Mental health condition of vocational high school students during COVID-19 pandemic in Indonesia.

This study aimed to determine the mental health condition of vocational high school students in Indonesia during the pandemic using the Rasch analysis method with the DASS-42 instrument. A total of 1381 vocational students in Indonesia participated in this study through the questionnaire. The results showed that more than 60 % of Indonesian vocational students experienced mental health problems during the COVID-19 pandemic due to social restrictions, and online learning. Furthermore, the findings of this study showed that mental health issues were mostly experienced by female students, firstborn children, and students who live in rural areas, and from middle-income backgrounds.

Validation of the Mental Health Changes Indicators Scale against Rasch measurement theory

The Mental Health Changes Indicators Scale (MHCIS) is a brief instrument designed to assess changes in an individual's mental health that occur in response to a specific life event. Although adequate psychometric properties have been demonstrated for this instrument based on classical test theory, the MHCIS has not yet been validated against Rasch measurement theory (RMT). We applied RMT to examine the psychometric properties of the MHCIS using data from 807 Chinese university students. The nominated life event in this study was the COVID-19 pandemic. Despite modest violations of unidimensionality and misfit to the Rasch model, in general, the results supported the validity of the 10-item MHCIS. We recommend further exploration of the generalizability of these results in other populations and across a range of potentially adverse life events.

Online Learning Engagement among Indonesian University Students during the COVID-19 Pandemic: A Rasch Model Analysis

The COVID-19 pandemic has caused a sudden and dramatic disruption to all levels of education. Universities all around the world have had to transition from the traditional face-to-face learning and teaching mode to the online learning mode. Indonesian universities are no exception, as online learning through the internet has become the ‘new normal’ for both educators and students. However, little is known about students’ engagement in the online mode of instruction during the COVID-19 pandemic, particularly in a developing country like Indonesia. The purpose of this non-experimental study was to investigate students’ engagement in online learning in terms of cognitive engagement, emotional engagement, and behavioral engagement. A total of 1303 public university students from Java Island, Indonesia participated in the study. Using the Rasch model analysis, the validity and reliability of the study’s instrument was established as good. The findings of the study showed that Indonesian students face difficulties adapting to full online learning. Differential item functioning (DIF) was conducted to assess students’ engagement in the online learning mode, specifically with regard to students’ demographic factors (gender and level of study), which revealed unique outcomes. The findings of this study help educators understand students’ responses to and engagement in online learning during the COVID-19 pandemic, especially in public universities in Indonesia. This study also encourages educators to reflect on their own online teaching and learning activities during the pandemic. Implications and recommendations for future research on blended learning practices are presented. © 2022 by Nova Science Publishers, Inc. All rights reserved.

Rasch Modeling and Multilevel Confirmatory Factor Analysis for the Usability of the Impact of Event Scale-Revised (IES-R) during the COVID-19 Pandemic.

BACKGROUND: Several instruments are currently used to assess Coronavirus Disease 2019 (COVID-19) -induced psychological distress, including the 22-item Impact of Event Scale-Revised (IES-R). The IES-R is a self-administered scale used to assess post-traumatic stress disorder (PTSD). The current study aimed to examine the construct validity of the IES-R, based on the Rasch model, with COVID-19-related data, as well as to test the multilevel construct validity of the IES-R within and among countries during the pandemic crisis. METHODS: A multi-country web-based cross-sectional survey was conducted utilizing the 22-item IES-R. A total of 1020 participants enrolled in our survey, of whom 999 were included in the analyses. Data were analyzed using Rasch modeling and multilevel confirmatory factor analysis (MCFA). RESULTS: The Rasch modeling results of the IES-R demonstrated that the IES-R is a satisfactory instrument with the five-point Likert scale, asserting that its 22 items are significant contributors to assessing PTSD as a unidimensional construct covered by the items of the IES-R. The MCFA confirmed that the 22-item IES-R, with its three factors, including intrusion, avoidance, and hyperarousal, demonstrates adequate construct validity at the within- and among-country levels. However, the results of the Akaike information criterion (AIC) model determined that the 16-item IES-R is better than the 22-item IES-R. CONCLUSION: The results suggested that the 22-item IES-R is a reliable screening instrument for measuring PTSD related to the COVID-19 pandemic, and can be utilized to provide timely psychological health support, when needed, based on the screening results.

Students’ perception of academic databases as recognition of learning and research during the COVID-19 pandemic

Consistent with their goal of becoming a centre for educational excellence in teaching, learning and research, the authorities of Chinese higher education introduced their academic database system as one of their e-library services. However, the existing literature exhibits inadequate empirical measurements of academic databases in all aspects of higher education throughout the world during the COVID-19 pandemic. To address this gap, this study aims to validate the technology satisfaction model (TSM) for measuring students’ satisfaction in using academic databases for their learning and research purposes. This study also analysed local and international academic databases to explore whether these databases could play a moderating role in shaping learners’ satisfaction. The data were collected through a survey of 500 respondents studying at a research university in Shanghai. The results, which were analysed by structural equation modelling and the Rasch model, showed that students’ satisfaction is determined by three valid predictors: computer self-efficacy, perceived usefulness and ease of use, and causal direct and indirect relationships among these variables in the use of local and international academic databases. Our new findings on the moderating effect of local (i.e. Chinese) and international (e.g. English) academic databases highlighted that the TSM has successfully estimated dual databases and produced insignificant, dissimilar results. This study could aid local and international educators, researchers, information science professionals and others in measuring the perception of academic databases for learning and research. This research could also serve as a guideline for researchers and psychometricians in measuring innovative learning technologies using structural equation modelling and the Rasch model. This is the unique contribution of this study, which concludes that local and international academic databases are almost equally important for postgraduate students at a research university in China. Moreover, these students are satisfied in using these academic databases to learn and do research. [ FROM AUTHOR] Copyright of Journal of Information Science is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Rasch Validation of Instrument Measuring Gen-Z Science, Technology, Engineering, and Mathematics (STEM) Application in Teaching during the Pandemic

The impact of the Covid-19 pandemic has had a far-reaching effect on higher education institutions, and individual student assessments have garnered much attention during the pandemic. This study aimed to validate Science, Technology, Engineering, and Mathematics (STEM) application instruments using the Rasch analysis employing Winsteps version 3.73. A survey was conducted with 201 respondents from two provinces in Indonesia. The students were selected by convenience sampling and answered the adopted STEM application instrument. The STEM application instruments were adapted, and these were divided into seven sub-constructs derived from STEM disciplines. Rasch Modelling was employed for data analysis using Winsteps version 3.7.3 to analyse reliability, separation, item fit statistics, unidimensionality, and rating scale calibration. Each sub-construct fulfilled a minimum of 0.65 for Cronbach alpha, item, and person reliability, and most of them had more than 1.5 person and item separation. In general, each item had a good score of the mean square, Z-tolerated standard, and point measure correlation, indicating fulfilment of the Rasch measurement model. The analysis also showed unidimensionality assumption and an excellent rating scale. This study contributed to the body of STEM knowledge by using Rasch Modelling to test the validity and reliability of STEM application instruments. © 2022 Society for Research and Knowledge Management. All rights reserved.

Technology-Enabled E-Learning Platforms in Chinese Higher Education During the Pandemic Age of COVID-19

The problem motivating this study is the fact that almost 19.70 million university students in China have been required to engage in e-learning under the government's initiative of "Classes are Suspended, yet Learning is still Ongoing" during the COVID-19 epidemic, coupled with varied responses, uneven adoption of e-learning platforms and varying degrees of satisfaction toward them. Using the online database adoption and satisfaction (ODAS) model, this study examines the determinants which impact university students' adoption of and satisfaction with e-learning platforms at this particular time in China. The ODAS model was also cross-validated using gender as a moderating variable. A purposive sampling procedure was used to survey a total of 1,136 students from six universities in five provinces or municipalities of China. The data for this survey were estimated using the Rasch model and structural equation modeling. Results exhibit that students' adoption of and satisfaction with e-learning platforms were significantly measured by their computer self-efficacy, their intention to use e-learning platforms, and their perceived ease of use and perceived usefulness of these platforms, while the relationships among these components were moderated by gender differences. This empirically-based cross-validation of the ODAS provides recommendations for future studies, including practical implications for e-learning. This current study contributes to the body of knowledge in evaluating e-learning platforms during the COVID-19 epidemic.

Government transfers, COVID-19 shock, and food insecurity: Evidence from rural households in India.

The coronavirus disease 2019 (COVID-19) pandemic has decimated the lives and livelihoods of people worldwide. The impact of COVID-19 has been especially devastating for low-income families in rural areas of India. Soon after the nationwide lockdown was announced, food insecurity became pervasive in rural areas, as many families relied on daily wage work to fund necessities. By providing cash transfers and additional foodgrains, Indian policymakers acted swiftly to reduce the financial impact on family income and consumption. This paper investigates the factors affecting rural families' participation in the cash transfer program and the effect of government cash transfers on food insecurity. Results indicate that India's government cash transfer program decreased moderate food insecurity by 2.4% and severe food insecurity by about 0.92% [EconLit Citations: O12, I31, I32, I38].

A Rasch Analysis of Perceived Stigma of Covid-19 among Nurses in Indonesia Questionnaire

This study is the first to investigate and validate the psychometric properties of the perceived stigma of the Covid-19 questionnaire among nurses in Indonesia. The respondents in the study were 2156 nurses from various regions in Indonesia (34 provinces), consisting of 613 males (28.4%) and 1543 females (71.6%). The number of nurses consisted of 300 respondents (13.9%) from the western region of Indonesia, 1825 respondents (84.6%) from the central region of Indonesia, and 31 respondents (1.4%) from the eastern region of Indonesia. The Rating Scale Model used to investigate the questionnaire's psychometric properties. The analysis results showed that the perceived stigma questionnaire met all the psychometric aspects (unidimensionality, item fit analysis, item validity, diagnostic rating scale, and reliability). Rasch Model analysis showed a value that meets all aspects measured criterion limit. Therefore, this perception stigma questionnaire can measure the perceived stigma of Covid-19 among nurses in Indonesia.

Rasch-Validated Italian Scale for Diagnosing Digital Eye Strain: The Computer Vision Syndrome Questionnaire IT©.

The use of digital devices affects eye health; this can influence the performance of workers. To assess this impact, validated patient-reported outcome questionnaires are needed. The purpose of this study was to validate the psychometric properties of the Italian version of the Computer Vision Syndrome Questionnaire (CVS-Q©) using Rasch analysis. Two hundred and forty-one Italian workers completed an ad hoc questionnaire on anamnesis and exposure to digital devices, and the Italian version of the CVS-Q©. Subsequently, a battery involving three clinical ocular surface and tear tests was performed. The reliability and validity of the scale was assessed using the Andrich Rating Scale Model, and the prevalence of computer vision syndrome (CVS) was calculated. A good fit of both items and persons to the predictions of the Rasch model was observed, with acceptable reliability, unidimensionality, and no or minimal severe differences as a function of gender or age; moreover, good test-retest repeatability, adequate values of sensitivity, reliability, and area under the curve, and adequate construct validity based on clinical tests were obtained. Workers with a questionnaire score ≥ 7 were found to present with CVS. The prevalence of CVS was 76.6%. The CVS-Q IT© is a valid and reliable scale to assess CVS in Italian workers who use digital devices.

Students’ readiness for blended learning in a leading Malaysian private higher education institution

Purpose>Teaching and learning are being transformed by digital technology, where the present generation of students, termed millennials, are more adept with the increasingly digitalised world we live in. Following this, lecturers and institutions are adapting and adopting a blended learning model across disciplines, which now commands an entire domain of research and application. However, questions remain about how ready students are for a blended learning model of instruction. The purpose of this study is to investigate students’ readiness for blended learning in a leading Malaysian private higher education institution.Design/methodology/approach>This study used a non-experimental quantitative research design. Data were gathered from a sample of 274 pre-university and undergraduate students using the blended learning readiness engagement questionnaire. Data was analysed using WINSTEPS Rasch model measurement software to determine the validity and reliability of the instrument. Descriptive statistics (mean and standard deviation) scores, (logit) value of the item and (logit) value of a person was used to examine students’ readiness for a blended learning model of instruction and specifically assess their readiness based on gender, age, ethnicity and field of study.Findings>Findings indicate that students were ready for blended learning. Further analysis indicated there were differences in students’ readiness for blended learning based on gender, age, ethnicity and field of study.Originality/value>This study provides insight into students’ readiness towards blended learning in a leading Malaysian private higher education institution, discusses implications for blended learning practices and offers recommendations for future research.

Development and Validation of the Robust - Pandemic Coping Scale (R-PCS).

The psychological consequences of epidemics/pandemics, such as the COVID-19 pandemic, include an increase in psychopathological symptoms, such as depression, anxiety, and stress, and negative emotions, such as fear. However, relatively little attention has been paid to how people cope with the pandemic. Coping is a multi-component process, helping to diminish the traumatic impact of stressful events in a variety of ways. We studied how university students coped with the first wave of the COVID-19 pandemic, by developing the Robust - Pandemic Coping Scale (R-PCS), a new scale for measuring coping strategies related to epidemics/pandemics. The scale is based on a classification of coping strategies referred to the needs of competence, relatedness, and autonomy. To create a robust scale, such that the item values would be independent of the sample used for developing it, we employed Rasch modeling. We used a sample of 2,987 Italian university students who participated in an online survey including the R-PCS and the Power to Live with Disasters Questionnaire (PLDQ), during March 2020. First, we applied a dual approach combining exploratory and confirmatory factor analyses, which supported the goodness of a 4-factor model (i.e., Despair, Adjustment, Proactivity, and Aversion) for the R-PCS, invariant across gender and age of respondents (younger or as old as 23 years, older than 23 years). We then transformed the raw scores of the R-PCS into interval logit scale scores applying the Rasch model. Second, our findings supported the discriminant validity and the criterion validity of the R-PCS, examining the correlations with the PLDQ. They also confirmed its predictive validity: the R-PCS scores were related to 2-month-later enjoyment and anger, indicating that Adjustment and Proactivity were adaptive while Despair and Aversion were maladaptive. Third, our study revealed gender and age differences: the scores were higher for Despair, Adjustment, and Proactivity for females; for Aversion for males; and for Proactivity for students older than 23 years. The study suffers from limitations related to social desirability, gender imbalance, and self-selection effects in the recruitment.

The application of WhatsApp to support online learning during the COVID-19 pandemic in Indonesia.

The current study aimed to evaluate university students' technological acceptance and connectedness to online learning with WhatsApp support. A total of 202 students from three different courses at an Indonesian private university participated in an online survey. Quantitative data analyses using Rasch modelling technique were conducted to evaluate the survey data. Findings show that most students accepted social media use to support learning and felt connected to the learning. The findings also have identified several drivers that promoted the high level of acceptance and connectedness to learning, such as students' perceived usefulness, availability of learning support, motivation, and connectedness with their friends. Implications for further research and practices of WhatsApp usage to support online learning are discussed.

Mental Health of Teachers Who Have Teleworked Due to COVID-19.

The impact of the COVID-19 pandemic on education included school closures and the implementation of virtual teaching and teleworking without the knowledge or resources needed to do so. This situation accentuated the inequality in accessing quality education and generated high rates of stress, anxiety, and general discomfort in teachers. This study aimed to explore the mental health of teachers who were forced to telework because of COVID-19, and to analyze the association with sociodemographic, teacher-related, and working conditions. The sample was 278 classroom teachers in Chile who teleworked more than 50% during the 2020 academic year. The participants were mostly women (82%) who entered the teaching profession at age 30 or younger (87%) and worked two or more unpaid overtime hours per day (67%). The dependent variable was mental health measured through the General Health Questionnaire (GHQ-12). The independent variables were sociodemographic, teacher-related, and work conditions. The internal structure of the mental health construct was evaluated using the Rasch model. Crude odds ratios (cORs) and adjusted odds ratios (aORs) were estimated using logistic regression models. A high rate of poor mental health was identified in teachers (58%). The variables associated with poor mental health were working in a private-subsidized school (aOR = 2.89; 95% CI: 1.16-7.22), working two or more unpaid overtime hours (aOR = 2.25; 95% CI: 1.11-4.59), and being absent due to sickness (aOR = 3.82; 95% CI: 1.53-9.58). These results provide evidence suggesting the need for actions to improve the working conditions of teachers who telework in order to improve their mental health, and thus have a positive impact on the entire educational community.

Vicarious Traumatization Questionnaire: Psychometric Properties Using Rasch Model and Structural Equation Modeling.

Frontline healthcare providers are exposed to indirect trauma through dealing with traumatized patients. This puts them at risk of vicarious traumatization. In response to the COVID-19 pandemic, this study seeks to establish the psychometric properties of the Malay version of the Vicarious Traumatization Questionnaire among healthcare providers. A cross-sectional study was conducted. The translated Malay version of the Vicarious Traumatization Questionnaire was completed by 352 healthcare providers in Kelantan, Malaysia. The data was entered using IBM SPSS Statistics version 26.0 (SPSS Inc., Chicago, IL, USA, 2019), and descriptive analysis was performed. The psychometric properties of the scale were assessed in two phases. The Rasch model to assess the validity and reliability was performed using Winsteps version 3.72.3. The confirmatory factor analysis using the structural equation modeling was performed using AMOS version 23.0. The Rasch analysis showed that the 38 items, in two constructs, had high item reliability and item separation at 0.97 and item separation at 5.36, respectively, while good person reliability and person separation were at 0.95 and 4.58, respectively. The correlations of all persons and items are greater than 0.20. There are no misfitting or overfitting items in the outfit MNSQ. There are four items that are challenging in answering the scale. The final model of the confirmatory factor analysis shows two constructs with 38 items demonstrating acceptable factor loadings, domain to domain correlation, and best fit (Chi-squared/degree of freedom = 4.73; Tucker-Lewis index = 0.94; comparative fit index = 0.94; and root mean square error of approximation = 0.10). Composite reliability and average variance extracted of the domains were higher than 0.7 and 0.5, respectively. The Vicarious Traumatization Questionnaire tested among healthcare providers has been shown to valid and reliable to assess vicarious traumatization.

Development and validation of Online Classroom Learning Environment Inventory (OCLEI): The case of Indonesia during the COVID-19 pandemic.

This paper reports the development and validation of a new questionnaire to assess students' perceptions of the online learning environment in Indonesia during the COVID-19 pandemic. In total, 669 participants (454 women, 215 men) from various universities were recruited online to complete a 25-item questionnaire. Item factor analysis verified a five-factor model, while multidimensional Rasch analysis showed that all items fit this model and have good reliability. The factors of Access, Interaction, Lecturer Support, Equity, and Investigation formed the valid and reliable Online Classroom Learning Environment Inventory (OCLEI). All aspects of online learning readiness were related to the five factors of the OCLEI, therefore supporting convergent validity. With these results, we concluded that the OCLEI is a novel measure that can be used in future educational research in Indonesia. Limitations and implications are noted.