Critique and Challenges of Questionnaire - Essay Example

METHODOLOGY: QUESTIONNAIRE Name Institution Course Tutor Date Methodology: Questionnaire Importance of Questionnaire Amongst the many instruments that can be used during a research to obtain data, questionnaire remains one of the commonly used in the contemporary studies (Saris & Gallhofer 2007). It is a research instrument involving a series or set of questions upon which the intended information is based as primary guidelines. In a study where a questionnaire is used as a methodology of acquiring data, numerous benefits are realised upon its effective employment. First, it can be argued that the use of questionnaires in a research permits respondents time to consider their thoughts and perspectives before providing their responses. According to Olson (2010), unlike other methodologies such as interviews, which may not give such privileges, questionnaires can anticipate and eliminate or prevent interferences and biasness. In this perspective, it can be argued that questionnaires opt carefully thought data or information. Secondly, Saris & Gallhofer (2007) argues that the methodology can be relatively cheap as compared to other instruments of obtaining data during a research. In terms of cost, copies of a series of questions can be issued to many respondents simultaneously; unlike in other such as interviews where a respondent is handled one by one, hence time consuming and relatively costly. There are certain factors that impact the quality or reliability of information that is obtained during a study. Such actors as anonymity remain one of the common ones that many intended respondents consider before their participation (Saris & Gallhofer 2007). However, with the use of questionnaires where anonymity and free express on opinion is encouraged and promoted, reliability is guaranteed and biasness is prevented. The use of questionnaire encourages anonymity hence enhances the quality of the intended information. Generally, questionnaires can be argued to be fast, relatively inexpensive, and considerably easy to employ in a research. Types and structure of questionnaire Just as it is in the case of interviews or guidelines for observation as a method in a research, logic is an essential aspect in the flow of questions. In an endeavour towards obtaining reliable information or data in a study, it is necessary that the questions’ logic of flow utilizes the idea of least to most in terms of sensitivity; the questions should begin with least to most sensitive ones (Olson 2010). Also, factual towards behavioural and then attitudinal should be the other criterion (Saris & Gallhofer 2007). It is these areas of classification that give rise to the types of questionnaires, which include questionnaires that entails questions for measuring separate variables and those that have questions that are aggregated into scale or index types (Saris & Gallhofer 2007). It is the primary theme of the research that determines the type and flow of questions in a questionnaire, hence its appropriateness. Critique and challenges of questionnaire In as much as questionnaires can be said to be quick, inexpensive and easy to analyse, amongst many other benefits including the fore-mentioned, the methodology is also subject to certain areas of critique. There are certain primary rules that a research needs to consider before or whilst using this method in his or her research. For example, it is imperative to ensure that the structure of the questions permits difference in answers and perspectives (Olson 2010). Also, it is important to use questions that can be interpreted in the same way by every participant (Saris & Gallhofer 2007). Besides the rules, the use of questionnaires in a research also follows certain administration modes upon which the reliability of the information, as well as validity, is maximized. According to Olson (2010), some of these modes include: face-to-face; paper-and-pencil; computerized questionnaire, and adaptive computerized questionnaire. Therefore, depending on the type of administration, the effectiveness of the methodology, as well as the efficiency of its employment during research, can be guaranteed. Concerning the challenges that a researcher may encounter whilst using a questionnaire to collect data during research, the methodology presents certain areas of problems. For instance, research using questionnaires to conduct their study may not be aware of whether respondents understood the questions or what is expected of them (Saris & Gallhofer 2007). Moreover, still on the questions asked, the data obtained through this type of research instrument can be minimal due the fact that questions tend to be relatively more specific based on what the research is for. Additionally, based on the mode of administration, questionnaires can also have very low rates of returns, especially where face-to-face mode is not an option (Olson 2010). Therefore, despite the benefits, it is also important to consider these challenges, amongst others. Data population and sampling One of the important aspects of research is to know the target population for participation and being aware of the number of respondents that are required for the effectiveness and validity of the method chosen. Bertlett et al. (2001) advice that making sure of the accuracy of the estimates and ensuring that errors are anticipated and minimized if not completely prevented are some of the major procedures for effective sampling in research. However, the author argue that the task of determining the ideal population and sample size can sometimes turns out to be challenging. Therefore, it is imperative to comprehend the factors upon the target group and the number required is based. The target population is based on the main theme on which research is conducted, which then ensures that participants chosen are the ideals for the topic (Waure et al. 2015). For instance, customer segmentation as a topic of research for an emergent business in an urban centre would consider participants relevant to the intended product. The idea of sample size that is appropriate in research is determined by confidence levels and margin of errors. Bertlett et al. (2001) explain that the idea of maximising reliability and validity of data obtained through questionnaire, the number of participants or questionnaires used during the study should be large enough to prevent biasness, encourage many responses for comparison and analysis, and maximise confidence. However, it is also imperative to note that too large size can also cause huge marginal errors, which should be prevented. Therefore, with a confidence level of 95%, calculating sample size upon determining the population would be as follows. i. Sample size calculation ii. Finite population correction The above distribution of 50% population would result in confidence level of 95% and a score of 1.96, which are some of the accepted values in research. Sampling techniques There are various methods of sampling in research. Snowball and non-probability are amongst the commonly used in most statistics and sociology research. Based on the non-probability sampling technique, the selection is not random (Waure et al. 2015; Heckathom 2002). In this criterion of sampling, the population is not represented well as in the case of probabilistic method, which makes it relatively challenging to determine or estimate confidence well. However, it is sometimes not feasible or theoretically sensible to employ random selection criterion in a research, hence non-probabilistic techniques can be effective, especially in social studies. Snowball sampling criterion is the further classification of non-probability approach to sampling where the study subjects recruits the future ones; the first respondents can be used to make estimates and implications on the future ones (Kaplan et al. 1987; Cochran 1977). For instance, it is relatively challenging to conduct a study with drug users as the population. It is the idea of snowballing that gives the study an opportunity to estimate the data for other future participants. However, the idea can be used to acquire knowledge based on the associations from the previous acquaintances (Waure et al. 2015; Kaplan et al. 1987), making it significant to make use of the first encounters whilst sampling. Therefore, the validity of the research with its population and sample depends on the use of multi-stage cluster selection criterion. Data analysis using SPSS Upon collection of data in research, the information is analysed for implications that can advise recommendations and decisions. Data analysis entails such steps as questionnaire checking, coding, data cleaning, and application of appropriate tools for analysis (Green 1996). SPSS is one of the popular packages for data analysis. In SPSS data analysis, T-test for mean variation, Chi-square tests for ensuring independence of variables used, correlation, and regression are used to observe the data (Greasley 2007). Therefore, T-test, and chi-square are the major tests involved. Reference List Bertlett, JE, Kotrlik, JW & Higgins, CC 2001, ‘Organisational research: determining appropriate sample size in survey research’, Information Technology, Learning and Performance Journal, Vol. 19, No. 1, pp. 43-50. Cochran, WG 1977, ‘Sampling techniques (3rd Ed.)’, Wiley. Greasley, P 2007, ‘Quantitative data analysis using SPSS: an introduction for health & social science’, New York, NY: Open University Press. Green, SM 1996, ‘Using SPSS for Windows: analysing and understanding data’, Upper Saddle River, NJ, USA: Patience Hall PTR. Heckathom, DD 2002, ‘Respondent-driven sampling II: deriving valid estimates from chain-referral samples of hidden populations’, Social Problems, Vol. 49, No. 1, pp. 11-34. Kaplan, CD, Korf, D & Sterk C 1987, ‘Temporal and social contexts of heroin-using populations: an illustration of the snowball sampling technique’, The Journal of Nervous and Mental Disease, Vol. 175, No. 9, pp. 566-574. Olson, K 2010, ‘An examination of questionnaire evaluation by expert reviewers’, Sociology Department, Faculty of Publications, Field Methods, Vol. 22, No. 4, pp. 295-318. Saris, WE & Gallhofer, IN 2007, ‘Design, evaluation and analysis of questionnaire for survey research’, New Jersey, NJ: John Wiley & Sons, Inc. Waure, C, Poscia, A, Virdis, A, Di Pietro, ML, & Ricciardi, W 2015, ‘Study population, questionnaire, data management and sample description’, Ann Ist Super Sanita, Vol. 51, No. 2, pp. 96-98. Read More