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Maintenance of Vertical Scales Under Conditions of Item Parameter Drift and Rasch Model-data MisfitO'Neil, Timothy Paul 01 May 2010 (has links)
With scant research to draw upon with respect to the maintenance of vertical scales over time, decisions around the creation and performance of vertical scales over time necessarily suffers due to the lack of information. Undetected item parameter drift (IPD) presents one of the greatest threats to scale maintenance within an item response theory (IRT) framework. There is also still an outstanding question as to the utility of the Rasch model as an underlying viable framework for establishing and maintaining vertical scales. Even so, this model is currently used for scaling many state assessment systems. Most criticisms of the Rasch model in this context have not involved simulation. And most have not acknowledged conditions in which the model may function sufficiently to justify its use in vertical scaling. To address these questions, vertical scales were created from real data using the Rasch and 3PL models. Ability estimates were then generated to simulate a second (Time 2) administration. These simulated data were placed onto the base vertical scales using a horizontal vertical scaling approach and a mean-mean transformation. To examine the effects of IPD on vertical scale maintenance, several conditions of IPD were simulated to occur within each set of linking items. In order to evaluate the viability of using the Rasch model within a vertical scaling context, data were generated and calibrated at Time 2 within each model (Rasch and 3PL) as well as across each model (Rasch data generataion/3PL calibration, and vice versa). Results pertaining the first question of the effect IPD has on vertical scale maintenance demonstrate that IPD has an effect directly related to percentage of drifting linking items, the magnitude of IPD exhibited, and the direction. With respect to the viability of using the Rasch model within a vertical scaling context, results suggest that the Rasch model is perfectly viable within a vertical scaling context in which the model is appropriate for the data. It is also clearly evident that where data involve varying discrimination and guessing, use of the Rasch model is inappropriate.
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Item Parameter Drift as an Indication of Differential Opportunity to Learn: An Exploration of item Flagging Methods & Accurate Classification of ExamineesSukin, Tia M. 01 September 2010 (has links)
The presence of outlying anchor items is an issue faced by many testing agencies. The decision to retain or remove an item is a difficult one, especially when the content representation of the anchor set becomes questionable by item removal decisions. Additionally, the reason for the aberrancy is not always clear, and if the performance of the item has changed due to improvements in instruction, then removing the anchor item may not be appropriate and might produce misleading conclusions about the proficiency of the examinees. This study is conducted in two parts consisting of both a simulation and empirical data analysis. In these studies, the effect on examinee classification was investigated when the decision was made to remove or retain aberrant anchor items. Three methods of detection were explored; (1) delta plot, (2) IRT b-parameter plots, and (3) the RPU method. In the simulation study, degree of aberrancy was manipulated as well as the ability distribution of examinees and five aberrant item schemes were employed. In the empirical data analysis, archived statewide science achievement data that was suspected to possess differential opportunity to learn between administrations was re-analyzed using the various item parameter drift detection methods. The results for both the simulation and empirical data study provide support for eliminating the use of flagged items for linking assessments when a matrix-sampling design is used and a large number of items are used within that anchor. While neither the delta nor the IRT b-parameter plot methods produced results that would overwhelmingly support their use, it is recommended that both methods be employed in practice until further research is conducted for alternative methods, such as the RPU method since classification accuracy increases when such methods are employed and items are removed and most often, growth is not misrepresented by doing so.
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Assessment of Item Parameter Drift of Known Items in a University Placement ExamJanuary 2012 (has links)
abstract: ABSTRACT This study investigated the possibility of item parameter drift (IPD) in a calculus placement examination administered to approximately 3,000 students at a large university in the United States. A single form of the exam was administered continuously for a period of two years, possibly allowing later examinees to have prior knowledge of specific items on the exam. An analysis of IPD was conducted to explore evidence of possible item exposure. Two assumptions concerning items exposure were made: 1) item recall and item exposure are positively correlated, and 2) item exposure results in the items becoming easier over time. Special consideration was given to two contextual item characteristics: 1) item location within the test, specifically items at the beginning and end of the exam, and 2) the use of an associated diagram. The hypotheses stated that these item characteristics would make the items easier to recall and, therefore, more likely to be exposed, resulting in item drift. BILOG-MG 3 was used to calibrate the items and assess for IPD. No evidence was found to support the hypotheses that the items located at the beginning of the test or with an associated diagram drifted as a result of item exposure. Three items among the last ten on the exam drifted significantly and became easier, consistent with item exposure. However, in this study, the possible effects of item exposure could not be separated from the effects of other potential factors such as speededness, curriculum changes, better test preparation on the part of subsequent examinees, or guessing. / Dissertation/Thesis / M.A. Educational Psychology 2012
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