[Associations between students' social background, mode of instruction and learning outcomes during the pandemic]. / Zusammenhänge zwischen sozialer Herkunft, Unterrichtsform und Learning Outcomes während der Pandemie.

The COVID-19 pandemic has led to widespread school closures, which have been associated with massive changes in teaching and learning and student learning outcomes. While initial performance studies have examined learning losses due to the school closures, there are few findings to date that provide evidence on key predictors of the development of other student outcomes (stress experience, learning gain, learning time) during the school closures. This study approaches these questions by retrospectively predicting student self-assessments in these student outcomes for the periods before and during school closures by social background (academic household, language spoken at home) and instructional design (open vs. traditional). The multilevel regression models presented are motivated by theories of educational inequality and concepts of open instruction. In addition, the hypotheses tested are based on recent survey studies on COVID-19 and school. Results calculated on the basis of data from N = 1566 upper secondary school students show higher values in the retrospectively assessed stress experience of students without German as their native language than for children with German as their native language during school closures. With regard to the retrospectively self-assessed learning gain and learning time, however, there are no correlations with social background (beyond the differences in the baseline values before COVID). With respect to the relations between open instruction and student outcomes, it appears that students from traditional instruction report statistically significant higher learning time during school closures than students in open instruction. Students in open instruction, however, do not rate their learning gain to be lower than traditionally taught students despite less learning time.

Educational inequality and COVID-19: Who takes advantage of summer schools and other remedial measures?: A latent mediation model analysis based on representative data from Austrian parents of school-aged children.

In spring 2020, the COVID-19 pandemic triggered a global crisis with far-reaching effects, not least on education. Since the beginning of the pandemic, its impact on learning losses and increasing educational inequality has been widely discussed. While empirical evidence of rising educational inequality and learning loss is steadily growing, at the same time little is known about the families who are interested in remedial measures like summer schools to bridge the negative effects of the pandemic and school closures. The present study addresses this lack of research by providing an initial examination of the empirical evidence of mechanisms underlying parental choice of remedial measures. We take a closer look on which parents are particularly attracted by remedial measures by using cross-sectional data from a parent survey (N = 3590 parents) in Austria. The findings, illustrated via a series of latent mediation models, indicate that parents' intention to use remedial measures is predicted by parents' attitudes towards the implementation of remedial measures, parents' assessment of their child's learning engagement and of the quality of distance learning during school closures. Moreover, the intention to use remedial measures is significantly influenced by the family's socioeconomic status. Supplementary Information: The online version of this article (10.1007/s35834-022-00356-4) contains supplementary material, which is available to authorized users.

[School Closures - an Ethical Challenge]. / Schulschließungen als ethische Herausforderung.

The COVID-19 pandemic has led many countries around the world to take drastic measures. Regardless of the epidemiological impact, it is undisputed that these measures have had significant negative effects on scholastic attainment, psychosocial and physical health of children and adolescents. Given their consequences, such interventions evoke the question of their ethical justifiability. This article introduces the most common ethical theories and, building on them, discusses the ethical evaluation of the COVID-19-related school closures.

[Meta-Review on findings about teaching and learning in distance education during the Corona pandemic-evidence from Germany, Austria and Switzerland]. / Was wissen wir über schulische Lehr-Lern-Prozesse im Distanzunterricht während der Corona-Pandemie? ­ Evidenz aus Deutschland, Österreich und der Schweiz.

The review provides a systematic overview of the state of quantitative research on teaching and learning characteristics during school closures due to corona. The review comprises 97 online surveys conducted between 24th of March 2020 and 11th of November 2020 and covering 255,955 cases (students, parents, teachers, school leaders etc.). The analysis and synthesis of the findings was carried out along two models, the phase model of the research process and the "integrative model on distance education". The review makes clear that central aspects of teaching and learning during corona-based school closures in Spring 2020, such as distance learning characteristics (e.g. quality dimensions), student characteristics (e.g. self-sufficiency) and characteristics of home resources for learning (e.g. parental support) have already been the object of many surveys. The school situation during the corona pandemic is therefore no longer an unexplored phenomenon. Rather, the scientific ethos of researchers in this field demands that the current state of research needs to be considered in their work. The review presented here is intended to facilitate this task by not only listing the existing surveys, but also synthesizing their central findings. In addition, the review provides a relevant information basis for decisions and action in politics, administration and school practice. At the same time, the review warns against an unreflected adoption of the findings by critically discussing the scientific quality of the surveys.

COVID-19 and schooling: evaluation, assessment and accountability in times of crises-reacting quickly to explore key issues for policy, practice and research with the school barometer.

The crisis caused by the COVID-19 virus has far-reaching effects in the field of education, as schools were closed in March 2020 in many countries around the world. In this article, we present and discuss the School Barometer, a fast survey (in terms of reaction time, time to answer and dissemination time) that was conducted in Germany, Austria and Switzerland during the early weeks of the school lockdown to assess and evaluate the current school situation caused by COVID-19. Later, the School Barometer was extended to an international survey, and some countries conducted the survey in their own languages. In Germany, Austria and Switzerland, 7116 persons participated in the German language version: 2222 parents, 2152 students, 1949 school staff, 655 school leaders, 58 school authority and 80 members of the school support system. The aim was to gather, analyse and present data in an exploratory way to inform policy, practice and further research. In this article, we present some exemplary first results and possible implications for policy, practice and research. Furthermore, we reflect on the strengths and limitations of the School Barometer and fast surveys as well as the methodological options for data collection and analysis when using a short monitoring survey approach. Specifically, we discuss the methodological challenges associated with survey data of this kind, including challenges related to hypothesis testing, the testing of causal effects and approaches to ensure reliability and validity. By doing this, we reflect on issues of assessment, evaluation and accountability in times of crisis.

Prior Specification for More Stable Bayesian Estimation of Multilevel Latent Variable Models in Small Samples: A Comparative Investigation of Two Different Approaches.

Bayesian approaches for estimating multilevel latent variable models can be beneficial in small samples. Prior distributions can be used to overcome small sample problems, for example, when priors that increase the accuracy of estimation are chosen. This article discusses two different but not mutually exclusive approaches for specifying priors. Both approaches aim at stabilizing estimators in such a way that the Mean Squared Error (MSE) of the estimator of the between-group slope will be small. In the first approach, the MSE is decreased by specifying a slightly informative prior for the group-level variance of the predictor variable, whereas in the second approach, the decrease is achieved directly by using a slightly informative prior for the slope. Mathematical and graphical inspections suggest that both approaches can be effective for reducing the MSE in small samples, thus rendering them attractive in these situations. The article also discusses how these approaches can be implemented in Mplus.