Based on a social relations perspective on mating, the actual and assumed reciprocity of mate choices was studied in a real-life speed-dating context. A community sample involving 382 singles aged 18-54 years filled out a questionnaire for the measurement of self-perceived mate value, sociosexuality, extraversion, and shyness and participated in free speed-dating sessions. Immediately after each date, choices and assumed choices were recorded. Measures of physical attractiveness and flirting behaviour were obtained by independent observers. Results show that actual mate choices are not reciprocal although people strongly expect their choices to be reciprocated and flirting behaviour is indeed strongly reciprocal. This interesting pattern of results was explained by investigating individual and dyadic effects of flirting, self-perceived mate value and physical attractiveness on mate choices. Results have important implications for understanding mating behaviour, sex differences and the (in)accuracies of mating decisions.

Trend estimation in international comparative large-scale assessments relies on measurement invariance between countries. However, cross-national differential item functioning (DIF) has been repeatedly documented. We ran a simulation study using national item parameters, which required trends to be computed separately for each country, to compare trend estimation performances to two linking methods employing international item parameters across several conditions. The trend estimates based on the national item parameters were more accurate than the trend estimates based on the international item parameters when cross-national DIF was present. Moreover, the use of fixed common item parameter calibrations led to biased trend estimates. The detection and elimination of DIF can reduce this bias but is also likely to increase the total error. 152

To depict the situation during the school closures in spring 2020 that were implemented to contain the spread of COVID-19, we conducted a self-constructed online survey on distance teaching among teachers regarding their teaching practices in this new situation, the challenges they experienced, and the prerequisites for successful distance teaching. The sample consisted of voluntarily participating German elementary (n = 857) and secondary school teachers (n = 1,590) from a sample of randomly drawn schools in four federal states in Germany. We describe the main survey findings and examine the importance of different distance teaching aspects for teacher reports of students attaining their learning objectives and students’ learning progress during distance teaching. Our results particularly highlight the necessity for students and teachers to remain in contact in all the surveyed school types. In elementary school, regular contact between teachers and parents is similarly important. The key challenges highlighted inadequate digitalization, the participation of all students, and students’ motivation. Correspondingly, adequate technical equipment for schools, teachers, and students, together with teachers’ and students’ competence to use technical devices and digital media as well as students’ motivation to participate in distance learning were found to be necessary prerequisites for successful distance teaching. We conclude that efforts should be devoted to enabling teachers and students to better communicate using digital devices, for example, expanding the digital infrastructure in combination with training teachers and students in the use of technical devices and digital media.

Mechanisms causing item nonresponses in large-scale assessments are often said to be nonignorable. Parameter estimates can be biased if nonignorable missing data mechanisms are not adequately modeled. In trend analyses, it is plausible for the missing data mechanism and the percentage of missing values to change over time. In this article, we investigated (a) the extent to which the missing data mechanism and the percentage of missing values changed over time in real large-scale assessment data, (b) how different approaches for dealing with missing data performed under such conditions, and (c) the practical implications for trend estimates. These issues are highly relevant because the conclusions hold for all kinds of group mean differences in large-scale assessments. In a reanalysis of PISA (Programme for International Student Assessment) data from 35 OECD countries, we found that missing data mechanisms and numbers of missing values varied considerably across time points, countries, and domains. In a simulation study, we generated data in which we allowed the missing data mechanism and the amount of missing data to change over time. We showed that the trend estimates were biased if differences in the missing-data mechanisms were not taken into account, in our case, when omissions were scored as wrong, when omissions were ignored, or when model-based approaches assuming a constant missing data mechanism over time were used. The results suggest that the most accurate estimates can be obtained from the application of multiple group models for nonignorable missing values when the amounts of missing data and the missing data mechanisms changed over time. In an empirical example, we furthermore showed that the large decline in PISA reading literacy in Ireland in 2009 was reduced when we estimated trends using missing data treatments that accounted for changes in missing data mechanisms.

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