Contributions of Measurement and Statistical Modeling to Assessment - Report Example

Contributions of measurement and Statistical Modeling to Assessment Contributions of measurement and Statistical Modeling to Assessment The standard psychometric models that has the most value The item response model has an edge over other standard psychometric models such as generalization theory and classical test theory (Embretson, 1996). This is because the item response theory is flexible and highly adaptive. This model has the most values, as it can be able to capture observation made on learning activities as well knowledge gained. Item response model uses test information function and conditional standard error of measurement function, which make an assembly of test to be powerful (Lord et al., 2008). In this, a description of performance of each item is better. This is because the result of the assessment using this model does not concern with the level of difficulty of the test. Thus, it is usable to assess student in various levels of study giving accurate results. The model fit; ensure that the scale of the items of test and students are in the same level. The statistics of the items is not dependent on the persons taking the exam (Lord et al., 2008). The item response model has an application that enables computerization of tests. This option is an asset in the modern setting of learning. This is because tests can be online, aiding students who are doing online studies. In addition, it helps in reducing the time it takes to do the test and increase its precision. This method focuses on the items, which in most cases are questions that have choices in two categories of right or wrong (Lord et al., 2008). The item response theory is an improvement of classical test theory. This is because of the flexibility that it brings. It also gives room for a researcher to reduce the commission of errors and increase reliability. The assumption that it works with is that a person with a given level of intelligence will be able to select the correct answer. Thus, it provides a reliable measure of the cognitive intelligence of a student (Lord et al., 2008). How to apply the material about incorporating cognitive elements in existing measurement models as an educator. Studies reveal that the kinds of mental structure that support problem‐solving and learning in various domains relates the thinking of high achievers, novices plus low achievers” (Bransford et al., 2001). There are differentiating factors between the performers and the non- performers. The mental process of the performers is such that the information acquired is easily retrievable when needed. The gained knowledge is kept such that when need arise the brain activates the process of retrieval. To an educator, the efforts should be on ensuring that the student knows when and how to apply the knowledge that they gain. The existing models of learning are rigid thus to get better results incorporation of cognitive elements becomes necessary. The cognitive elements require an understanding of the general information about the student. This comes in handy in the relating of the content that one is teaching to what is familiar to the students. When effectively done the student are able to apply the information learned appropriately (Lord et al., 2008). The cognitive nature is such that it has a selective memory. A student remembers what he is familiar to him. Acquiring knowledge needs time and concentration, thus; it is essential to have teaching methods that are able to capture the attention of the student and sustain it. As an educator coming up with diagrammatical illustration, that help to build the picture of what I teach in the minds of the students (Lord et al., 2008). In addition, varying the activities in the class to create appeal to the learner and have them desire to learn. Giving of feedback to the student about their performance and the expected performance helps in learning. The feedback has to be in such a way that it builds, a positive and winning attitude in the student. For example, student who gives a wrong answer to a question receives an encouragement like good attempt then teacher supplies the correct answer after immediately after that student. The memory of the student will be of the correct answer and not repressed by feelings of failure (Lord et al., 2008). Use of bayes nets as a cognitive psychometric structure in professional career Unified Model assumes that student’s performances can be categorized differently using task analysis. M2RCML suggests that the level of knowledge that a student has, manifests in student application of the knowledge gained. This approach applies when the information that we assess is data related. Bayes Nets is a more holistic approach as it concerns the knowledge a student has gained and other skills that come along with learning (Embretson, 1996). I am in favor of the Bayes Net model this is because of it holistic nature. In assessing the students, it is paramount to capture as multiple aspects that explain their proficiency. This model enables the joining of different information pieces relevant in making of inferences on the capabilities of the student. This gives information on how a student performs at all level i.e. in the classroom, outside the classes in other school activities, in a group and as an individual (Bransford, 2001). This model tries to look at how the knowledge a student has, developing of the area where a student excels. The model measures the cognitive characteristic of the student since it uses both qualitative and quantitative measure to establish intelligence. The challenge to this is how to determine what actions and behavioral observation will provide accurate information to use in the making of the inferences (Lord et al., 2008). A profession need to get a comprehensive understanding of the student level of knowledge absorption, the Bayes Net becomes an efficient model (Bransford, 2001). According to Groenen, “Bayes nets model is used as the numerical model underlying such complex assessment contexts as intelligent tutoring systems as in the example by Mislevy and Drew Gitom” (2006). This illustrates that this model is usable in complex analysis. This may pose as a limitation for use of this model as it requires one to understand how it works. However to overcome that challenge other models can be used alongside. This ensures efficiency in the outcome, that a professional receives. The weakness of all models and how to address them According to Frederick, “there has been substantial growth in the measurement arena, conventionally known as “psychometrics. The measurement models employed are complex although they have a small influence on education assessment (2008). The scholars have worked towards ensuring efficiency in the process of assessment of student’s capacity to gain knowledge. There has been achievements in terms of coming up with models that try to give accurate and consistent results. However, the models have a weakness in the outdated ideas of learning that are entails in most of the assessment model. The psychometric and assessment models are rigid and associated with repetitive test formats that put strong emphasis on expertise and ranking. Their approach is narrow and leaves a gap in the measure of capability. This weakness has led to research that probe on how best it is to assess students. In these researches, there has been a consensus for the need of simplicity, flexibility and efficiency in the assessment model. Advance technological methods can capture multiple observations to track students teaching (Lord et al., 2008). The use of cognitive elements to enhance the current models would make them yield better inferences regarding the student’s knowledge. Learning if taken as a multidimensional process in which the learner is not learning in isolation but within the context of the immediate environment. In this regard, as an educator there is interest in how a student operates as an individual and in-group context (Embretson, 1996). Further the approach to learning would Endeavour to move gradually from the known to the unknown. This will enable the student to correlate what they learn to the natural and physical world. This will significantly aid them to know the correct applicability of acquired information and assessing them would be easier (Lord, Novick & Birnbaum, 2008). Reference Bransford, J. D., (2001). National Research Council. How people learn: Brain, mind, experience, and school. Washington, DC: National Acad. Press. Embretson, Susan E. 1996. "Multicomponent Response Models." In Handbook of Modern Item Response Theory, ed. Win J. van der Linden and Ronald K. Hambleton. New York: Springer. Lord, F. M., Novick, M. R., & Birnbaum, A. (2008). Statistical theories of mental test scores. Charlotte, NC: Information Age Pub Groenen, P. F., & Andries van der Ark, L. L. (2006). Visions of 70 years of psychometrics: the past, present, and future. Statistica Neerlandica, 60(2), 135-144. doi:10.1111/j.1467- 9574.2006.00318.x Read More