Burned-Out: Middle School Teachers After One Year of Online Remote Teaching During COVID-19.

During the height of the COVID-19 pandemic, teachers around the globe had been forced to move their teaching to full-time online, remote teaching. In this study, we aimed at understanding teacher burnout during COVID-19. We conducted a survey among 399 teachers at the peak of a prolonged physical school closure. Teachers reported experiencing more burnout during (vs. before) the COVID-19 pandemic. Contributing factors to this burnout were high family work conflict and low online teaching proficiency. Burnout was associated with lower work-related wellbeing: Lower work commitment, and higher turnover intentions. It was also associated with lower psychological wellbeing: More depressive and anxiety symptoms, and lower subjective wellbeing. Approach (but not avoid) coping strategies served as a protective factor against the burnout-turnover intentions association. We conclude with recommendations on how to mitigate teacher burnout, thereby contributing to teacher wellbeing.

Classroom discussion practices in online remote secondary school settings during COVID-19.

Academically productive talk (APT) in classrooms has long been associated with significant gains in student learning and development. Yet, due to COVID-19 related restrictions, teachers around the world were forced to adapt their teaching to online, remote settings during the pandemic. In this investigation, we studied APT in junior high school during extended online, remote teaching spells. Specifically, we focused on the extent APT was a part of online teaching practices, what characterized teachers who tended to promote APT more in online, remote teaching, and associations between APT and teacher well-being, as well as student motivation and engagement. Findings from two survey studies (Study 1: 99 teachers, and 83 students; Study 2: 399 teachers) revealed the following patterns: Students and teachers agreed that APT was used to a lesser extent in remote, online classes, and associated with more interactive instructional formats (whole classroom discussion, peer group work, and questioning), but not with frontal teaching and individual task completion. Teachers with a higher sense of teaching self-efficacy, autonomous orientations, and higher empathy tended to promote APT in online, remote teaching more. More APT was associated with greater teachers' work-related (i.e., lower burnout, more commitment to teaching, and lower turnover intentions) and psychological well-being (i.e., less depressive and anxiety symptoms, and higher subjective well-being). Finally, student experiences with APT in online, remote learning was positively associated with learning motivation and engagement. Theoretical and practical implications are discussed.

Deep neural networks detect suicide risk from textual facebook posts.

Detection of suicide risk is a highly prioritized, yet complicated task. Five decades of research have produced predictions slightly better than chance (AUCs = 0.56-0.58). In this study, Artificial Neural Network (ANN) models were constructed to predict suicide risk from everyday language of social media users. The dataset included 83,292 postings authored by 1002 authenticated Facebook users, alongside valid psychosocial information about the users. Using Deep Contextualized Word Embeddings for text representation, two models were constructed: A Single Task Model (STM), to predict suicide risk from Facebook postings directly (Facebook texts → suicide) and a Multi-Task Model (MTM), which included hierarchical, multilayered sets of theory-driven risk factors (Facebook texts → personality traits → psychosocial risks → psychiatric disorders → suicide). Compared with the STM predictions (0.621 ≤ AUC ≤ 0.629), the MTM produced significantly improved prediction accuracy (0.697 ≤ AUC ≤ 0.746), with substantially larger effect sizes (0.729 ≤ d ≤ 0.936). Subsequent content analyses suggested that predictions did not rely on explicit suicide-related themes, but on a range of text features. The findings suggest that machine learning based analyses of everyday social media activity can improve suicide risk predictions and contribute to the development of practical detection tools.

In times of war, adolescents do not fall silent: Teacher-student social network communication in wartime.

Exposure to war is associated with psychological disturbances, but ongoing communication between adolescents and teachers may contribute to adolescents' resilience. This study examined the extent and nature of teacher-student communication on Social Network Sites (SNS) during the 2014 Israel-Gaza war. Israeli adolescents (N = 208, 13-18 yrs) completed information about SNS communication. A subset of these (N = 145) completed questionnaires on social rejection and distress sharing on SNS. More than a half (56%) of the respondents communicated with teachers via SNS. The main content category was 'emotional support'. Adolescents' perceived benefits from SNS communication with teachers were associated with distress sharing. Social rejection was negatively associated with emotional support and perceived benefits from SNS communication. We conclude that SNS communication between teachers and students may provide students with easy access to human connections and emotional support, which is likely to contribute to adolescents' resilience in times of war.

Small-group, computer-mediated argumentation in middle-school classrooms: the effects of gender and different types of online teacher guidance.

BACKGROUND: Research has shown the importance of careful teacher support during collaborative group work to promote productive discourse between students (Webb, 2009). However, this research has traditionally focused on face-to-face communication. The role of online teacher guidance of small-group computer-mediated discussions has received little attention, especially in secondary school classroom settings. Researchers of computer-supported collaborative learning (CSCL), on the other hand, have traditionally focused on software-embedded features, such as scripts, to support a-synchronous peer dialogue, and less so on human guidance of synchronous group discussions. AIMS: The main aim of the present in vivo, experimental study is to examine whether online teacher guidance can improve the quality of small-group synchronous discussions, and whether different types of guidance (epistemic or interaction guidance) affect these discussions differently, when compared to an unguided condition. The second goal of this study is to explore potential differences between all-female and all-male discussion groups. SAMPLE: Eighty-two 9th graders (three classrooms) and six teachers from a rural high school in Israel. RESULTS: Whereas epistemic guidance only improved aspects of the argumentative quality of the discussion, interaction guidance only improved aspects of collaboration. Discussions of all-girls groups scored higher on aspects of collaboration and argumentative quality, compared to all-boys groups. CONCLUSIONS: The findings show that teacher guidance of synchronous, online discussions in classrooms is realizable and reasonably reaches its intended goals. Training should be focused on acquiring various guidance strategies to augment their beneficial effects. Furthermore, future research should pay more attention to potential gender differences in peer-to-peer argumentation.

Argumentation and Explanation in Conceptual Change: Indications From Protocol Analyses of Peer-to-Peer Dialog.

In this paper we attempt to identify which peer collaboration characteristics may be accountable for conceptual change through interaction. We focus on different socio-cognitive aspects of the peer dialog and relate these with learning gains on the dyadic as well as the individual level. The scientific topic that was used for this study concerns natural selection, a topic for which students' intuitive conceptions have been shown to be particularly robust. Learning tasks were designed according to the socio-cognitive conflict instructional paradigm. After receiving a short instructional intervention on natural selection, paired students were asked to collaboratively construct explanations for certain evolutionary phenomena while engaging in dialectical argumentation. Two quantitative coding schemes were developed, each with a different granularity. The first assessed discrete dialog moves that pertained to dialectical argumentation and to consensual explanation development. The second scheme characterized the dialog as a whole on a number of socio-cognitive dimensions. Results from analyses on the dyadic as well as the individual level revealed that the engagement in dialectical argumentation predicted conceptual learning gains, whereas consensual explanation development did not. These findings open up new venues for research on the mechanisms of learning in and from peer collaboration.