Validity and Reliability Clause Samples
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Validity and Reliability. Having seen the results of the model it is now appropriate to discuss the validity in relation to the applied methodology. Most of the issues with regards to validity have to do with the data used. Especially when it comes to the skills required and the experience needed to perform jobs, the data sets do not contain all of the options a worker or job has in real life skill sets. As mentioned in „Competence and work experience‟ in Chapter 4 most of the workers posses a combination of either mechanics and hydraulics, or electrics and automation (PLS). There are a couple of service engineers that for instance have electrics and mechanics, or electrics and hydraulics. Even so, each worker has what is known a primary and secondary skill. Because of this, the data used comes mainly from the primary skills leaving either mechanics or electrics left. A job from a customer may require a service engineer with hydraulics or PLS background and would then, in the data set, be converted into mechanical or electrics. This simplification is based on the presuppose that the problem would be easier to model and formulate in AMPL. Only a few jobs require hydraulics or PLS, but not all of the workers with mechanical or electrician skills can perform these. Determining if a worker is able to perform the tasks required of him for a certain job is very difficult. Because of the lack of competency records the PC has to telephone each person to confirm whether or not he can perform the job described by the customer in the job pack. Even though it seems that a mechanical job can be performed by any service engineer with a mechanical background, there are some instances where this may not be the case, due to special circumstances. Because of this uncertainty the simplification to disregard this issue has been made, allowing every worker with the same skill as the job to be allocated to it without further ado. When dealing with large amount of data and manual labor, some input errors are usually made. In the table 2 there is a deviation of 3 days in the first data set and in the second data set 13 days. But because of the large number of days used in these sets both errors only result in 0.2% variation from one another. When it comes to the model and data set, because the model does not consider historical data, jobs with start dates before day 1 in the time period are not fully included. Nor are the jobs with finish dates later than day 45 as explained earlier. As a result a truly c...
Validity and Reliability. Maximizing validity and reliability in qualitative work requires a researcher to be both reflexive about her own role in data collection and to provide rich data to confirm findings. In this section, I share my own perspective as the researcher and reflect the ways this perspective might have influenced the research process. I also discuss threats to reliability, internal validity, and external validity, and share measures I took to minimize these threats. prior contact with the schools, my own educational philosophy, and my personal experiences may have predisposed me to see the data differently than another researcher. During the study, I acted mainly as an observer within classrooms, and asked teachers to see me as an observer rather than a participant. On occasion, students would ask me for help during independent work time, and I infrequently asked students about what they were learning or doing. As students were often curious about the information I was typing on my computer, I showed my notes and noted how I was writing down what happened in the class “like a play.” In classrooms where students did not understand their learning activity and were not being helped by an adult, I helped to explain the activity they were being asked to complete. This role and perspective opened me up to specific biases as a researcher. In the following sections, I discuss the ways in which I attempted to limit these potential sources of bias. Internal validity. Internal validity ensures that the findings accurately reflect the phenomenon under study. Because in qualitative research, the investigator is herself the instrument for the study, I used internal validity checks to hold myself accountable to accurately describe and investigate the schools in this study. I engaged in multiple methods of triangulation (Merriam, 1998), seeking to improve internal validity. First, I designed the study to use data source triangulation, which “looks to see if the case remains the same at other times, in other spaces, or as persons interact differently” (Stake, 1995, p. 112). I collected multiple sources of data in order to triangulate findings. Second, I employed investigator triangulation, which ▇▇▇▇▇ defined as having “other researchers take a look at the same scene or phenomenon” (p. 113) by asking fellow graduate students to code portions of my transcripts. Next, I used member checks on the classroom observations, interviews, and focus groups. I shared selections of my field note...
Validity and Reliability. The researcher determined from the Panorama Education Well-Being User’s Guide that current validity data is ongoing, but a final report will be published in 2021 with updated results further supporting convergent/discriminant validity of each scale. The Survey Checklist (Manifesto, 2018) evidencing how the survey was produced to include best practices in the science of survey design (▇▇▇▇▇▇▇ & ▇▇▇▇▇▇ ▇▇., 2018) and was available on the Panorama Education website. The User Guide states, “After designing an initial survey, we pilot-tested it in 100 schools, collecting initial data from over 25,000 students. Using these results and feedback from our pilot partners, we refined the survey to maximize its psychometric qualities and practical utility” (Education, P. ,2021, p.
Validity and Reliability. Validity is very important in conducting effective research because it determines the value of this research. In a qualitative research, the subjectivity of respondents usually lowers validity to some degree because of the limitation of scope of people’s knowledge. However, the validity of research can be addressed with the increase of depth of data collected, the subjects interviewed and their connection with the research themes and the objectivity of the researcher (▇▇▇▇▇, ▇▇▇▇▇▇ & ▇▇▇▇▇▇▇▇ 2007, p.133). In this research, I succeed in interviewing the management members of UiN and they are very much know this cooperation. A good research should have a very good quality of reliability. Reliability refers to the extent to which the data collected reflect the “truth”. The researcher will influence the reliability strongly because the objectivity is very hard to control during all the process of research. Researchers develop their own ideas in the process of doing research, with time pass, they would unavoidably put their own ideas or opinions into the research, which will destroy the reliability of the thesis. So, having known this, I attempt not to put too much my personal ideas into the interview and make sure the data are all from the respondents. For example, I seldom express my approval or disapproval towards respondents’ answer, and I will also try not to interrupt them or use two much facial expression.
Validity and Reliability. 65 Data Analysis ....................................................................................................... 68
Validity and Reliability. The empirical research conducted included interviews, questionnaires as well as a case study on an actual property development project. This was done to establish and add to the reliability and validity of the study.
Validity and Reliability. Reliability and validity are major components of research that enhance the credibility of a study. The BMMRS and Bully Survey instruments were selected because they are both reliable and valid research instruments that have been widely used. Selection of the instruments provided reliability and validity strategies to increase the likelihood that the research would provide a strong contribution to the field of study through reliable findings. Clarifying researcher bias was used as a validity strategy to ensure readers understand the researcher’s position and assumptions from the outset of the study. By keeping in mind her passion for the topic, the researcher was very careful not to project bias. The researcher also incorporated member checking when conducting the study to promote the credibility of the research findings.
Validity and Reliability. While there are many arguments about whether validity and reliability mean different things in quantitative and qualitative projects, there is agreement that these are important issues in both paradigms (▇. ▇▇▇▇▇ et al., 2011; ▇▇▇▇ & ▇▇▇▇▇▇▇, 2005). Validity concerns the extent to which a study explores what it claims to, and therefore, the extent to which it is credible (Perakyla, 2004). Reliability concerns whether the claims made through data interpretation are grounded in the data (▇▇▇▇▇ & ▇▇▇▇▇▇▇, 2003). These issues are closely related, and as ▇▇▇▇▇ et al. have suggested, there is “some blurring of the edges between validity and reliability in the literature” (2011, p. 204). In this study reliability and validity are addressed in several ways. The methods used are consistent with the ontological, epistemological and axiological perspectives taken in this study. For example, as outlined in section 3.2.1, knowledge is understood to be socially constructed for the purposes of this study, therefore research tools were used that collect and generate socially constructed data. One potential limitation of this study is the extent to which people who do not participate in PES might understand what PES is and how PES practices work enough to discuss it. This problem was addressed through the inclusion of accompanied visits to PES activities and through the provision of concrete examples of PES activities for participants to engage with in discussions. In these ways, therefore, the research process can be said to be valid because it examines the phenomena it claims to. One limitation regarding the reliability of the data collected was the potential positive bias in participants responses to the accompanied visits involved in this study. Since I organised the visits, participants may have tried to be more positive in their feedback than they might have been otherwise. Furthermore, by the time the visits were conducted I had spent between two and six months with the participants involved and was clearly seen as an ‘insider’ to PES, as well as someone they had befriended, and may not have wanted to upset. This potential reliability problem was addressed through critical reflection on their feedback and the comparison of their visit feedback with the recordings, field notes and photographs from the visits, as well as by comparison with the other data collected for this study. The reliability of this study was therefore developed through the processes of triangulat...
Validity and Reliability. 39 Plan for Data Collection ............................................................................................ 40 Plan for Data Analysis ............................................................................................... 41 Ethical Issues ............................................................................................................. 42 Summary.................................................................................................................... 43 CHAPTER 4: FINDINGS ..................................................................................................... 46 Participants’ Demographics....................................................................................... 47 Summer Success Program (Jump$tart and Wings) ....................................... 48