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 of Health & Welfare and Natural Sciences, Mathematics & Statistics. Educational technology used for emergency remote teaching are most often synchronous collaborative tools, used in combination with text-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 ¼ 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.

The COVID-19 pandemic had a strong impact on higher education in 2020. Worldwide, universities developed and implemented online courses for distance learning within a relatively short amount of time. The current study investigated how ready students were for this exceptional situation and how their readiness for digital learning influenced their socio-emotional experiences. N = 1,826 students from across all institutional faculties of a German comprehensive university took part in the online survey immediately before the semester began. Results indicate that, on average, higher education students 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 technological equipment, prior experiences with e-learning, and skills for digital learning). Finally, students’ socio-emotional experiences, that is, their perceived stress, their work-life-balance as well as social and emotional loneliness significantly differed due to their cluster membership. Hence, the study points to the need to support higher education students in successfully coping with the challenges of emergency remote studying.

Two studies were conducted to further examine the unskilled-and-unaware effect and to test whether lowperforming students are indeed unaware of their (expected) lower metacognitive monitoring abilities. Postdicted judgments of performance and second-order judgments (SOJs) were solicited to test students' metacognitive awareness. Given that global and local judgments tend to differ (the confidence-frequency effect), we investigated whether students' (un)awareness pertains to both types of judgments. A first study focusing on global judgments was conducted in a regular exam setting with 196 undergraduate education students. A second study with 115 undergraduate education students examined both global and local judgments. Local judgments were analyzed on an average level and according to different signal detection theory categories (hits, correct rejections, misses, and false alarms). In both studies, students were grouped in four performance quartiles. The results showed that lowperforming students highly overestimated their performance (they were functionally overconfident). However, their SOJs indicated that they were less confident in their judgments than the other students, and thus seemed to be aware of their low ability to estimate their own performance (they were not subjectively overconfident). This was observed for global as well as for averaged local SOJs. Moreover, an analysis of the local judgments revealed that students' SOJs varied depending not only on whether their judgments were accurate but also on whether or not they thought they knew the answer to an item. In sum, SOJs provide valuable information about students' metacognitive awareness.

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.