Due to the Covid-19 pandemic that spread globally in 2020, higher education courses were subsequently offered in fully remote, online formats. A plethora of primary studies began investigating a range of topics exploring teaching and learning in higher education, particularly during the initial semester. In order to provide an overview and initial understanding of this emerging research field, a systematic mapping review was conducted that collates and describes the characteristics of 282 primary empirical studies. Findings reveal that research was carried out mostly descriptively and cross-sectionally, focusing predominantly on undergraduate students and their perceptions of teaching and learning during the pandemic. Studies originate from a broad range of countries, are overwhelmingly published open access, and largely focused on the fields ofHealth & WelfareandNatural Sciences, Mathematics & Statistics. Educational technology used for emergency remote teaching are most oftensynchronous collaborative tools, used in combination withtext-based tools. The findings are discussed against pre-pandemic research on educational technology use in higher education teaching and learning, and perspectives for further research are provided.

The current study investigated how ready higher education students were for emergency remote teaching due to the COVID-19 pandemic and how this influenced their socio-emotional perceptions. Results of N = 1,826 higher education students indicate that they seem to be ready for digital learning. A k-means cluster analysis revealed two groups of students that significantly differed with respect to their readiness for digital learning (in terms of technology equipment availability, prior experiences with e-learning, and skills for digital learning). Finally, students’ socio-emotional perceptions, that is, stress-related emotions (worries, tension, joy, and overload) as well as social and emotional loneliness significantly differed due to cluster membership. Hence, the study points a need for support of higher education students in successfully coping with the challenges of emergency remote studying.

Extensive research has been conducted to understand how accurately students monitor their studying and performance via metacognitive judgments. Moreover, the bases of students’ metacognitive judgments are of interest. While previous results are quite consistent regarding the importance of performance for the accuracy of metacognitive judgments, results regarding motivational and personality variables are rather heterogeneous. This paper reports on two studies that simultaneously examined the predictive power of several performance, motivational, and personality variables on metacognitive judgments. The studies investigated a set of judgments (local and global postdictions in Study 1 and global pre- and postdictions in Study 2) and accuracy scores (bias, sensitivity, and specificity) in two different settings. Individual differences in judgments and judgment accuracy were studied via hierarchical regression analyses. Study 1 with N = 245 undergraduate students identified performance and domain-specific self-concept as relevant predictors for judgments after test taking. This was consistently found for local and global judgments. Study 2 with N = 138 undergraduate students hence focused on domain-specific self-concept and extended results to predictions. Study 2 replicated results for global postdictions but not predictions. Specifically, before task processing, students’ judgments relied mostly on domain-specific self-concept but not on test performance itself. The studies indicate that different judgments and measures of judgment accuracy are needed to obtain comprehensive insights into individual differences in metacognitive monitoring.

Given that video conferencing serves as a crucial means for remote teaching, the current study investigated higher education students’ (non)use of webcams and engagement in synchronous online courses. Three phases were studied: (1) A state of engagement; (2) antecedents that influence it; and (3) consequences of engagement. The cross-sectional online survey encompassed 3,610 students. Results indicated that visual and verbal engagement were only slightly related to each other. Structural equation modelling revealed different direct and indirect influences on either visual or verbal engagement in synchronous online higher education courses. Due to the novelty of the research scope, results of this study provide a foundation for further investigation.