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Computer programming provides a framework for interdisciplinary learning in sciences, arts and languages. However, increasing integration of programming in K–12 shows that the block-based and text-based dichotomy of programming environments does not reflect the spectrum of their affordance. Hence, educators are confronted with a fundamental hurdle of matching programming environments with learners' cognitive abilities and learning objectives. This study addresses this challenge by analyzing 111 articles evaluating the affordances of programming environments to identify both structural and theoretical models to support educators' choice of programming environments. The following dimensions of programming environments were identified: connectivity mode, interface natural language, language inheritance, age appropriateness, cost of environment, output interface, input interface, and project types. For each of these dimensions, the synthesis of the literature ranged from examining its nature and effect on learning programming to the implications of choosing an environment and the critical gaps that future studies should address. The findings offer instructors useful parameters to compare and assess programming environments' suitability and alignment with learning objectives. [ABSTRACT FROM AUTHOR]

Applications of instructional models are among the key factors in enhancing student performance. While the BOPPPS model is widely implemented, a thorough and systematic evaluation of its impact on student performance remains absent. This systematic review synthesized findings from 19 studies to explore the relationship between the BOPPPS model and student performance. Using the PRISMA, Studies were analyzed for research characteristics, focusing on the use of BOPPPS model, learning subjects, student learning formats, and research theories to better analyze student performance. Specific student-related variables analyzed included academic performance, learning performance, skill tests performance, learning and cognitive ability performance, attendance performance, classroom performance, online performance, and other aspects. The results from the majority of the included studies consistently demonstrated a positive impact of the BOPPPS model on student performance across these diverse areas. To enhance understanding of the BOPPPS model's impact, future research could adopt longitudinal and mixed-method approaches, diversify and expand sample sizes, and explore cross-disciplinary and cross-cultural applications. Integrating new tools with the BOPPPS model is also recommended to further improve learner outcomes. [ABSTRACT FROM AUTHOR]

Biological memory networks are thought to store information by experience-dependent changes in the synaptic connectivity between assemblies of neurons. Recent models suggest that these assemblies contain both excitatory and inhibitory neurons (E/I assemblies), resulting in co-tuning and precise balance of excitation and inhibition. To understand computational consequences of E/I assemblies under biologically realistic constraints we built a spiking network model based on experimental data from telencephalic area Dp of adult zebrafish, a precisely balanced recurrent network homologous to piriform cortex. We found that E/I assemblies stabilized firing rate distributions compared to networks with excitatory assemblies and global inhibition. Unlike classical memory models, networks with E/I assemblies did not show discrete attractor dynamics. Rather, responses to learned inputs were locally constrained onto manifolds that 'focused' activity into neuronal subspaces. The covariance structure of these manifolds supported pattern classification when information was retrieved from selected neuronal subsets. Networks with E/I assemblies therefore transformed the geometry of neuronal coding space, resulting in continuous representations that reflected both relatedness of inputs and an individual's experience. Such continuous representations enable fast pattern classification, can support continual learning, and may provide a basis for higher-order learning and cognitive computations. [ABSTRACT FROM AUTHOR]

Despite the growing attention to the technology-enhanced embodied learning approach in mathematics education and its pedagogical potential, much remains unexplored regarding its implementation in real-world classroom contexts and student engagement in embodied learning activity. Addressing this gap, we introduce an embodied learning game leveraging computer vision and Augmented Reality (AR) techniques. We implemented the embodied AR game into fourth-grade classrooms to explore its impact on students’ geometry understanding, attitudes, and engagement patterns. Our analysis revealed significant enhancements in students’ geometry understanding from pre- to post-test, whereas their attitudes remained unchanged. A multiple regression analysis on students’ in-game log and hand gesture data showed that only time spent on making-angle activities predicts students’ cognitive learning gain, suggesting that not all hand gestures were meaningful to students’ learning. In addition to demonstrating the pedagogical benefits of cost-effective AR-based embodied learning in classroom settings, our findings highlight the importance of thoughtfully designing embodied actions that are both educational and engaging. [ABSTRACT FROM AUTHOR]

Education is an activity that involves great cognitive load for learning, understanding, concentrating, and other high-level cognitive tasks. The use of the electroencephalogram (EEG) and other brain imaging techniques in education has opened the scientific field of neuroeducation. Insights about the brain mechanisms involved in learning and assistance in the evaluation and optimization of education methodologies according to student brain responses is the main target of this field. Being a multidisciplinary field, neuroeducation requires expertise in various fields such as education, neuroinformatics, psychology, cognitive science, and neuroscience. The need for a comprehensive guide where various important issues are presented and examples of their application in neuroeducation research projects are given is apparent. This paper presents an overview of the current hardware and software options, discusses methodological issues, and gives examples of best practices as found in the recent literature. These were selected by applying the PRISMA statement to results returned by searching PubMed, Scopus, and Google Scholar with the keywords "EEG and neuroeducation" for projects published in the last six years (2018–2024). Apart from the basic background knowledge, two research questions regarding methodological aspects (experimental settings and hardware and software used) and the subject of the research and type of information used from the EEG signals are addressed and discussed. [ABSTRACT FROM AUTHOR]

Experience with instances that vary in their surface features helps individuals to form abstract task knowledge, leading to transfer of that knowledge to novel contexts. The current study sought to examine the role of this variability effect in how adults and school-aged children learn to engage cognitive control. We focused on the engagement of cognitive control in advance (proactive control) and in response to conflicts (reactive control) in a cued task-switching paradigm, and conducted four preregistered online experiments with adults (Experiment 1A: N = 100, Experiment 1B: N = 105) and 9- to 10-year-olds (Experiment 2A: N = 98, Experiment 2B: N = 97). It was shown that prior task experience of engaging reactive control makes both adults and 9- to 10-year-olds respond more slowly in a subsequent similar-structured condition with different stimuli in which proactive control could have been engaged. 9- to 10-year-olds (Experiment 2B) exhibited more negative transfer of a reactive control mode when uninformative cue and pre-target stimuli, which do not convey task-relevant information, were changed in each block, compared with when they were fixed. Furthermore, adults showed suggestive evidence of the variability effect both when cue and target stimuli were varied (Experiment 1A) and when uninformative cue and pre-target stimuli were varied (Experiment 1B). The collective findings of these experiments provide important insights into the contribution of stimulus variability to the engagement of cognitive control. [ABSTRACT FROM AUTHOR]

This study investigates the impact of AI-assisted language learning (AIAL) strategies on cognitive load and learning outcomes in the context of language acquisition. Specifically, the study explores three distinct AIAL strategies: personalized feedback and adaptive learning, interactive exercises with speech recognition, and intelligent tutoring with data-driven insights. The research employs a pretest-posttest random assignment experimental design, utilizing three experimental groups and a control group, with a total of 484 EFL students specializing in teaching English as a foreign language participating in the study. Data collection involves pre- and post-tests, questionnaires, and interviews to assess the influence of AIAL strategies on cognitive load and learning outcomes. Cognitive load is measured using the Cognitive Load Scale, while pretest-posttest assessments evaluate the efficacy of AIAL interventions across various language skills. These results contribute to the existing body of AIAL research by offering empirical evidence for the effectiveness of specific strategies in optimizing language learning experiences. The implications of this study extend to educators, researchers, and developers in the field of AIAL, emphasizing the potential of AIAL to enhance language acquisition processes and inform instructional design practices. [ABSTRACT FROM AUTHOR]

The cognitive emotions of individuals during tasks largely determine the success or failure of tasks in various fields such as the military, medical, industrial fields, etc. Facial video data can carry more emotional information than static images because emotional expression is a temporal process. Video-based Facial Expression Recognition (FER) has received increasing attention from the relevant scholars in recent years. However, due to the high cost of marking and training video samples, feature extraction is inefficient and ineffective, which leads to a low accuracy and poor real-time performance. In this paper, a cognitive emotion recognition method based on video data is proposed, in which 49 emotion description points were initially defined, and the spatial–temporal features of cognitive emotions were extracted from the video data through a feature extraction method that combines geodesic distances and sample entropy. Then, an active learning algorithm based on complexity and uncertainty was proposed to automatically select the most valuable samples, thereby reducing the cost of sample labeling and model training. Finally, the effectiveness, superiority, and real-time performance of the proposed method were verified utilizing the MMI Facial Expression Database and some real-time-collected data. Through comparisons and testing, the proposed method showed satisfactory real-time performance and a higher accuracy, which can effectively support the development of a real-time monitoring system for cognitive emotions. [ABSTRACT FROM AUTHOR]

With the continuous development of embodied cognition theory and virtual reality (VR) technology, its application in teaching has been paid more and more attention by researchers. However, there are still few practical studies on the combination of VR technology and embodied learning. Starting from literature research, the paper analyzes the factors that affect the embodied learning in the VR environment; then, put forward the design principles under the support of VR based on the previous studies; finally, constructs the embodied learning design framework, combined with the two parts of study. The research chooses a course (namely Discrete Mathematics) as an example of embodied learning design case, which organizes the application facing college students in Computer Science and Technology major of Nanchang Institute of Technology. The study found that the body is indeed involved in the cognitive process, and the embodied learning based on VR can effectively improve the learning achievement and has a positive impact on learners' learning participation and interest in learning during the experiment. [ABSTRACT FROM AUTHOR]

This mixed method study examined the effects that a Self-Regulated Multimedia Cognitive Learning Model, infused with internationally acclaimed effective instructional vocabulary strategies, had on the vocabulary acquisition skills of adult English Learners enrolled in a college course. Outcome measures included vocabulary pretests and posttests, surveys, and participant interviews. Quantitative data were analyzed using descriptive statistics and paired samples t-tests whereas qualitative data was analyzed using open, axial, and selective coding. Findings were statistically significant across all six vocabulary tests, with large effect sizes. Overall, adult English Learners perceived the vocabulary instruction using a Self-Regulated Multimedia Cognitive Learning Model to be beneficial to their vocabulary learning and useful for generalization purposes outside of the classroom. Future research and implications for practice are also offered for the use of the Self-Regulated Multimedia Cognitive Learning Model to improve second language learning and the college success rates of English Learners in the United States. [ABSTRACT FROM AUTHOR]

This paper explores how business angels develop the knowledge necessary to offer sustainability-value-adding activities, thereby becoming green angels. A multiple case study was conducted based on five investors from Germany and Sweden who offer sustainability-value-adding activities without having had explicit previous sustainability experience. Bringing together the empirical findings and literature on angel learning and sustainability competences, the introduced model illustrates that angels continuously apply a combination of hybrid strategies. The result of these learning strategies is sustainability-specific knowledge in a complex entrepreneurial context, including conceptual and systemic sustainability knowledge, critical thinking, ethical considerations, and capabilities for change. This study adds to the business angel literature as it empirically demonstrates how business angels go beyond the experiential, informal, and individual learning centered by existing literature and include a combination of vicarious, collective, and formal strategies. [ABSTRACT FROM AUTHOR]

Previous studies have reported the importance of regulation in collaborative learning. To understand and support students' learning, researchers have identified that regulation in collaboration emerges as a series of contingent activities at individual and social levels, addressing various learning foci in cognitive, motivational, emotional, and behavioural aspects. However, explanations on how different levels and foci of regulation together influence learning performance have not been made clear. To capture the complexity of regulated learning and the linkage to learning performance, this study examined the temporal sequences of regulated learning, including types (levels), sub-processes, and foci of regulation. Video and interview data were collected from undergraduate students working on a collaborative learning task. These multi-channel data were analysed by content analysis and triangulated to identify the dynamic emergence of regulation events. Process mining was employed to analyse and visualise the temporality and sequences of regulatory processes. The results showed that co-regulated content monitoring was critical in facilitating regulation and task execution at a group level. High-performing groups demonstrated different patterns in developing shared content monitoring and co-regulation of motivation and emotion in the overall learning task. Meanwhile, the variances in how the groups regulated content development and task progress across learning phases were identified. This research extends the conceptualisation of regulated learning to a dynamic multi-layered system. The methods and findings from this study have implications for developing timely and systemic support to improve group performance. [ABSTRACT FROM AUTHOR]

AbstractPrior research has focused on students’ affectional states during learning, recognizing that affect can elevate learning and cognitive development. This study hypothesized and investigated the bidirectionality or reciprocity of the relationships between students’ affects and performance in reading comprehension. Mixed methods were used in the study. 41 3rd grade (9-year-old) students went through mind mapping in reading intervention for one semester. Pre- and post-intervention surveys and post-interviews were conducted to investigate their affectional and self-efficacy levels in reading comprehension. Their mind maps were also collected to evaluate their performance in reading comprehension. The study results revealed that the use of mind mapping in reading activities led to a widespread sense of positive affect. Furthermore, positive affect was found to be influenced by reading comprehension, and reading comprehension could contribute to changes in affect by enhancing reading performance and increasing self-efficacy. This study elevates the understanding of the mind mapping in reading strategies, provides references for the affectional design of such activities, and derives design and enactment principles to transform mind mapping in reading activities. [ABSTRACT FROM AUTHOR]

Inspired by animal navigation strategies, we introduce a novel computational model to navigate and map a space rooted in biologically inspired principles. Animals exhibit extraordinary navigation prowess, harnessing memory, imagination, and strategic decision-making to traverse complex and aliased environments adeptly. Our model aims to replicate these capabilities by incorporating a dynamically expanding cognitive map over predicted poses within an active inference framework, enhancing our agent's generative model plasticity to novelty and environmental changes. Through structure learning and active inference navigation, our model demonstrates efficient exploration and exploitation, dynamically expanding its model capacity in response to anticipated novel un-visited locations and updating the map given new evidence contradicting previous beliefs. Comparative analyses in mini-grid environments with the clone-structured cognitive graph model (CSCG), which shares similar objectives, highlight our model's ability to rapidly learn environmental structures within a single episode, with minimal navigation overlap. Our model achieves this without prior knowledge of observation and world dimensions, underscoring its robustness and efficacy in navigating intricate environments. [ABSTRACT FROM AUTHOR]

Serious games are generally considered to induce positive effects in the areas of learning motivation and learning gains. Yet few studies have examined how these factors are related specially in the context of visual aesthetic studies. Therefore, an empirical study was conducted to test the relationship between anticipated enjoyment and willingness to play, as well as between game enjoyment, self-reported cognitive and motivational learning gains and test results. In an explorative study, 25 students from undergraduate course in architecture school played the learning game Temple Lego. The results of pre-test and post-tests were analyzed using multiple linear regressions. The analysis showed that anticipated enjoyment played only a minor part in students' willingness to learn with serious games. Of greater importance was the students' expectation that the learning game would be easy and instructive. There was a correlation between enjoyment and the post-test scores to continue being engaged with the subject matter of the game. We discuss the findings and pedagogical implications that can be applied to developing serious virtual reality (VR) games to learn about similar historical structures and contexts which is novel and sparsely explored. [ABSTRACT FROM AUTHOR]

This study describes and evaluates online simulations of social work practice skills training, which involved social worker-client interaction exercises that students performed on Zoom with trained actors portraying clients. The aim was to identify factors that affect learning in a simulation exercise. To improve our understanding of learning in a simulation, we looked at the applicability of an integrative pedagogy model to analyze the data. In total, 38 social work students replied to the online survey consisting of Likert-scale and open-ended questions. The quantitative data was analyzed with principal components factoring method and analysis of variance, and the qualitative material with content analysis. In the students' learning process, three levels of human activity based on the integrative pedagogy model were obtained from the quantitative data: emotional, cognitive, and social. Based on the qualitative material, factors that strengthen learning at different levels were identified. In the results, the role of emotions in the learning process was emphasized. Emotional learning is strengthened by overcoming performance anxiety and the courage to immerse oneself in the exercise, which is connected to a feeling of security, and a permissive and constructive atmosphere. Intermediate interruptions are a significant factor in strengthening cognitive learning in simulation exercises. [ABSTRACT FROM AUTHOR]

Explaining how neuronal activity gives rise to cognition arguably remains the most significant challenge in cognitive neuroscience. We introduce neuro-cognitive multilevel causal modeling (NC-MCM), a framework that bridges the explanatory gap between neuronal activity and cognition by construing cognitive states as (behaviorally and dynamically) causally consistent abstractions of neuronal states. Multilevel causal modeling allows us to interchangeably reason about the neuronal- and cognitive causes of behavior while maintaining a physicalist (in contrast to a strong dualist) position. We introduce an algorithm for learning cognitive-level causal models from neuronal activation patterns and demonstrate its ability to learn cognitive states of the nematode C. elegans from calcium imaging data. We show that the cognitive-level model of the NC-MCM framework provides a concise representation of the neuronal manifold of C. elegans and its relation to behavior as a graph, which, in contrast to other neuronal manifold learning algorithms, supports causal reasoning. We conclude the article by arguing that the ability of the NC-MCM framework to learn causally interpretable abstractions of neuronal dynamics and their relation to behavior in a purely data-driven fashion is essential for understanding biological systems whose complexity prohibits the development of hand-crafted computational models. Author summary: Despite several decades of research, the way in which neuronal activity generates cognition remains elusive. A significant obstacle to understanding this phenomenon is the lack of a rigorous mathematical framework for exploring such questions, including a precise definition of what constitutes a cognitive state. In this work, we introduce such a framework along with machine-learning algorithms capable of learning cognitive states from neuronal data. A distinctive feature of our approach is causal consistency; that is, we develop a cognitive model that aligns with the neuronal-level model in such a way that causal assertions at one level can always be translated to the other level. We demonstrate the application of these models using the simple model organism C. elegans, in which we find highly reproducible cognitive states across multiple animals. [ABSTRACT FROM AUTHOR]

Simple Summary: Larval zebrafish are increasingly used as a model for studying the neurobiology of cognition, but reliable methods for assessing cognitive functions such as learning and memory in their early developmental stages remain scarce. A recently developed operant conditioning procedure allows newly hatched larvae to associate a specific stimulus with a food reward, providing a tool to investigate diverse aspects of cognition. However, this method also presents some limitations that could hinder its adoption as a standard procedure across research laboratories. In our study, we replicated the procedure in a separate laboratory, achieving only partial success. Two further experiments were conducted to optimize the methodology. While both modified procedures con-firmed a stimulus–response association in newborn larvae, neither achieved the performance levels reported by the original research. Our findings underscore the importance of validating and refining behavioral paradigms to ensure their robustness and ease of reproduction across laboratories. This work contributes to establishing reliable methods for exploring cognitive development in zebrafish, with potential implications for broader neurobiological research. Zebrafish have emerged as prominent model organisms in neurobiological research. Although most studies are performed on embryonic and larval stages within the first week post-hatching, tools for assessing cognitive functions during these early developmental stages remain limited. An appetitive conditioning paradigm has been recently developed that demonstrates discrimination learning within days of hatching and holds promise for the assessment of perception, memory, and executive functions. Despite its potential, the utility of this paradigm is hindered by certain limitations and confounding factors that may undermine its replicability. To address these concerns, we conducted a replication of the experiment in a separate laboratory, which revealed partial replicability and confirmed the drawbacks identified in the original study. Subsequently, we explored two modifications to the procedure in an effort to overcome these limitations. While both experiments demonstrated significant stimulus–response associations, the outcomes were unsatisfactory as performance in both cases fell well below that of the original procedure. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to assess the effectiveness of brainbased learning methods in enhancing seventh-grade students' intrinsic motivation and performance in mathematics. Methods and Materials: An applied, intervention-based study design was employed with 39 seventh-grade male students from a public middle school in Tehran during the 2023-2024 academic year. The study used simple random sampling and included three phases: baseline, intervention, and postintervention. Quantitative data were collected using the Mathematics Motivation Scale (MMS), while qualitative data were gathered through field notes. The intervention phase incorporated brain-based learning activities such as visual storytelling, role-playing, kinesthetic learning, brainstorming, critical thinking, and creative thinking exercises. Data analysis involved one-way repeated measures analysis of variance (ANOVA) and thematic analysis using SPSS and NVivo software. Findings: The results indicated that the students' average scores for intrinsic motivation and performance in mathematics were significantly higher during the intervention phase compared to the baseline phase. Although scores decreased in the post-intervention phase, they remained higher than the baseline scores. The ANOVA results, adjusted using the Huynh-Feldt correction, showed a significant effect of brain-based learning activities on intrinsic motivation (F(2.95) = 111, p < 0.01, ηp2 = 0.75). Qualitative analysis supported these findings, highlighting increased student engagement and participation during the intervention phase. Conclusion: Brain-based learning activities significantly enhance students' intrinsic motivation and performance in mathematics. The study underscores the importance of incorporating such strategies into regular teaching practices to sustain high levels of student motivation and achievement. [ABSTRACT FROM AUTHOR]

Copyright of Retos: Nuevas Perspectivas de Educación Física, Deporte y Recreación is the property of Federacion Espanola de Asociaciones de Docentes de Educacion Fisica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: How can managers reduce information asymmetry in dyadic manager-external stakeholder relationships in a complex and evolving environment? Addressing this question has significant implications for firm survival, growth, and competitive advantage. Design/methodology/approach: We have adopted a multiparadigm approach to theory building, known as metatriangulation. We integrate the dynamic capabilities, sensemaking, and evolutionary theory literatures to theorize how managers can relate to stakeholders in a complex and evolving environment. Findings: We propose, via a conceptual framework and three propositions, "evolutionary sensemaking" as the managerial metacognitive dynamic capability that helps managers hone their understanding based on the evolutionary changes in the stakeholder's interpretations of information quality preferences. The framework unfolds across three evolutionary stages: sensing preferences' variation of the stakeholder, seizing preferences, and transforming for complexity alignment and retention. The propositions focus on managing complexity in stakeholder information quality preference, employing cognitive capabilities to simplify, interpret, and align interpretations for effective information asymmetry reduction. Practical implications: To develop the metacognitive dynamic capability of evolutionary sensemaking, managers need to train for and foster the underlying complex cognitive capabilities by enhancing their (1) perception and attention skills, (2) problem-solving and reasoning skills, and (3) language, communication, and social cognition skills, focusing specifically on reducing the complexity embedded in stakeholder cognition and diverse stakeholder preferences for information quality. Contrary to the current advice to "keep things simple" and provide "more" information to the stakeholders for opportunism reduction, trust-building, and superior governance, our framework suggests that managers hone their cognitive capabilities by learning to deal with the underlying complexity. Originality/value: The proposed framework and propositions address research gaps in reducing information asymmetry. It enriches the dynamic capabilities literature by recognizing complexity (as opposed to opportunism) as an alternative source of information asymmetry, which needs to be addressed in this stream of research. It extends the sensemaking literature by identifying the complexity sources – i.e. stakeholder preferences for diverse information quality attributes and the associated cognitive preference interpretation processes. The article enhances evolutionary theory by delving into microprocesses related to information asymmetry reduction, which the existing literature does not thoroughly investigate. [ABSTRACT FROM AUTHOR]

As an innovative form of course, connectivist massive open online courses (cMOOCs) have attracted widespread participation. Learners in cMOOCs achieve cognitive network development through instructional interactions, but the underlying laws of this development are not yet fully understood. This study aims to contribute to this exploration by focusing on the analysis and comparison of cognitive networks, as represented by interaction content, among different types of learners. It established a cognitive encoding framework, encoded learners’ interaction content, classified learners based on learning outcomes and engagement durations, and applied epistemic network analysis and statistical analysis to data from the first Chinese cMOOC. The findings indicate that cMOOC learners can be classified into four categories: successful long-term learners, failed long-term learners, successful short-term learners and failed short-term learners. Learners with different outcomes exhibit varying cognitive networks, with certificated learners showing more complex structures. Learners with different time investments do not exhibit differences in their cognitive networks. Successful short-term learners, demonstrating more complex cognitive networks, tend to rush to complete assignments. This study contributes to the field by providing recommendations for promoting cognitive development of cMOOC learners. These insights are valuable for instructional design, learners’ cognitive assessment and learning interventions for future cMOOCs. [ABSTRACT FROM AUTHOR]

Introduction: Building upon previous research, this study aims to provide answers to the questions of how the presence of a humanoid artificial pedagogical agent as teacher and instructor and visual self-other representation of the learners through avatars influence the immediate cognitive performance and learning experience in online learning among adult learners. Methods: Several outcome measures were investigated to evaluate if effects are the same or different for the different experimental conditions and if learning with the pedagogical agent and visual self-other representation is modulated by the learner's previous experiences with and preferences for online learning. Teacher presence and self-other presence of the learners were experimentally manipulated. A humanoid artificial agent, visible on all of the slides of the online course material and instructing the material represented the teacher. The avatars of the learners (self-avatar and peer avatars) were kept of minimal functionality but self-avatars were preselected or could be self-selected by the learners. The learner's cognitive learning performance, the learner's attention to the pedagogical agent, their sense of teacher presence and of self- and other-presence, their satisfaction with the course as well as the learner's previous learning experiences were measured by cognitive testing, self-report, and linguistic analysis as major performance indicators and a positive learning experience. The analysis comprised 133 university students and results were additionally compared for two subsamples. Results: Learning performance, learning satisfaction, and the attention paid to the teacher were positively related. In addition, positive evaluations of the cognitive presence elicited by the teacher were found. Self- or other-presence of avatars did not significantly influence the learner's performance beyond teacher presence but the learner's perception of it and their motivation to study online. Discussion: The study and its results extend the previous literature that focused on the effects of pedagogical agents in online teaching or on virtual representations of the learner's self and classmates in online learning. Despite limitations, the results of this study provide insights into combining teaching with artificial pedagogical agents and visual avatars for self-other representation during online teaching and the observations can serve as catalyst for future research. [ABSTRACT FROM AUTHOR]

AbstractEnsuring equitable access to professional education programs for learners who need accommodations is distinctly challenging when education moves beyond the classroom into clinical or fieldwork sites. Fieldwork educators and university academic coordinators who arrange fieldwork placements work with university accessibility services and students to arrange required accommodations, while preserving confidentiality, maintaining high learning standards, and ensuring attainment of professional competencies. This work is complicated by time pressures and heavy caseloads in fieldwork settings. Here we report on a subset of data from a cross-Canada online survey of fieldwork educators (n = 233) and academic coordinators (n = 54) in 10 health and social service professions. Using descriptive statistics, we analyze responses to two question series concerning perceptions of the capacity of disabled students to attain professional competencies, and overall perceptions of students who need accommodations. Respondents showed most concern about competency attainment for learners with cognitive or learning disabilities, followed by neurological and mental health issues. Thematic analysis of open-ended comments suggests doubt regarding the ability of institutional fieldwork sites to adequately implement accommodations. In their perception of learners who need accommodations, academic coordinators were somewhat more negative than fieldwork educators, in particular seeing students who need accommodations as a potential burden that could harm placement relationships with fieldwork sites. They tended to indicate that fieldwork success depended on student insight and self-advocacy. Struggles faced by disabled students in health and social service professions appear to be occasioned not only by disabling systems and institutions, but also by perceptions that they may have diminished competence. [ABSTRACT FROM AUTHOR]

The relationship between cognitive engagement and learning gains in computer programming has not been well-studied. This study examined the relationship between students' cognitive engagement and learning gains in the context of Python programming. Cognitive engagement, defined by the Interactive, Constructive, Active, Passive (ICAP) framework, refers to the level and depth of mental effort and involvement a learner invests in an educational activity. In this paper, we provide details about how students' actions were classified into three levels of cognitive engagement. We studied these actions' frequency and duration differences and performed regression analysis. The results revealed significant student diversity regarding frequency and time allocation to these engagement categories and highlight the complex interplay between students' cognitive activities and their corresponding time investments. Further, the regression analysis results showed that the constructive and passive levels of engagement were significant predictors of students' learning gains in the case of Python programming.These findings offer actionable insights into why some students may have lower learning gains. By examining the specific levels of cognitive engagement that lead to better learning outcomes, this study hopes to inform the development of more effective learning environments that support student engagement and improve programming education. [ABSTRACT FROM AUTHOR]

Cognitive ability plays a crucial role in adolescents' academic performance and subsequent career development. Although previous studies have demonstrated that physical activity, self-education expectations, and learning behaviors positively affect the cognitive development of adolescents, the extent of their influence and their mediating roles require further elucidation. This study is based on tracking survey data from 2,688 adolescents in Chinese households collected in 2018. Multiple linear regression, Propensity Score Matching, and Quantile regression were employed to analyze the impact and heterogeneity of physical activity on adolescents' cognitive ability. Furthermore, the Bootstrap mediation test was used to explore the mediating roles of self-education expectations and learning behaviors in this process. The results indicate the following: Physical activity significantly promotes adolescents' cognitive ability; for those with poorer cognitive ability, it exerts a greater impact. Moreover, in addition to its direct effects, physical activity indirectly enhances adolescents' cognitive ability through the mediation of three factors (self-education expectations, learning behaviors, self-education expectations and learning behaviors). These discoveries offer significant insights into diverse strategies for developing cognitive ability in adolescents, contributing to both theoretical research and practical interventions. [ABSTRACT FROM AUTHOR]

Background: Critical thinking and learning styles are important in students' learning processes. The study examined the relationship between critical thinking and cognitive learning styles with general English proficiency and success in examinations. Method: In this descriptive cross-sectional study, 138 students at Gonabad University of Medical Sciences in 2019-2020 were selected through convenience sampling. To collect data, a critical thinking scale, a learning cognitive style questionnaire, a general English proficiency test, and a general English final exam were used. The obtained data were analyzed using descriptive and inferential statistics through SPSS V.22. Results: Descriptive statistics showed that among critical thinking components, 35.4% of participants had deductive and inductive reasoning components. Out of cognitive learning styles, most had divergent styles, claiming 47.1% of the cases. ANOVA results showed a significant relationship between critical thinking and general English proficiency as well as success in the English final exam (p=0.045 and p=0.037, respectively). However, ANOVA results revealed no significant relationship between cognitive learning styles and general English proficiency as well as success in the English final exam among students (p=0.41 and p=0.06, respectively). Conclusion: It is concluded that the higher the critical thinking skills in deductive and inductive components among students are, the greater their proficiency in the English language and their success in English final exams will be. Regarding cognitive learning styles, the students would integrate concrete experimental methods and reflective observational methods and have the greatest ability to observe concrete situations. [ABSTRACT FROM AUTHOR]

Purpose: Focused feedback, such as mentoring and coaching, is a crucial ingredient for generating the intellectual capital needed for successful venture creation and has become a structural resource offered to entrepreneurs in business incubator/accelerator programs. Yet so far, literature has remained silent on the way that entrepreneurs differ in their engagement with focused feedback in such programs. This study poses the question of how focused feedback engagement shapes cognitive development during value creation (i.e. business opportunity development), aimed at the construction of a taxonomy of such feedback engagement. Design/methodology/approach: Focusing on cognitive learning outcomes, we carried out a qualitative analysis using NVivo to perform content analysis on the logbooks of 70 entrepreneurs engaged in business opportunity development in a highly regarded accelerator program. Findings: Results show that engagement with focused feedback and its effects relate to the state of tangibility of the entrepreneur's value offer and to the amount of prior entrepreneurial experience. We also develop a promising taxonomy to classify entrepreneurs on their learning needs and outcomes (e.g. procedural versus declarative knowledge). Originality/value: This study brings together types of human learning (types of knowledge acquired) with types of focused feedback. This connection has been speculated to exist in entrepreneurial settings; this study provides strong initial evidence that argues for more explicit consideration in practice. Adding the intellectual capital perspective further enabled this study to better address implications for practice as well as motivate powerful new directions for research. [ABSTRACT FROM AUTHOR]

Assigning students to work in permanent teams is a design principle in Team-based learning (TBL). It has been assumed that a stable team composition supports the emergence of collaborative problem-solving and learning: when students became more familiar with each other, they shared more information and resolved discrepancies together, which in turn stimulated knowledge acquisition and comprehension. However, this assumption had not been probed by a randomized controlled trial with performance assessment as an outcome. In an online course for second term medical students, 50% of the students were reassigned to new teams for each of the 24 problems to be solved during four classes, thus precluding familiarity. The learning outcome was assessed shortly after the third of four classes by a domain knowledge test. Whether TBL teams were permanent or temporary did not affect the score of a domain knowledge test. As expected, participation in online TBL improved the domain knowledge test results. Overall, the permanent team seems to be less important for cognitive learning outcomes than previously assumed, but this may depend on the specific educational setting. However, team familiarity may still be important for team decision-making. As clinical reasoning in the medical workplace often involves collaborating in changing teams, future research on TBL should focus on how to utilize this format to prepare medical students for decision-making and optimal learning outcomes under these conditions. [ABSTRACT FROM AUTHOR]

A highly authentic learning setting is likely to trigger positive motivational and emotional reactions due to its emphasis on promoting the acquisition of knowledge that is connected and transferable to real-world phenomena outside the learning environment. However, a high level of authenticity is usually accompanied by a high level of complexity due to the complexity inherent in the real world. This complexity can be overwhelming for learners and can hamper or even prevent cognitive learning outcomes. Consequently, to help learners cope with this complexity, they need some kind of instructional support. By building a high level of support into the learning setting in order to promote cognitive learning outcomes, the level of authenticity and thereby the effects of authenticity on motivational outcomes may, however, in turn be reduced. In the present conceptual paper, we refer to this tension between authenticity and complexity, on the one hand, and instructional support, on the other hand, as the "authenticity dilemma". Based on existing empirical evidence from previous studies, we (1) outline this dilemma, (2) discuss ways to reconceptualize it, and (3) derive implications regarding the conditions and effects of authentic learning. Finally, we discuss the findings of the studies included in the special issue "Perspectives on Authentic Learning" through the lens of the authenticity dilemma. [ABSTRACT FROM AUTHOR]

The implementation of video modeling examples of mathematical hands-on experimentation may provide students with authentic and, at the same time, not too cognitively overwhelming experiences. However, the effectiveness of video modeling examples can be influenced by different characteristics of the observed models. On the one hand, based on the model-observer similarity hypothesis, it is likely that the observation of peers is particularly conducive to learning. On the other hand, from an authentic learning perspective, the presence of experts is considered to constitute a core design element of authentic learning settings which may foster motivational and cognitive learning outcomes. Against the background of these contradictory assumptions, the present study investigates the effects of observing models with different degrees of authenticity on students' perceived authenticity, their situational interest, and their knowledge acquisition. We conducted an experimental study with 105 10th graders who observed either peer or scientist models performing a mathematical hands-on experiment in a video recording. As expected, the results show that students perceived the scientist models as more authentic than the peer models. Furthermore, we found neither a direct effect of condition nor an indirect effect mediated by students' perceived authenticity of the observed models on students' situational interest and knowledge acquisition. With this study, we contribute to the literature on the conditions and effects of authentic learning. [ABSTRACT FROM AUTHOR]

This research investigates the influence of cognitive styles and learning interest on students' understanding of physics concepts. Using a survey method with a sample of 88 first-year students from four programs at a Health Polytechnic in South Jakarta, data were collected through questionnaires on cognitive style perception, learning interest, and a physics concept understanding test. Findings from multiple regression analysis reveal: (1) Cognitive styles and learning interest collectively have a significant influence on physics concept understanding (p = 0.000, F = 26.084); (2) Cognitive style perception independently affects concept understanding (p = 0.047, t = 2.013); and (3) Learning interest significantly impacts concept understanding (p = 0.001, t = 3.426). The study highlights the interplay between cognitive preferences and motivation in achieving mastery of physics concepts. [ABSTRACT FROM AUTHOR]

The steam turbine and its digital electro-hydraulic (DEH) control system constitute vital elements within thermal power generation. However, the complexity of the on-site environment and the high production costs of the equipment hinder users, especially novices, from fully understanding and mastering the operation mechanisms and production processes. In the realm of emerging technologies, the digital twin stands out as a powerful tool for enhancing industrial training and learning for students and operators in this field. This paper details the design and implementation of a web-based digital twin steam turbine system. Initially, a pioneering web-based digital twin architecture is proposed, featuring high-fidelity equipment modeling, web-based immersive 3D displays, algorithm design and networked implementation, and data-driven model synchronization. Subsequently, the functionalities and benefits of the digital twin system in facilitating industrial training are explained, covering aspects such as steam turbine cognitive learning, DEH system simulation learning, and condition monitoring. Finally, a case study in a real thermal power plant is presented to demonstrate the practicability and effectiveness of this web-based digital twin system. This research endeavors to contribute valuable insights and potential solutions to the growing field of web-based digital twin applications in industry. [ABSTRACT FROM AUTHOR]

Online learning burnout poses a paramount concern due to its detrimental influence on students' academic cognitive learning and mental health. Aiming to explore the association between teacher humour (content-related and content-unrelated) and online learning burnout, this study surveyed 585 college students enrolled in various online courses. The results show that teacher humour, regardless of its relevance to the course content, does not directly correlate with online learning burnout. However, both types of humour can indirectly relate to burnout through enjoyment and boredom. Content-related humour exhibits a negative correlation with boredom and a positive relationship with enjoyment. In contrast, content-unrelated humour is positively correlated with boredom. These findings underscore that teachers should be cautious about employing humour in online teaching because not all forms of humour can play a positive role. This study also contributes to inspiring teachers to integrate content-related humour with online teaching, laying a foundation for future research. [ABSTRACT FROM AUTHOR]

Cognitive styles and affective factors are critical factors affecting e-learning performance in this digital era. Learners can enhance their affective learning with a correct cognitive style. This study aims to examine various cognitive styles with effective learning measurement tools through subjective and objective instruments by observing physiological signals and mental load questionnaires as the matching and mismatching styles matter to learning outcomes. The research design adopted multiple measurements to examine the effects of cognitive styles on learning outcomes. The mental load measure included the system usability scale and the NASA task load index (NASA-TLX) scale. The objective measure adopted physiological signals, including emotion, brainwave attention, heart rhythm variability, blood oxygen concentration, breathing, skin temperature, and galvanic skin response. The results revealed that matching cognitive style learners had better learning performance with more positive emotion and less mental load, fatigue, and stress than mismatching cognitive style learners. We concluded that the matching cognition of learning materials could benefit learning outcomes. [ABSTRACT FROM AUTHOR]

Online collaborative learning (OCL) has become a common instructional strategy in higher education for developing students' skills in collaboration, problem-solving, and critical thinking. Cognitive engagement in OCL evolves dynamically, but we do not yet fully understand which patterns of cognitive engagement are conducive to OCL and when to promote them. This study used entropy analysis, sequential pattern mining, and temporal network analysis to examine the online discourse of 44 college students who participated in three OCL tasks. Results showed that, compared with the low-performance groups, the high-performance groups exhibited patterns of continuous perspective elaboration and low-level regulation, as well as frequent shifts from perspective expression to perspective elaboration. In addition, there were differences in the longitudinal evolution patterns of cognitive engagement between the high- and low- performance groups. These findings have important implications for learning tool design and improving collaborative learning design. [ABSTRACT FROM AUTHOR]

This study investigates the impact of using rock type classification comparator board media in contextual learning on the geography learning outcomes of grade X students at SMAN 22 Surabaya. The research employed a quantitative descriptive approach with a quasi-experimental design, involving pre-tests and post-tests for experimental and control groups. Data were collected through observations, questionnaires, and test instruments. The validity and reliability of the research instruments were confirmed through Cronbach's Alpha values exceeding 0.6. Results indicate that the use of comparator board media significantly enhances student learning outcomes in terms of cognitive, affective, and psychomotor aspects. The Mann-Whitney Test revealed a significant difference between pre-test and post-test scores (p < 0.05), while the Spearman Rank Correlation showed varied results, with positive correlations in the affective aspect (0.611) and negative correlations in cognitive (-0.146) and psychomotor (-0.087) aspects. Despite the high cost of the media being a limitation, the tool's functionality and its ability to foster collaborative learning make it effective in improving student engagement and understanding of lithosphere materials. This study highlights the importance of innovative teaching tools in enhancing learning outcomes. [ABSTRACT FROM AUTHOR]

Leadership is an essential, fundamental quality for university students in the present age. Leadership education is essential for students to develop new talents with an international outlook and a willingness to shoulder international responsibilities. Emotionally intelligent leadership (EIL) is an organic aspect of leadership in university students, with the cognitive dimension of university student leadership often realized via their emotional intelligence. To investigate the relation between EIL in students and their cognitive learning ability, this study surveyed 480 students (157 males and 323 females) from three arts universities in Hebei province, China. The results indicate that emotional awareness, self-awareness, and awareness of others have a significant impact on cognitive learning abilities. Gender is a moderating factor between EIL and cognitive learning abilities, with the effect of EIL on such abilities being greater for males than females. The results and suggestions of this study will provide new exploration for the development of emotionally intelligent leadership theory and provide a theoretical basis for the management of art major classes in higher education institutions in Hebei province, so as to better fulfill the function of talent cultivation. [ABSTRACT FROM AUTHOR]

The authors review the philosophical understanding of design education in basic school education, and this suggests the need for a more contextual re-conceptualization of the topic. The article expands on an epistemological perspective on understanding the cognitive modes and the learning styles in relation to design education as a part of the basic school education. The authors re-conceptualize the topic and offer clear propositions and models for more insightful and meaningful teaching-learning. The models are examined in depth through a practice research study that explores the scope for feasibility, implementation, and evaluation of the effectiveness of an activity-based teaching-learning, as a part of middle school craft and design education. The objective of the practice is to develop and examine an interdisciplinary teaching framework for Design Education based on the traditional approaches to design learning at Bauhaus, Ulm, and the National Institute of Design. The theoretical significance of the study is to set an example of how design sensibility and awareness can be cultivated in children through indigenous resources and strengths and art and craft heritage. The participatory visual research method is employed, in which the students present their work as learning evidence. The effectiveness of the project is further evaluated by giving the students a pre-questionnaire and a post-questionnaire to determine the enhancement in learning. The results that are drawn from this intervention aim to contribute to future practice and research in design education and the development of a framework for design education curriculum at the school level. [ABSTRACT FROM AUTHOR]

This systematic review examines 76 studies that have utilised portable electroencephalographic (EEG) devices in naturalistic and semi‐naturalistic contexts. The review considers themes, purposes, contexts, application populations, device characteristics, and data use. The results show a dominance of studies focused on attention, in technology‐mediated semi‐naturalistic situations, in which records are made individually, with university students using low‐cost equipment with fewer than 15 channels. This review highlights an emerging field within educational research that has not yet been fully integrated into educational practice. However, these first experiences can gradually generate a body of knowledge that will facilitate future applications, together with the development of better and more accessible devices. The use of these devices in educational contexts raises ethical concerns, particularly the influence on teaching decisions by opaque commercial algorithms that may oversimplify assessments of specific cognitive processes and fail to adapt to individual student characteristics. Context and implicationsRationale for this study: Portable EEG devices are emerging tools that offer new insights into cognitive processes in learning situations.Why the new findings are important: The findings of this study demonstrate the potential of EEG to monitor aspects such as attention and cognitive load in real time, which could enhance the personalisation of educational strategies.Implications for educators, researchers and policy makers: This study has implications for educators, researchers and policy makers, as it illustrates how neurotechnology can be integrated into educational settings and emphasises the need for more naturalistic studies to maximise its impact. It also highlights the ethical challenges associated with the use of commercial algorithms in educational decision‐making. [ABSTRACT FROM AUTHOR]

Earlier studies repeatedly showed increased learner motivation due to game elements, while overall cognitive effects on learning outcomes were absent. One possible explanation for this discrepancy is provided by theories integrating cognitive and affective learning processes: the beneficial effect on learner motivation eventually balancing simultaneously higher cognitive processing demands associated with game elements. In this paper, we provide results of an empirical test of this theoretical suggestion. In particular, we report results of a value-added online experiment (with n = 61 participants, mostly students; 44 female, 15 male, 2 diverse; median age: 24 years), comparing a more gameful with a less gameful version of a learning task. In agreement with earlier studies, we find similar cognitive learning outcomes (d < 0.2), but medium (d ~ 0.5) and large (d ~ 0.9) effects on affective and motivational outcomes, respectively. Furthermore, mediation models show that a small negative direct effect of game elements on cognitive outcomes (ß ~ -0.2) is indeed effectively cancelled by an indirect path through motivational outcomes (ß ~ +0.4). Overall, our results corroborate the tenability of the integrated cognitive affective model of learning with multimedia. This implies its feasibility in purposefully designing learning environments with specific motivational or cognitive aims in mind. [ABSTRACT FROM AUTHOR]

The innovative application of indirect feedback alignment (IFA) in deep learning enhances workplace self-confidence analytics through cognitive agent modeling. IFA addresses the challenge of credit assignment in multilayer neural networks, offering a more efficient and biologically plausible alternative to traditional backpropagation methods. The paper delves into the integration of IFA in workplace dynamics, focusing on the development of a state-determined system to describe and analyze the dynamics of selfconfidence, self-concept, self-esteem, and self-efficacy among employees. Utilizing a combination of endogenous and exogenous factors, the study presents a comprehensive model that captures the complex interplay of these factors in professional settings. The research further conducts experiments to observe and analyze the behavior and pattern formation among real workers in various settings, demonstrating the practical implications of the theoretical model. The findings highlight the potential of IFA in enhancing and accelerating the components of deep learning associated with selfconfidence in the workplace, contributing significantly to the fields of neural computation and cognitive psychology. The proposed method was tested in various situations to assess its alignment with the core concepts of workplace self-confidence. Mathematical analysis was employed to explore feasible equilibrium conditions and compatible cases found in the literature. [ABSTRACT FROM AUTHOR]

Picture-in-Picture (PIP) is an effective lecture video design that includes a screen capture video in the center and the instructor's talking head in one corner. Few research studies have directly investigated the usage of PIP lecture design by non-native English-speaking (NNES) instructors. The current study investigated the effects of PIP lecture design by NNES instructors and measured participants' cognitive load and learning outcomes. Participants in the study (n = 56) watched four lecture videos about airplane flight, completed cognitive load measure questionnaires, and completed the subsequent recall tasks. The videos included either an NNES instructor or a native English-speaking (NES) instructor. Our findings indicated that PIP lecture videos produced by an NNES instructor caused a higher cognitive load, especially in learners with lower accented-language experience. Lecture videos produced by the NNES instructor also led to lower recall performance, but the PIP design did not cause a significant change in participants' recall performance. Findings from the current study have implications for online lecture designs, especially for NNES instructors. [ABSTRACT FROM AUTHOR]

Procedural learning and automatization have widely been studied in behavioral psychology and typically involves a rapid improvement, followed by a plateau in performance throughout repeated training. More recently, brain imaging studies have implicated frontal-striatal brain circuits in skill learning. However, it is largely unknown whether frontal-striatal activation during skill learning and behavioral changes follow a similar learning curve pattern. To address this gap in knowledge, we performed a longitudinal brain imaging study using a procedural working memory (pWM) task with repeated measurements across two weeks to map the temporal dynamics of skill learning. We additionally explored the effect of the BDNF Val66Met polymorphism, a common genetic polymorphism impacting neural plasticity, to further inform the relevance of the identified neural markers. We used linear and exponential modeling to characterize procedural learning by means of learning curves on the behavioral and brain functional level. We show that repeated training led to an exponential decay in a distributed set of brain regions including fronto-striatal circuits, which paralleled the exponential improvement in task performance. In addition, we show that both behavioral and neurofunctional readouts were sensitive to the BDNF Val66Met polymorphism, suggesting less efficient learning in 66Met-allele carriers along with protracted signal decay in frontal and striatal brain regions. Our results extend existing literature by showing the temporal relationship between procedural learning and frontal-striatal brain function and suggest a role of BDNF in mediating neural plasticity for establishing automatized behavior. [ABSTRACT FROM AUTHOR]

Summary: Optimizing node deployment in the underwater Internet of Things (UIoT) poses significant challenges due to the complex and dynamic nature of underwater environments. This research introduces the adaptive long short‐term memory‐based egret swarm optimization algorithm (ALSTM‐ESOA), a novel approach designed to enhance network coverage and performance efficiently. Unlike traditional methods, ALSTM‐ESOA incorporates cognitive learning capabilities from long short‐term memory (LSTM) and dynamic adaptation strategies inspired by the hunting behaviors of egrets. The algorithm's effectiveness was tested through extensive simulations in MATLAB, demonstrating notable improvements over existing models: network throughput increased by up to 55.56%, deployment time decreased by 88.89%, and energy efficiency improved significantly. These enhancements are critical for robust, real‐time data collection and monitoring in underwater settings, providing substantial benefits for marine research and resource management. The findings suggest that ALSTM‐ESOA significantly outperforms conventional algorithms, offering a promising new tool for the advancement of UIoT applications. After being implemented in MATLAB, the suggested ALSTM‐ESOA model for the node deployment optimization in UIoT is examined. The proposed ALSTM‐ESOA in terms of network throughput is 55.56%, 38.89%, 36.11%, and 11.11% better than CNN, LSTM, ARO‐RTP, and IGOR‐TSA, respectively. Similarly, the proposed ALSTM‐ESOA with respect to deployment time is 88.89%, 81.82%, 75%, and 50% better than CNN, LSTM, ARO‐RTP, and IGOR‐TSA, respectively. For the purpose of exploring marine resources, monitoring underwater environments, and conducting marine scientific investigation, the research's findings are extremely valuable. [ABSTRACT FROM AUTHOR]

This article focuses on underachievement among disadvantaged pupils in Dutch primary education. Underachievement is defined as the discrepancy between cognitive ability and school performance. Based on data from the Netherlands Cohort Study on Education (NCO), enriched with individual information on cognitive learning potential and achievement test scores in reading comprehension, spelling and arithmetic-mathematics, we investigated to what extent underachievement is more likely to be identified among pupils with low-educated parents, those with a non-Western migration background and boys. The empirical analysis concerns 3,402 fourth grade pupils of school year 2020-2021. The results show considerable numbers of underachievers. Underachievement is mainly found among pupils from disadvantaged backgrounds. In particular, pupils with low- and intermediate-educated parents are identified as underachievers in all three domains. [ABSTRACT FROM AUTHOR]

While the COVID-19 pandemic made the use of video conferencing software a common part of online teaching, little research has explored how to optimize the use of such technologies. This study set out to understand how instructors' choice of professional vs. personal virtual backgrounds may affect students' cognitive learning and instructor's credibility. An online experiment was conducted using a 3 (virtual background: Beach, Architecture, and University) x 2 (student gender: male and female) between-subjects design. The data collected from undergraduate students (n = 466) through an online experiment indicate that female students assess the instructor as credible and have consistent perceived cognitive learning across virtual backgrounds. However, male students experience less perceived cognitive learning or rate the professor as less trustworthy and caring when personal virtual backgrounds are used. [ABSTRACT FROM AUTHOR]