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Advantages and disadvantages of reliability in research
Why is reliability important in research
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Research findings are considered reliable if they are consistent over a period of time and they accurately represent the total population under evaluation or study (McMillan, 2016; Golafshani, 2013). Moreover, the findings of a research study are considered reliable if they can be reproduced using similar methodology. In this regard, replication and consistency are the two characteristics that determine the reliability of any given research tool or test. Validity establishes if the research study actually measures what it was initially intended to measure (McMillan, 2016). In this regard, validity of a research is determined by how accurate the measurement tool is in measuring what it was intended to establish. Therefore, the quality of research is determined by its reliability and validity. The validity and reliability of any …show more content…
Test-retest entails giving the test to the same students over a period of time (Carmines & Zeller, 2009). In this case, the reliability will be established if the results from the students are consistent. Obtaining similar results on both occasions with high and positive reliability coefficient is an indicator that the data is reliable. The other criteria that I would use to determine reliability of the data is splitting the results into two halves, and then correlate the results on each half. In this care, reliability of the results would be established if the score on both halves demonstrate a high correlation. Another approach that I would use to ascertain the quality of reliability is the alternative form method, which involves subjecting another test to the same students. These tests should be redesigned to measure the same thing, to minimize the influence of the student’s memory on performance of the test (Carmines & Zeller,
The sampling procedures that can be utilized in evaluation research is vast. The selected sampling procedure is important in the consideration of external validity. External validity generalizes the findings to individuals in the study sample with characteristics that are alike (DiClemente et al., 2013). Although, not all research studies will require a sampling procedure that would deliver an external validity.
Michele Obama once stated, “If my future were determined just by my performance on a standardized test, I wouldn 't be here. I guarantee you that.” The First Lady is, in other words, to say that standardized testing was a major factor into her life’s outcome and her scores could have potentially not put her in her position of power that she is highly recognized in today’s society. Although standardized tests do play a large role in any college application, standardized testing may not count as much toward one’s college admissions or success because standardized tests are not the only factor toward college applications, these tests only benefit a specific target group of people, and standardized tests are better used for giving insight on one’s
...the data did not involve member checking thus reducing its robustness and enable to exclude researcher’s bias. Although a constant comparative method was evident in the discussion which improved the plausibility of the final findings. Themes identified were well corroborated but not declared was anytime a point of theoretical saturation Thus, the published report was found to be particularly strong in the area of believability and dependability; less strong in the area of transferability; and is weak in the area of credibility and confirmability, although, editorial limitations can be a barrier in providing a detailed account (Craig & Smyth, 2007; Ryan, Coughlan, & Cronin, 2007).
Since the U.S. Congress passed the No Child Left Behind program, standardized testing has become the norm for American schools. Under this system, each child attending a school is required to take a standardized test at specific grade points to assess their level of comprehension. Parents, scholars and all stakeholders involved take part in constant discussions over its effectiveness in evaluating students’ comprehension, teachers’ competency and the effects of the test on the education system. Though these tests were put in place to create equality, experts note that they have created more inequality in the classroom. In efforts to explore this issue further, this essay reviews two articles on standardized testing. This essay reviews the sentiments of the authors and their insight into standardized examination. The articles provide sufficient evidence to demonstrate that standardized tests are not effective at measuring a teacher’s competency because they do not take into account the school environment and its effect on the students.
Evaluating and understanding research findings is a very important skill for professionals to acquire. It is necessary to thoroughly collect data, findings, and results of the experiments to produce accurate detailed accounts of the studies.
Replicability and generalizability are important considerations when analyzing research findings. Result replicability measures the extent to which results will remain the same when a new sample is drawn, while generalizability refers to the ability to generalize the results from one study to the population (Guan, Xiang, & Keating, 2004). If results are not replicable they will not be generalizable. Replicability is important because it determines whether results are true or a fluke. Measures of replicability can be obtained using either external or internal methods. External replicability analysis requires redrawing a completely new sample and replicating the study. Internal replicability analysis involves procedures used to investigate replicability within the current study sample (Zientek & Thompson, 2007). Although only external analysis can provide definitive answers regarding result replicability, a flawed assessment of result replicability via internal analysis is still better than conjecture (Thompson, 1994).
Scholar Bill Ayers believes standardized testing in schools does not accurately measure what is necessary to be successful in life. Ayers insists that Standardized tests such as the American College Test (ACT) and the Scholastic Aptitude Test (SAT) measure specific facts and function which are among the least interesting and slightest important information that children should know. In an article titled “Testing the Right Way for Talent”, written by Hugh Price, argues the fact that standardized tests fail to capture the qualities that are necessary to be successful in the business world. Another article labeled “Implementing NCLB Assessment and Accountability Requirements in an Imperfect World” composed by Stuart Kahl, is in agreement with both Price and Ayers. According to Bill Ayers, Hugh Price and Stuart Kahl, standardized tests are uncalled excuse for a traumatic and stressful time in a child’s life.
Standardized testing is not an effective way to test the skills and abilities of today’s students. Standardized tests do not reveal what a student actually understands and learns, but instead only prove how well a student can do on a generic test. Schools have an obligation to prepare students for life, and with the power standardized tests have today, students are being cheated out of a proper, valuable education and forced to prepare and improve their test skills. Too much time, energy, and pressure to succeed are being devoted to standardized tests. Standardized testing, as it is being used presently, is a flawed way of testing the skills of today’s students.
According to Terre Blanche, Durrheim and Painter (2006), reliability is “the degree to which results are repeatable”. It can apply to the scores achieved by the study or the study as a whole. A more reliable study will yield similar results no matter how many times the test is repeated. In order to calculate the reliability for this study Split-half reliability, Cronbach’s alpha and Spearman Brown prophecy will be used.
The father of quantitative analysis, Rene Descartes, thought that in order to know and understand something, you have to measure it (Kover, 2008). Quantitative research has two main types of sampling used, probabilistic and purposive. Probabilistic sampling is when there is equal chance of anyone within the studied population to be included. Purposive sampling is used when some benchmarks are used to replace the discrepancy among errors. The primary collection of data is from tests or standardized questionnaires, structured interviews, and closed-ended observational protocols. The secondary means for data collection includes official documents. In this study, the data is analyzed to test one or more expressed hypotheses. Descriptive and inferential analyses are the two types of data analysis used and advance from descriptive to inferential. The next step in the process is data interpretation, and the goal is to give meaning to the results in regards to the hypothesis the theory was derived from. Data interpretation techniques used are generalization, theory-driven, and interpretation of theory (Gelo, Braakmann, Benetka, 2008). The discussion should bring together findings and put them into context of the framework, guiding the study (Black, Gray, Airasain, Hector, Hopkins, Nenty, Ouyang, n.d.). The discussion should include an interpretation of the results; descriptions of themes, trends, and relationships; meanings of the results, and the limitations of the study. In the conclusion, one wants to end the study by providing a synopsis and final comments. It should include a summary of findings, recommendations, and future research (Black, Gray, Airasain, Hector, Hopkins, Nenty, Ouyang, n.d.). Deductive reasoning is used in studies...
Reliability and validity are reliant on what is being measured and so they are likely to be affected, depending on context and purpose of the measurement. Taking this into consideration, the aim of this study was to develop an effective measure, with an acceptable internal reliability.
Reliability can be defined as the statistical measurement of how consistent and repetitive a research tool or instrument can measure what it is purported to do (Litwin, 1995, p. 6). Validity on the other hand is the measure of how truly or correctly the tool or instrument can measure what it is designed to do (Miller & Kirk, 1986, p.19). Reliability and validity are asymmetrical, meaning that one can be able to achieve ideal reliability with no validity but with a perfect validity comes a perfect reliability. But theoretically, one cannot be able to achieve a perfect validity as no instrument or tool can perfectly be standardized and no assessment or experiment can be perfectly controlled (Miller & Kirk, 1995, p. 21). Normally, tests on reliability are done but none are done on validity. To assess the reliability and validity of the questions that MADD want to use in their survey, several tests will be run on the questions to evaluate the different types or reliabilities and validity. To establish the validity and reliability of this survey, a pilot survey ...
It is important to note that high reliability of scores does not guarantee that those scores are a valid representation of the construct they are intended to measure. Reliability does not guarantee validity; however, it does determine how valid scores obtained from an instrument can be. The upper limit of the validity coefficient can be determined by taking the square root of the reliability
A few types of reliability include: test-retest reliability, internal consistency reliability, and interrater reliability. Test-retest reliability is the measure of whether a procedure yields the same results when originally tested and when retested at a later time. A test would not be considered reliable if the results were not stable after multiple retests. Furthermore, internal consistency reliability describes the requirement that the different sections of a test yield consistent results. For instance, if a test is administered to assess depression, each section of the test must be relevant to depression.
External validity is the establishment of the domain to which study’s findings can be analytically generalized. Reliability is the demonstration that the operations of the study, such as the data