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Online courses are particularly attractive in continuing education because they offer a high degree of autonomy and flexibility, although this requires learners to take greater responsibility for self-regulating their learning. That can be challenging for adult learners as they need to handle other obligations in addition to learning. Thus, self-regulated learning (SRL) support might be needed. In the present study, we aimed to investigate how the specific SRL challenges that adult learners face in online courses can be supported adaptively. Main challenges for adult learners consist in managing learning resources (e.g., time, attention, learning environment). To address these challenges, we developed an adaptive support intervention comprising several features. To assess the effects of the adaptive support on the self-reported SRL strategy application of adult learners, we analysed data from five iterations of a continuing education online course comparing iterations with adaptive support (with a total of N = 36 participants) to iterations without (with a total of N = 35 participants). Results indicate that the adaptive support significantly improved environmental structuring but did not significantly affect other SRL strategies. Further analyses revealed that learners who did not use the support deteriorated in managing their learning time and in setting specific learning goals during the course.

In recent years, interest in the usage of computer-based methods in archaeology, especially regarding field documentation, has grown significantly. In 2021, Göttlich et al. presented a new large-scale three-dimensional (3D) capture method for the documentation of pottery using structure from motion. This method, however, was only tested on a very small sample set and never truly conducted in a large-scale documentation surrounding. Consequently, we decided to test this workflow on a large-scale basis during three field campaigns (March 2022, November 2022, and March 2023) in Lebanon, documenting more than 4,000 sherds in total. In this article, I will present the results and observations of these campaigns, critically discuss the workflow involved (documentation and processing), and propose a refined workflow for this methodology. This article focuses solely on the relevant documentation and 3D processing.

Artificial intelligence (AI) can enhance teachers' capabilities by sharing control over different parts of learning activities. This is especially true for complex learning activities, such as dynamic learning transitions where students move between individual and collaborative learning in un-planned ways, as the need arises. Yet, few initiatives have emerged considering how shared responsibility between teachers and AI can support learning and how teachers' voices might be included to inform design decisions. The goal of our article is twofold. First, we describe a secondary analysis of our co-design process comprising six design methods to understand how teachers conceptualise sharing control with an AI co-orchestration tool, called "Pair-Up." We worked with 76 middle school math teachers, each taking part in one to three methods, to create a co-orchestration tool that supports dynamic combinations of individual and collaborative learning using two AI-based tutoring systems. We leveraged qualitative content analysis to examine teachers' views about sharing control with "Pair-Up," and we describe high-level insights about the human-AI interaction, including control, trust, responsibility, efficiency, and accuracy. Secondly, we use our results as an example showcasing how human-centred learning analytics can be applied to the design of human-AI technologies and share reflections for human-AI technology designers regarding the methods that might be fruitful to elicit teacher feedback and ideas. Our findings illustrate the design of a novel co-orchestration tool to facilitate the transitions between individual and collaborative learning and highlight considerations and reflections for designers of similar systems.

Abstract Background Mental health problems, such as depression, have a high prevalence in young people. However, the majority of youths suffering from depression do not seek professional help. This study aimed to compare help-seeking behavior, intentions and perceived barriers between youthswith different levels of depressive symptoms. Methods This cross-sectional study is part of a large-scale, multi-center project. Participants were n = 9509 youths who were recruited in German schools and completed a baseline screening questionnaire. Based on their depressive symptoms, youths were allocated to the following three subgroups: (a) without depressive symptoms, (b) with subclinical symptoms, (c) with clinical symptoms (measured by PHQ-A). Quantitative analyses compared previous help-seeking behavior, help-seeking intentions and perceived barriers (Barriers questionnaire) between these subgroups. An additional exploratory qualitative content analysis examined text answers on other perceived barriers to help-seeking. Results Participants were mostly female (n = 5575, 58.6%) and 12 to 24 years old (M = 15.09, SD 2.37). Participants with different levels of depressive symptoms differed significantly in help-seeking behavior, intentions and perceived barriers. Specifically, participants with clinical depressive symptoms reported more previous help-seeking, but lower intentions to seek help compared to participants without symptoms (all p

This paper presents a fine-grained process analysis of 22 students in a classroom-based learning setting. The students engaged (and failed) in problem-solving attempts prior to instruction (i.e., the Productive-Failure approach). We used the HeuristicsMiner algorithm to analyze the data of a quasi-experimental study. The applied algorithm allowed us to investigate temporally structured think-aloud data, to outline productive and unproductive problem-solving strategies. Our analyses and findings demonstrated that HeuristicsMiner enables researchers to effectively mine problem-solving processes and sequences, even for smaller sample sizes, which cannot be done with traditional coding-and-counting strategies. The limitations of the algorithm, as well as further implications for educational research and practice, are also discussed.

The worst performance rule (WPR) describes the phenomenon that individuals' slowest responses in a task are often more predictive of their intelligence than their fastest or average responses. To explain this phenomenon, it was previously suggested that occasional lapses of attention during task completion might be associated with particularly slow reaction times. Because less intelligent individuals should experience lapses of attention more frequently, reaction time distribution should be more heavily skewed for them than for more intelligent people. Consequently, the correlation between intelligence and reaction times should increase from the lowest to the highest quantile of the response time distribution. This attentional lapses account has some intuitive appeal, but has not yet been tested empirically. Using a hierarchical modeling approach, we investigated whether the WPR pattern would disappear when including different behavioral, self-report, and neural measurements of attentional lapses as predictors. In a sample of N = 85, we found that attentional lapses accounted for the WPR, but effect sizes of single covariates were mostly small to very small. We replicated these results in a reanalysis of a much larger previously published data set. Our findings render empirical support to the attentional lapses account of the WPR.

Background The COVID-19 pandemic negatively affected students’ mental health, increasing pre-existing psychosocial vulnerabilities. University students worldwide have presented differences in their mental health status; however, cross-country studies comparing students’ mental health during the pandemic are lacking. Aims To investigate potential differences between university students from Brazil and those from Germany with respect to (a) depressive symptoms and alcohol and drug consumption, (b) social and emotional aspects (loneliness, self-efficacy, perceived stress, social support and resilience) and (c) attitudes towards vaccination. Method Two online cross-sectional studies were conducted with university students during the COVID-19 pandemic in Brazil (November 2021 to March 2022) and in Germany (April to May 2022). Depressive symptoms, alcohol consumption, loneliness, self-efficacy, perceived stress, social support, resilience, sociodemographic information and attitudes towards vaccination were assessed. Data were analysed using univariate and bivariate models. Results The total sample comprised N = 7911 university students, with n = 2437 from Brazil and n = 5474 from Germany. Brazilian students presented significantly more depressive symptoms and suicidal thoughts, higher levels of perceived stress, higher frequency of drug or substance consumption, and lower levels of perceived social support and resilience than German students, whereas German students presented higher levels of loneliness than Brazilian students. A more favourable opinion towards vaccinations in general was found among Brazilian students compared with German students. Conclusions In both countries, low-threshold (online) counselling targeting university students is needed. The differences between the samples could indicate country and/or cultural differences which justify further research in this area.

IntroductionElectroconvulsive therapy (ECT) is the most effective treatment for patients suffering from treatment-resistant depression but its use is often limited by the concern for cognitive side effects. This study examines the effect of ECT on autobiographical and verbal memory compared to a healthy control group and the impact of the mean stimulus dose on cognition after ECT.MethodsAutobiographical and verbal memory were assessed in depressed patients and healthy controls before the first and within one week after the last ECT treatment. Neuropsychological testing included the Autobiographical Memory Interview, the Verbal Learning and Memory Test and five tests from the Cambridge Neuropsychological Test Automated Battery. The mean charge delivered across the ECT series and the total number of sessions were examined in relationship to cognitive impairment after ECT using a multiple regression model.ResultsAutobiographical memory was significantly impaired after ECT treatment compared to healthy controls. Baseline scores were lower for depressed patients on all cognitive domains. Improvements in performance after ECT were found on tests for executive functions and working memory. Effects of the mean charge delivered on cognitive functioning after ECT were heterogeneous across cognitive domains but significant for verbal retrograde memory.ConclusionECT led to autobiographical memory impairment. The relationship between mean charge delivered and cognitive performance is heterogeneous across different cognitive domains and requires further research. Significant effects of the mean charge delivered were found without a significant difference in cognitive functioning compared to a healthy control group.

Children and youth from lower subjective socioeconomic status (SES) backgrounds are at a heightened risk of mental disorders. Online counseling is a valuable tool to reach those less likely to seek professional help, but its success across different SES backgrounds remains unclear. This study explores the association between subjective SES and online counseling outcomes. Children and youth (N = 2139) between 10 and 24 years-of-age received chat-based online counseling and reported on SES, negative feelings before and after the chat, and perceived helpfulness of the chat via an online assessment tool. The results of a latent change score model showed a significant association between SES and negative feelings before chatting, indicating that lower SES predicted more negative feelings (r = −0.26, p

Botulinum neurotoxins (BoNTs) are among the most lethal toxins known to humans, comprising seven established serotypes termed BoNT/A-G encoded in two types of gene clusters (ha and orfX) in BoNT-producing clostridia. The ha cluster encodes four non-toxic neurotoxin-associated proteins (NAPs) that assemble with BoNTs to protect and enhance their oral toxicity. However, the structure and function of the orfX-type NAPs remain largely unknown. Here, we report the crystal structures for OrfX1, OrfX2, and an OrfX1-OrfX3 complex, which are encoded in the orfX cluster of a BoNT/E1-producing Clostridium botulinum strain associated with human foodborne botulism. These structures lay the foundation for future studies on the potential roles of OrfX proteins in oral intoxication and pathogenesis of BoNTs.

Botulinum neurotoxin E (BoNT/E) is one of the major causes of human botulism and paradoxically also a promising therapeutic agent. Here we determined the co-crystal structures of the receptor-binding domain of BoNT/E (HCE) in complex with its neuronal receptor synaptic vesicle glycoprotein 2A (SV2A) and a nanobody that serves as a ganglioside surrogate. These structures reveal that the protein-protein interactions between HCE and SV2 provide the crucial location and specificity information for HCE to recognize SV2A and SV2B, but not the closely related SV2C. At the same time, HCE exploits a separated sialic acid-binding pocket to mediate recognition of an N-glycan of SV2. Structure-based mutagenesis and functional studies demonstrate that both the protein-protein and protein-glycan associations are essential for SV2A-mediated cell entry of BoNT/E and for its potent neurotoxicity. Our studies establish the structural basis to understand the receptor-specificity of BoNT/E and to engineer BoNT/E variants for new clinical applications.