The purpose of this study was to assess for posttraumatic growth (PTG) in individuals with rheumatoid arthritis (RA). This study also sought to determine the relationship between PTG and mindfulness for people with RA. RA is a degenerative disease characterized by chronic joint pain and is associated with various kinds of psychological distress, including depression, anxiety, and low self-esteem. More recently, researchers have looked to ways in which living with RA may also promote personal growth. One of the most commonly researched conceptualizations of growth following hardship is posttraumatic growth (PTG). Some studies suggest that PTG may be positively related to mindfulness, such that people who are more mindful also experience more growth following adversity. The present study examines the extent to which people report experiencing growth as a result of living with RA, as well as participants’ levels of trait or dispositional mindfulness. Descriptive data are presented for all gathered data and the relationship between PTG and mindfulness was examined. Results of this study suggested that people with RA report moderate levels of PTG as a result of navigating this difficult disease. Findings also indicated no significant relationship between PTG and trait mindfulness for this sample of people with RA. Both PTG and trait mindfulness were significantly related to participants’ pain severity, however. The results of this study add to a small body of literature suggesting that people with RA do experience PTG. Understanding the correlates of PTG following RA will help physicians and psychologists maximize opportunities for positive adjustment above and beyond premorbid levels of functioning for those living with RA. This study’s findings also point to the importance of continuing to investigate the relationship between PTG and mindfulness.

This study investigates the impact of online versus pen and paper homework on college students' learning and performance, and explores their experiences in each modality. After familiarizing students with two different homework modalities, students' decision to work in the online versus the traditional environment was utilized as the student preference indicator. Students' gender and computer comfort levels were also recorded. Although differences were found on the computer comfort levels of male and female students, there were no significant differences on learning outcomes. The findings suggest that students can learn equally well in either modality, regardless of their preference, gender or computer comfort level. In the attempt to better understand their experiences, students were asked to describe and compare their learning in both modalities. According to the students, instant feedback was the most valuable feature. They enjoyed working with computers; it helped them stay interested and motivated. They mentioned, however, that they learn better writing down on paper rather than typing on a computer keyboard.

Item response theory (IRT) modeling is a statistical technique that is being widely applied in the field of educational and psychological testing. The usefulness of IRT models, however, is dependent on the extent to which they effectively reflect the data, and it is necessary that model data fit be evaluated before model application by accumulating a wide variety of evidence that supports the proposed uses of the model with a particular set of data. This thesis addressed issues in the collection of two major sources of fit evidence to support IRT model application: evidence based on model data congruence, and evidence based on intended uses of the model and practical consequences. Specifically, the study (a) proposed a new goodness-of-fit procedure, examined its performance using fitting and misfitting data, and compared its behavior with that of the commonly used goodness-of-fit procedures, and (b) investigated through simulations the consequences of model misfit on two of the major IRT applications: equating and computer adaptive testing. In all simulation studies, 3PLM was assumed to be the true IRT model, while 1PLM and 2PLM were treated as misfitting models. The study found that the new proposed goodness-of-fit statistic correlated consistently higher than the commonly used fit statistics with the true size of misfit, making it a useful index to estimate the degree of misfit, which is often of interest but unknown in practice. A major issue with the new statistic is its inappropriately defined null distribution and critical values, and as a result the new statistical test appeared to be less powerful, but less susceptible to type I error rate either. In examining the consequences of model data misfit, the study showed that although theoretically 2PLM could not provide a perfect fit to 3PLM data, there was minimum consequence if 2PLM was used to equate 3PLM data and if number correct scores were to be reported. This, however, was not true in CAT given the significant bias 2PLM produced. The study further emphasized the importance of fit evaluation through both goodness-of-fit statistical tests and examining practical consequences of misfit.

More and more testing programs are transferring from traditional paper and pencil to computer-based administrations. Common practice in computer-based testing is that test items are utilized repeatedly in a short time period to support large volumes of examinees, which makes disclosed items a concern to the validity and fairness of test scores. Most current research is focused on controlling item exposure rates, which minimizes the probability that some items are over used, but there is no common understanding about issues such as how long an item pool should be used, what the pool size should be, and what exposure rates are acceptable. A different approach to addressing overexposure of test items is to focus on generation and investigation of item statistics that reveal whether test items are known to examinees prior to their seeing the tests. A method was proposed in this study to detect disclosed items by monitoring the moving averages of some common item statistics. Three simulation studies were conducted to investigate and evaluate the usefulness of the method. The statistics investigated included classical item difficulty, IRT-based item raw residuals, and three kinds of IRT-based standardized item residuals. The detection statistic used in study 1 was the classical item difficulty statistic. Study 2 investigated classical item difficulty, IRT-based item residuals and the best known of the IRT-based standardized residuals. Study 3 investigated three different types of standardizations of residuals. Other variables in the simulations included window sizes, item characteristics, ability distributions, and the extent of item disclosure. Empirical type I error and power of the method were computed for different situations. The results showed that, with reasonable window sizes (about 200 examinees), the IRT-based statistics under a wide variety of conditions produced the most promising results and seem ready for immediate implementation. Difficult and discriminating items were the easiest to spot when they had been exposed and it is the most discriminating items that contribute most to proficiency estimation with multi-parameter IRT models. Therefore, early detection of these items is especially important. The applicability of the approach to large scale testing programs was also addressed.

The practice of equating educational and psychological tests to create comparable and interchangeable scores is increasingly becoming appealing to most testing and credentialing agencies. However, the Malawi National Examinations Board (MANEB) and many other testing organizations in Africa and Europe do not conduct equating and the consequences of not equating tests have not been clearly documented. Furthermore, there are no proper equating designs for some agencies to employ because they administer tests annually to different examinee' populations and they disclose all items after each administration. Therefore, the purposes of this study were to: (1) determine whether it was necessary to equate MANEB tests; (2) investigate consequences of not equating educational tests; and (3) explore the possibility of using an external anchor test that is administered separately from the target tests to equate scores. The study used 2003, 2004, and 2005 Primary School Leaving Certificate (PSLCE) Mathematics scores for two randomly equivalent groups of eighth grade examinees drawn from 12 primary schools in the Zomba district in Malawi. In the first administration, group A took the 2004 test while group B took the 2003 form. In the second administration both groups took an external anchor test and five weeks later, they both took the 2005 test. Data were analyzed using identity and log-linear methods, t-tests, decision consistency analyses, classification consistency analyses, and by computing reduction in uncertainty, and the root mean square difference indices. Both linear and post-smoothed equipercentile methods were used to equate test scores. The study revealed that: (1) score distributions and test difficulties were dissimilar across test forms signifying that equating is necessary; (2) classification of students into grade categories across forms were different before equating, but similar after equating; and (3) the external anchor test design performed in the same way as the random groups design. The results suggest that MANEB should equate tests scores to improve consistency of decisions and to match their distributions and difficulty levels across forms. Given the current policy of exam discloser, the use of an external anchor test that is administered separately from the operational form to equate score is recommended.

The appeal of computer adaptive testing (CAT) is growing in the licensure, credentialing, and educational fields. A major promise of CAT is the more efficient measurement of an examinee's ability. However, for CAT to be successful, a large calibrated item bank is essential. As item selection depends on the proper calibration of items, and accurate estimation of the item information functions, obtaining accurate and stable estimates of item parameters is paramount. However, concerns of item exposure and test security require item parameter estimation with much smaller samples than is recommended. Therefore, the development of methods for small sample estimation is essential. The purpose of this study was to investigate a technique to improve small sample estimation of item parameters, as well as recovery of item information functions by using auxiliary information about item in the estimation process. A simulation study was conducted to examine the improvements in both item parameter and item information recovery. Several different conditions were simulated, including sample size, test length, and quality of collateral information. The collateral information was used to set prior distributions on the item parameters. Several prior distributions were placed on both the a - and b-parameters and were compared to each other as well as to the default options in BILOG. The results indicate that with some relatively good collateral information, nontrivial gains in both item parameter and item information recovery can be made. The current literature in automatic item generation indicates that such information is available for the prediction of item difficulty. The largest improvements were made in the bias of both the a-parameters and the information functions. The implications are that more accurate item selection can occur, leading to more accurate estimates of examinee ability.

Abstract not available

As demanded by the No Child Left Behind (NCLB) legislation, state-mandated testing has increased dramatically, and almost all of these tests report examinee's performance in terms of several ordered proficiency categories. Like licensure exams, these assessments often have high-stakes consequences, such as graduation requirements and school accountability. It goes without saying that we want these tests to be of high quality, and the quality of these test instruments can be assessed, in part, through the decision accuracy (DA) and decision consistency (DC) indices. With the popularization of IRT, an increasing number of tests are adopting IRT for test development, test score equating and all other data analyses, which naturally calls for approaches to evaluating DA and DC in the framework of IRT. However, it is still common to observe the practice of carrying out all data analyses in IRT while reporting DA and DC indices derived in the framework of CTT. This situation testifies to the necessity to the exploration of possibilities to quantify DA and DC under IRT. The current project addressed several possible methods for estimating DA and DC in the framework of IRT with the specific focus on tests involving both dichotomous and polytomous items. It consisted of several simulation studies in which the all IRT methods introduced were valuated with simulated data, and all methods introduced were also be applied in a real data context to demonstrate their application in practice. Overall, the results from this study provided evidence that would support the use of the 3 IRT methods introduced in this project in estimating DA and DC indices in most of the simulated situations, and in most of the cases the 3 IRT methods produced results that were close to the "true" DA and DC values, and consistent results to (sometimes even better results than) those from the commonly used L&L method. It seems the IRT methods showed more robustness on the distribution shapes than on the test length. Their implications to educational measurement and some directions for future studies in this area were also discussed.

Using community college students enrolled in a competency-based psychology course, the investigator studied the interrelationships among three tests of cognitive/learning styles: (1) Group Embedded Figures Test; (2) Kolb Learning Style Inventory; (3) Tenore Learning Style Assessment Inventory. The relationships among these measures as they related to student characteristics were also investigated. The student characteristics included achievement (as measured by grade in the psychology course, cumulative grade point average, grade point average within subject discipline), semester hours of credit completed, ethnic origin (American or ESL), age, and sex. Results indicate that the three assessment instruments are unrelated. The measures appear to be tapping different aspects of cognitive/learning styles. In examining the relation of the various elements of the instruments to selected student variables, the investigator found low correlations. The findings of this study suggest that in the widespread practice of categorizing and labeling types of learning style, operational definitions are not uniform.

The field of New Media authoring is still evolving and is largely an inexact science. The power of New Media lies in it's capability to present information in various forms to the learner for not only the acquisition of needed information but to allow for new ways of interpreting and understanding the information. More knowledge is needed to understand how best to combine different forms of media to enhance learning especially in domains of knowledge that are ill-defined and ill-structured. This investigation explores and examines how to best combine visual and textual information in the context of science education to promote conceptual change. Cognitive Flexibility Theory (CFT) will serve as the basis for this study. Tornado formation was chosen as the subject matter. The main principles of CFT are that learning activities must provide multiple representations of content with instructional materials should avoid oversimplifying the content domain and support context-dependent knowledge. Also, instruction should be case-based and emphasize knowledge construction, not transmission of information and knowledge sources should be highly interconnected rather than compartmentalized. The main hypothesis is that employment of the principles of CFT in a hypermedia learning environment that directs browsing of the dynamics of tornado formation will improve learning and transfer of complex knowledge of the subject matter and initiate conceptual change. The hypothesis was tested by having the subjects first complete a pre-test in which they displayed their current understanding of how a tornado forms. They are then directed to enter the hypermedia site via an entry point based on their apparent misconception of the subject matter as seen in the pre-test. The hypermedia treatment guides the student through both textual and graphical information about the formation of tornadoes in accordance with the principles of CFT. The subjects are allowed to change their conceptual understanding at points along the way. They are allowed to see case studies, definitions and an animation. Soon after the treatment is finished, they complete a post-test which is identical to the pre-test. The change in the test responses represents a conceptual change. The results showed a profound increase towards a conceptual change representing a shift from the subject's original misconception to a more correct understanding of the phenomenon. Specifically, when the counter-examples were in their initial positions so that they would counteract the subject's misconception, the rate of positive conceptual change was high. Also, when the examples were reversed in an effort to see if they could bring about a continued high rate of change, they were indeed able to produce this rate of change. Presumably, this was due to a heightened contrast between the misconception and the correct concept as the subject was lead deeper into their misconception before seeing the correct concept. In both cases, the number of subjects displaying a positive conceptual change was in excess of 60%.