Today the world is suffering from coronavirus (COVID-19) pandemic illness, and people all around the world stay at home due to its rapid spread. People including students gather information and government instructions through TVs, social media and others around them. Since the classes were canceled in many countries, the novel coronavirus affects students' interest in coursework. The purpose of this study was to examine the effect of TV news, social media and communication with people on interest in coursework, and mediating roles of fear of contamination, depression, and anxiety on these effects. A path analysis was carried out with the data collected from 773 college students. The results showed that interest in coursework was most strongly affected by communication with people. This was due to its direct and indirect effects. Social media and TV News did not directly affect interest in coursework, but indirectly affected. The study also found that among the three mediator variables, the mediator roles of anxiety was bigger than the others. Understanding the findings of this research has become very important to us, especially at a time when face-to-face lessons have been canceled all over the world and transitioned to online education. Specific recommendations for practitioners and limitations for future research were also provided in the study.

Routing examinees to modules based on their ability level is a very important aspect in computerized adaptive multistage testing. However, the presence of missing responses may complicate estimation of examinee ability, which may result in misrouting of individuals. Therefore, missing responses should be handled carefully. This study investigated multiple missing data methods in computerized adaptive multistage testing, including two imputation techniques, the use of full information maximum likelihood and the use of scoring missing data as incorrect. These methods were examined under the missing completely at random, missing at random, and missing not at random frameworks, as well as other testing conditions. Comparisons were made to baseline conditions where no missing data were present. The results showed that imputation and the full information maximum likelihood methods outperformed incorrect scoring methods in terms of average bias, average root mean square error, and correlation between estimated and true thetas.

This study compares two methods of defining groups for the detection of differential item functioning (DIF): (a) pairwise comparisons and (b) composite group comparisons. We aim to emphasize and empirically support the notion that the choice of pairwise versus composite group definitions in DIF is a reflection of how one defines fairness in DIF studies. In this study, a simulation was conducted based on data from a 60-item ACT Mathematics test (ACT; Hanson & Béguin). The unsigned area measure method (Raju) was used as the DIF detection method. An application to operational data was also completed in the study, as well as a comparison of observed Type I error rates and false discovery rates across the two methods of defining groups. Results indicate that the amount of flagged DIF or interpretations about DIF in all conditions were not the same across the two methods, and there may be some benefits to using composite group approaches. The results are discussed in connection to differing definitions of fairness. Recommendations for practice are made.

ObjectiveThe purpose of this study was to investigate the impact of the COVID-19 pandemic on the quality of life of families of children with disabilities and the mediating roles of perceived social support, perceived parental self-efficacy, psychological health, psychological resilience, and perceived family burden on this relationship.BackgroundChildren with disabilities and their families are among the most affected populations from the restrictions imposed to prevent the spread of COVID-19 virus, as the special education and rehabilitation services they had been receiving were interrupted.MethodA correlational survey design was used to collect data from 824 parents of children with disabilities in Turkey. Path analysis was used to examine the direct and indirect effects of COVID-19 on family quality of life.ResultsResults indicated that COVID-19 had a significant total effect on family quality of life and perceived social support, parental self-efficacy and psychological resilience had a mediating role on the relationship between impact of the COVID-19 pandemic and family quality of life. Perceived social support was found to the strongest mediator of the relationship between the impact of COVID-19 and the family quality of life, while perceived family burden did not have a statistically significant association with these variables.ConclusionFamily quality of life for children with disabilities decreased as the impact of COVID-19 pandemic increased. Perceived social support, parental self-efficacy and psychological resilience had mediating roles in the relationship between the impact of the COVID-19 pandemic and family quality of life.ImplicationsCOVID-19 has resulted in disruption of special education and rehabilitation services for children with disabilities and their families. Changes in daily routines have brought up additional responsibilities to parents of children with disabilities. These additional responsibilities may adversely affect and increase the burden and stress families of children with disabilities experience. The high levels of stress in families negatively affect the welfare and quality of life and result in decreased parental attention to support their children. Findings of this study show the mediating link of perceived social support, parental self-efficacy and psychological resilience in the relationship between the impact of the COVID-19 pandemic and family quality of life. Policymakers and service providers should develop and implement specific care actions to support children with disabilities and their families during and after the pandemic.

There are many item selection methods proposed for computerized adaptive testing (CAT) applications. However, not all of them have been used in computerized multistage testing (ca-MST). This study uses some item selection methods as a routing method in ca-MST framework. These are maximum Fisher information (MFI), maximum likelihood weighted information (MLWI), maximum posterior weighted information (MPWI), Kullback-Leibler (KL), and posterior Kullback-Leibler (KLP). The main purpose of this study is to examine the performance of these methods when they are used as a routing method in ca-MST applications. These five information methods under four ca-MST panel designs and two test lengths (30 items and 60 items) were tested using the parameters of a real item bank. Results were evaluated with overall findings (mean bias, root mean square error, correlation between true and estimated thetas, and module exposure rates) and conditional findings (conditional absolute bias, standard error of measurement, and root mean square error). It was found that test length affected the outcomes much more than other study conditions. Under 30-item conditions, 1-3 designs outperformed other panel designs. Under 60-item conditions, 1-3-3 designs were better than other panel designs. Each routing method performed well under particular conditions; there was no clear best method in the studied conditions. The recommendations for routing methods in any particular condition were provided for researchers and practitioners as well as the limitations of these results.