and is more flexible since it allows the researcher use dynamic, deviated and wise questions according to varying circumstances. Most literatures including Maxwell (2012, p. 89) and Miles and Huberman (1994, p. 18) emphasized that unstructured interview provided more economical, comparable and potentially generalized findings. Conducting an unstructured interview perhaps requires a great deal of skills and talents, but still, it has the virtue of being guided by the interviewee. In this discussion form, I strongly recommend that an unstructured interview is always better as the researcher is allowed to focus on particular phenomena and to follow the interests of informants when they relate to their own thought process. References Daymon, C & Holloway, I. 2010, Qualitative Research Methods in Public Relations and Marketing Communications, Second edition, Routledge Goodwin, W. L & Goodwin, L.D. 1996, Understanding Quantitative and Qualitative Research in Early Childhood Education, Teachers College Press Shank, G.D. 2006, Qualitative Research: A Personal Skills Approach, Second Edition, Merrill Prentice Hall, Pearson Education Inc Maxwell, J.A. 2012, Qualitative Research Design: An Interactive Approach: An Interactive Approach, SAGE Miles, M. B., & Huberman , A.M. 1994, Qualitative Data Analysis: An Expanded Sourcebook, SAGE Assignment: 2, Week 5 Application Position paper on sample size In sampling, one of the most ticklish question is how large or small should be the sample size. If the sample size is too small, it may be easy for in-depth study of each individual, but it may not serve to achieve the objectives. If the sample size is too large, it may provide more meaningful research data, but it is more likely to incur higher costs and waste of resources. It is generally agreed that an optimum sample size, that is neither too large nor too small, is more preferable to provide both in-depth insights and for more meaningful research data. Literatures have poised different suggestions on what method of sampling will be more effective when sample size is small or when it is large. For instance, random sampling can be very effective when the sample size is small, but a stratified sampling is preferred when the size is quite large (Maxwell, 2012, p. 97). In research literatures, it is a general consensus that a large sample size is more likely to be more representative than a small sample. This principle is often termed as Law of Large Numbers that states that larger the sample size, the more likely that the values obtained from the sample are similar to the actual values of population. A sample is a large sample is more likely to represent the whole population than in a sample with small size (Gravetter and Forzano, 2010, p. 142). In contrast, large sample size has been found to yield type II errors, where the researcher may accept the findings of the research when he rejects the same. Type II errors are more likely to occur in large sample sizes because even weak relationship between two variables might reach to a significance stance and the researcher will come to believe the relationship found in the sample when in reality it is not true (Sekaran and Bougie, 2010, p. 296). Since a sample selected from small sample size may not accurately represent the values in total population even though it helps the researcher conduct an in-depth study of each individual, I recommend a large or optimum size for sample because the sample selected from a large sample size is more likely to represent the population and thus provides more accuracy for the data to be gathered. Based on Roscoe’s study, Sekaran and Bougie (2010, p. 296) proposed certain rules of thumb for determining sample size. According to this rule, sample size larger than 30 and not more than 500 are more appropriate for most researches. Secondly, when samples are to be broken down in to subsamples such as males & females, seniors & juniors etc, a minimum sample size of 30 or below can be preferred. I propose to select a sample size of below 500 population for my research so as to ensure representation of accurate value between sample and population along with ease of in-depth study up to an extent. References Gravetter, F. J & Forzano, L. B, 2010, Research Methods for the Behavioral Sciences (Gravetter), Cengage Learning Maxwell, J.A. 2012, Qualitative Research Design: An Interactive Approach: An Interactive Approach, SAGE Sekaran, U, & Bougie, R. 2010, Research Methods for Business: A Skill Building Approach, Fifth edition, John Wiley & Sons, Assignment: 3, Week: 5 Journal on Role of the researcher in the data collection procedure A researcher begins collecting data once he completes designing the sample or data collection methods such as interview, survey etc. When the researcher initially visualizes how the research project will unfold and emerge, he also imagines how the data will look like and how these data can be organized or made available for further analysis. The researcher is required to follow certain step-by-step procedures to collect data in a systematic and scientific way. For collecting data, there are primary and secondary sources and there are different types to each of these categories. The researcher has to necessarily assess the accuracy and effectiveness of the data he proposes to collect from a specific source. The researcher has to define the research purpose and accordingly select data collection method. It is critically important to decide whether to select structured or unstructured interviewing or to decide whether a large sample or smaller sample size to be selected for collecting data. In data collection, the researcher reviews coded field notes and then enters the data in to displays or scripts by using a word processor or by any other writing accompanying analytic texts. This provides a conclusion drawn from the displayed data (Miles and Huberman, 1994, p. 17). When the researcher uses quantitative research, he is tempted to reduce the data to computerizable form and then enters in to a database. He then endeavors to analyze the data by using a packaged statistical program or application. But in contrast, qualitative data cannot be easily handled as is possible in the case of quantitative data. If the researcher doesn’t care about converting qualitative data in to symbols or models in database or computerizable formats, then he is more likely to make mistakes because qualitative data cannot be accurately represented quantitatively to computer-analyze them (Berg, 2009, p. 53). Qualitative data take different forms such as audio, video, textual and so on. Collecting and organizing of qualitative data depend on what and how the data look like. If these data are in textual form like field notes or can be converted to textual form from a tape-recorded interview, this can be organized in one manner. If these data are video, audio or photographic material, then the researcher requires a different form of data collection as well as data organization method. In data collection, one of the most critically important roles a researcher should play is that he should maintain a relationship between research question and data collection method. The method a researcher may select for data collection may not follow logical deductions from the research question. As there is not any easier way to directly convert research question in to research method, it is important that the researcher should understand that the method is simply a means to answering or finding the solution for the research question. References Berg, B. L. 2009, Qualitative Research Methods for the Social Sciences, Seventh Edition, Allyn & Bacon, Pearson Education, Inc. Miles, M. B., & Huberman , A.M. 1994, Qualitative Data Analysis: An Expanded Sourcebook, SAGE Read More