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Purpose: Constraint-induced movement therapy (CIMT) is an evidence-based intervention for arm recovery after acquired brain injury. Clinician knowledge, time and confidence in delivering CIMT are established barriers to the routine use of CIMT in practice. CIMT delivery via telehealth is one option to help overcome these barriers. This study aimed to understand clinician experiences of using an educational website and if the education and online resources contributed to their self-reported use of constraint-induced movement therapy via telehealth (TeleCIMT) in practice. Materials and Methods: Data were collected from a purposive sample of therapists registered to use the TeleCIMT website and website analytics. An online survey explored participants' experience with CIMT delivery (both face to face and via telehealth), their perceptions of the website, and barriers and enablers to TeleCIMT implementation using the Capability, Opportunity, Motivation—Behaviour model. Website analytics were used to evaluate website traffic and resource use. Data were analysed using descriptive statistics (quantitative data) and content analysis (qualitative data). Results: Forty therapists responded to the survey; 72.5% (n = 29) of the respondents were occupational therapists, and 37.5% (n = 15) had delivered TeleCIMT. Most of the participants agreed that the website was easy to navigate (n = 26, 90%) and felt that they had the knowledge (n = 28, 96.6%) and skills (n = 24, 82.7%) to deliver TeleCIMT. The enablers to TeleCIMT included motivation to implement learnings from the website, confidence in delivering the programme, and the convenience of remote delivery. The perceived barriers to TeleCIMT use included limited access to technology and the availability of a client supporter to enable engagement in TeleCIMT. The resources used most frequently by the respondents were the participant preparation pack and participant programme pack. Shorter video learning modules (<11 min in duration) had greater engagement than longer video learning modules. Conclusions: Whilst online education and resources may enhance clinician knowledge of constraint-induced movement therapy and telehealth delivery, other barriers such as lack of technology access, may need to be addressed through additional learning and implementation strategies to support the routine use of TeleCIMT in practice. [ABSTRACT FROM AUTHOR]

Introduction: Massive Open Online Courses (MOOCs) are an agile context for workplace training, which can provide physicians with needed knowledge and skills related to their clinical practice. From an organisational standpoint, their effectiveness can be assessed on physicians' intention to transfer what they learn through them in the workplace. Despite the Theory of Planned Behaviour (TPB) standing among the more solid models in explaining individuals' behavioural intention, its adoption in investigating the training transfer process among physicians is notably underdeveloped, limiting its contribution to enhancing the transfer rates of MOOCs content. Method: Based on such a consideration, the present study adopted an extended TPB model to investigate the potential psychosocial factors affecting the intention to transfer knowledge and skills learned through MOOCs in the workplace among 217 Italian physicians who completed an online self-report questionnaire. Results: Hierarchical regression analyses were performed, showing that among the TPB variables, perceived behavioural control and attitude significantly predicted transfer intention. The inclusion of training satisfaction and job autonomy in the model significantly increased the explained variance in intention. Conclusions: These findings have valuable implications for human resource development (HRD) in healthcare as they suggest the need to design MOOCs based on a flexible competency model in order to promote physicians' engagement and commitment to adopting new knowledge and skills. Finally, interventions aimed at recognising physicians' efforts in transferring learned content as well as empowering their ability to shape how they perform their professional duties could further enhance the impact of workplace training. [ABSTRACT FROM AUTHOR]

Traditional In-Person Semester-Length (IP-SL) courses often struggle with inherent time constraints, lack of flexibility, and geographic limitations, delaying effective learning and accessibility for students. Moreover, the extended duration of the Semester-Length (SL) structure reduce focus due to engagement with multiple subjects simultaneously, increased stress, and limited timely feedback and assessment. This study evaluates the Online Real-Time Block Model (ORT-BM), an intensive online model, highlighting its potential to enhance engagement, satisfaction, and inclusivity in project-based programs like construction in higher education. Building surveying as a critical field in construction is selected as the case study since professional surveyors must stay current with rapidly evolving building codes, regulations, and sustainability practices. However, the rigid structure of IP-SL courses often leaves graduates less prepared to meet industry needs. Conducting a comparative analysis of a case study, the Bachelor of Building Surveying program (NBBS) at Victoria University, the research compares three teaching models: IP-SL (2016–2018), In-Person Block Model (IP-BM, 2019–2020), and ORT-BM (2020–2023) using Student Evaluation of Units (SEU) data and Quality Indicators for Learning and Teaching (QILT) metrics. Findings, derived from SEU and QILT, reveal that ORT-BM improves student satisfaction, accelerates course completion rates, and fosters gender equity through inclusive learning environments while enhancing accessibility for geographically dispersed and disadvantaged students. By integrating advanced digital tools like virtual site visits, ORT-BM enhances professional readiness, aligning education with evolving industry standards. Future research may explore developing hybrid models to optimize cognitive load further, improve accessibility, and enhance flexibility. [ABSTRACT FROM AUTHOR]

Knowledge tracing (KT) aims to understand the evolution of students' knowledge states during learning using machine learning techniques. While KT has made significant strides with deep learning techniques, a gap remains reflecting students' actual knowledge level—the significant effects of students' learning behaviors and abilities are omitted, which can reflect their knowledge acquisition more deeply and ensure the reliability of the response. This paper introduces the Enhanced Learning Behaviors and Ability Knowledge Tracing model (LBAKT), addressing this gap by incorporating both learning behavior and ability into its framework. The LBAKT model is structured into four layers: embedding, learning, forgetting, and predicting. The embedding layer enriches exercise information through an exercise embedding unit (capturing knowledge skills, exercises, and difficulty) and a learning ability embedding unit (considering answer time, answers, and hint times), forming a fundamental learning embedding. The learning layer quantifies learning gain by analyzing differences between current and previous learning embedding, interval times, and relative knowledge states, employing a learning gate to assess students' capacity to absorb knowledge. The forgetting layer models forgetting behavior with forgotten erasing and retention functions, based on previous knowledge states, current learning gains, and interval times. Experimental results demonstrate that LBAKT outperforms existing models in terms of Area Under the Curve (AUC) and Accuracy (ACC) metrics when predicting students' knowledge states. Specifically, on the longer sequence datasets ASSIST2012 and ASSISTChall, LBAKT achieved an AUC that is 8.8% higher than that of the worst-performing model, demonstrating superior performance. However, the model's performance on the shorter sequence Algebra0607 was less satisfactory, with an AUC 3.16% lower and an ACC 5.0% lower than that of the top-performing model. Furthermore, our model enhances interpretability by integrating learning behavior and ability, a crucial factor for a deeper understanding of how students acquire and retain knowledge over time. [ABSTRACT FROM AUTHOR]

The recent advancements in large language models (LLMs) have brought significant changes to the field of education, particularly in the generation and evaluation of feedback. LLMs are transforming education by streamlining tasks like content creation, feedback generation, and assessment, reducing teachers' workload and improving online education efficiency. This study aimed to verify the consistency and reliability of LLMs as evaluators by conducting automated evaluations using various LLMs based on five educational evaluation criteria. The analysis revealed that while LLMs were capable of performing consistent evaluations under certain conditions, a lack of consistency was observed both among evaluators and across models for other criteria. Notably, low agreement among human evaluators correlated with reduced reliability in LLM evaluations. Furthermore, variations in evaluation results were influenced by factors such as prompt strategies and model architecture, highlighting the complexity of achieving reliable assessments using LLMs. These findings suggest that while LLMs have the potential to transform educational systems, careful selection and combination of models are essential to improve their consistency and align their performance with human evaluators in educational settings. [ABSTRACT FROM AUTHOR]

Online learning is a framework for processing and learning from sequential data in real time, offering benefits such as promptness and low memory usage. However, it faces critical challenges, including concept drift, where data distributions evolve over time, and class imbalance, which significantly hinders the accurate classification of minority classes. Addressing these issues simultaneously remains a challenging research problem. This study introduces a novel algorithm that integrates adaptive weighted kernel density estimation (awKDE) and a conscious biasing mechanism to efficiently manage memory, while enhancing the classification performance. The proposed method dynamically detects the minority class and employs a biasing strategy to prioritize its representation during training. By generating synthetic minority samples using awKDE, the algorithm adaptively balances class distributions, ensuring robustness in evolving environments. Experimental evaluations across synthetic and real-world datasets demonstrated that the proposed method achieved up to a 13.3 times improvement in classification performance over established oversampling methods and up to a 1.66 times better performance over adaptive rebalancing approaches, while requiring significantly less memory. These results underscore the method's scalability and practicality for real-time online learning applications. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has caused major changes in pedagogical practices worldwide. As COVID-19 cases increased, universities had to move their teaching online, requiring both instructors and students to engage through online learning platforms. This study explored the effects of students' online learning readiness and online self-regulated English learning on their satisfaction with the online English learning experience. Additionally, it investigated whether and how online learning readiness and online self-regulated English learning influenced students' perceived English self-efficacy which could in turn influence their satisfaction with the online English learning experience. Data were collected from 163 university students in Macau, China. The results of partial least squares structural equation modeling showed that students' online learning readiness significantly influenced their satisfaction with the online English learning experience directly and indirectly through online self-regulated English learning. Furthermore, online learning readiness affected students' perceived English self-efficacy. However, online self-regulated English learning did not significantly impact students' perceived English self-efficacy, and there was no significant link between students' perceived English self-efficacy and their satisfaction with the online English learning experience. The implications of this study are given. [ABSTRACT FROM AUTHOR]

As online learning platforms become prevalent, online learning has been an important way for college students. Online learning engagement, as an evaluation of online learning quality, is crucial for enhancing learning quality and promoting higher education by investigating college students' engagement and its influencing factors in the online learning environment. This paper aims to identify key factors affecting college students' online learning behavioral engagement. Based on a literature review, the Delphi expert consultation method was used to build an assessment framework covering five dimensions (participation, concentration, interaction, challenge, and self-monitoring) with sixteen specific indicators. The Analytic Hierarchy Process (AHP) determined the weights of these factors. Then, data from 63 students using the "Ketangpai" online learning platform were collected and analyzed to explore the correlation and predictive relationships between online learning behavior indicators and academic achievements. The results showed a strong correlation between the frequency of accessing online learning resources and long-term online learning and academic performance, and a prediction model was established. The framework offers theoretical and methodological insights for designing online learning activities and evaluating learning quality. It supports intervening in and assessing college students' online learning processes and improving learning quality. Also, exploring the relationship helps educators formulate personalized online teaching strategies, improving online education effectiveness and students' learning experiences. [ABSTRACT FROM AUTHOR]

This study investigates the impact and mechanisms of achievement goal orientation on online learning engagement among undergraduates, using a sample of 461 students enrolled in online courses from four universities of varying levels in Shanghai, China. Self-efficacy is introduced as a mediating variable, and structural equation modeling is employed to assess the effects. The findings reveal that different types of achievement goals have varying natures and intensities in their associations with undergraduate online learning engagement. Self-efficacy partially mediates the effect of mastery-approach goals on online learning engagement, but does not mediate the effects of mastery-avoidance, performance-approach, or performance-avoidance goals. The study recommends leveraging the guiding role of mastery-approach achievement goals to help students set scientific and reasonable goals, and stimulating students' self-efficacy through the dual influences of external support and internal motivation. With the support of these strategies, significant improvements in undergraduate online learning engagement can be achieved. [ABSTRACT FROM AUTHOR]

In the present study, a short instrument (eight-item self-report, five-point Likert scales) was developed and validated to assess self-perceived mental health problems in online learning. The participants were 398 Romanian university students from nine different faculties. The factor structure of the scale was assessed using Exploratory Factor Analysis (Principal Axis Factoring extraction method) and Confirmatory Factor Analysis. The high goodness-of-fit indices validated a second-order factor model of mental health problems, with two distinct but correlated sub-constructs, psychological distress, and online academic difficulties, integrated under a single higher-level factor. Psychological distress comprises indicators such as anxiety and stress, while online academic difficulties contain, for instance, indicators such as decreased performance, fatigue or lack of motivation. The results of applying multiple assessment criteria showed good reliability (e.g., McDonald's omega), as well as convergent validity (e.g., Average Variance Extracted) and discriminant validity (e.g., the heterotrait–monotrait ratio of correlations) of the scale. Also, correlations analysis between mental health problems occurred in online learning context and other measures indicated a strong negative relation with online course satisfaction and weak negative relations with subjective academic performance, perceived social competence, and perceived digital competence. In conclusion, the scale appears to be a valid instrument for measuring some negative mental health outcomes in online learning, perceived by university students. The implications of the results and limitations of this study are also discussed. In conclusion, the scale has multiple possible applications, the most important being (1) the assessment of mental health problems both in ordinary online learning situations and in emergency ones, which would allow the early detection of these issues, (2) the possibility of assessing relations between the sub-constructs of the scale and other psychological constructs of interest in scientific research, and (3) the feedback for teaching staff involved in the online learning system. [ABSTRACT FROM AUTHOR]

The document discusses the increasing importance of vocational education in global education systems, focusing on China, the United States, and Germany as examples. It emphasizes the need for vocational education to adapt to technological advancements and societal needs, highlighting the role of vocational education in skill formation and social development. The text also addresses challenges faced by vocational education, such as social biases and lack of recognition, while exploring opportunities for innovation and policy support to enhance the sector's development. [Extracted from the article]

Multiselfing is a form of musicianship where one person digitally clones themself into several single selves, creating layers and a musical collective that would otherwise be impossible without the mediation of technology. There are various kinds of multiselfers. This article categorizes them as the following: singers, instrumentalists, loopers, live performers, and hybrids. While these five categories are presented distinctly here, they may often overlap. This article explores the notion of multiselfing and its implicit potential when situated in music education to develop comprehensive music skills. Comprehensive musicianship is important because it enables students to grow in broad musical knowledge and skills at all levels of instruction by synthesizing the musical materials they are working with and by making conceptual connections through performance, analysis, and composition. In addition to including many examples, this article also includes lists of resources and applications to help schoolteachers better understand how to integrate multiselfing into their pedagogic practices. [ABSTRACT FROM AUTHOR]

Effective communication between students and instructors is vital for student success. Traditionally, this communication has taken place in person within classroom settings. However, with technological advancements, online classes have become more common. The COVID-19 pandemic accelerated this shift, significantly disrupting traditional communication methods between students and instructors and transforming the educational landscape, particularly in higher education. We conducted a qualitative narrative literature review of the technological tools that emerged during the pandemic and explored how today's instructors can effectively use them to enhance student engagement and motivation in online classrooms. The review utilized the SANRA (scale for the assessment of narrative reviews) guidelines to ensure the quality of the studies used. Twenty-two articles published within the last ten years were chosen based on their relevance to higher education and student–instructor communication. The articles were analyzed for effective and ineffective educational communication tools (e.g., Zoom or Google Classroom) utilized during the pandemic, focusing on what worked and what could be improved. The findings revealed that live video sessions were more effective than pre-recorded videos, voice-only sessions, or email/text communications in fostering student engagement and motivation. [ABSTRACT FROM AUTHOR]

This study explores the practices of distributed teaching presence (DTP) to promote students' shared metacognitive responsibilities in online learning. The DTP practices included providing explicit instruction on DTP techniques and guiding students to label their cognitive presence in online discussion. Data were collected through asynchronous online discussion and a questionnaire survey from 53 students enrolled in a graduate-level course at a northeastern private university in the United States. By analyzing the discussion transcripts, students' cognitive and teaching presences were examined to reveal the influence of the interventions on students' learning engagement. Both qualitative and quantitative analysis were conducted to analyze the 2557 messages created by 53 students. The results showed that guiding students to use DTP techniques credibly improved students' teaching and cognitive presence. We also found that students' teaching presence behaviors were positively associated with peers' cognitive presence and their own higher-level learning. The implications for research and practices in designing and facilitating shared metacognitive learning experience are also discussed. [ABSTRACT FROM AUTHOR]

Background/Objectives: The Fukushima Daiichi Nuclear Power Station accident underscored the critical role of public health nurses (PHNs) in managing evacuees during nuclear emergencies. Despite their importance, PHNs often lack sufficient knowledge and experience, which may make them anxious about this role. This study aimed to investigate the factors associated with PHNs' anxiety about accepting evacuees and identify strategies to alleviate this anxiety. Methods: A cross-sectional survey was conducted among 100 PHNs working in Oita Prefecture, Japan, a region designated to receive evacuees in the event of a nuclear disaster. Data were collected via an online questionnaire assessing radiation knowledge, workplace characteristics, and anxiety about accepting evacuees. Univariate and multivariate logistic regression analyses were performed to identify the predictors of anxiety. Results: PHNs working in prefectural offices were 3.4 times more likely to feel anxious about accepting evacuees than those in municipal offices (OR = 3.488, 95% CI = 1.236–10.963, p = 0.023). Awareness of evacuation site responsibilities significantly reduced anxiety (OR = 0.412, 95% CI = 0.134–1.211, p = 0.110). Overall, knowledge of radiation was low, with only 8% correctly identifying the differences between stochastic and deterministic effects. Online training was the preferred format for education. Conclusions: Workplace characteristics and knowledge of evacuation responsibilities significantly influence PHNs' anxiety levels. Addressing knowledge gaps through tailored, accessible training programs, particularly in online formats, is essential. Strengthening preparedness among PHNs could enhance their confidence and ability to manage evacuees effectively during nuclear disasters. [ABSTRACT FROM AUTHOR]

Background/Objectives: High levels of emotional intelligence (EI) and resilience in primary care physicians (PCPs) can help them communicate better with patients, build stronger relationships with colleagues, and foster a positive and collaborative workplace. However, studies have indicated that primary care physicians (PCPs) often do not focus enough on developing these skills. Consequently, the purpose of this mixed methods study was to evaluate the effectiveness of an experiential online training (EOT) intervention in enhancing the EI and resilience of PCPs who treat patients with chronic respiratory diseases (CRDs). Methods: A total of 46 PCPs from Greece participated in a 25-hour EOT program, which focused on counseling skills for lifestyle change and breathing techniques for self-regulation. Quantitative data were collected using the Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF) and the Connor–Davidson Resilience Scale (CD-RISC-25) before, immediately after, and three months post-intervention. Additionally, qualitative data were obtained through written reflections from participants regarding their clinical practice. Results: The results revealed significant improvements in EI and resilience scores immediately after the intervention (ΕΙ: 5.13, SD: 0.65 vs. 5.3, SD: 0.57, p = 0.007; resilience: 76.6, SD: 11.75 vs. 79.83, SD: 10.24, p = 0.029), as well as at the three-month follow-up (ΕΙ: 5.3, SD: 0.57 vs. 5.36, SD: 0.48, p = 0.007; resilience: 79.83, SD: 10.24 vs. 81.03, SD: 7.86, p = 0.029). The thematic analysis of qualitative data identified improvements in five key themes: communication skills, stress management, emotional awareness, resilience, and patient care. Participants reported feeling more confident, empathetic, and effective when interacting with patients, particularly those from diverse backgrounds. The convergence of the quantitative and qualitative findings showed the efficacy of the EOT intervention in enhancing PCPs' EI, resilience, well-being, and, ultimately, their practice. Conclusions: These findings underscore the importance of integrating EI and resilience training into medical education and professional development programs. Such initiatives could effectively support the emotional and psychological needs of PCPs and potentially contribute to an improved quality of care for patients with CRDs. [ABSTRACT FROM AUTHOR]

The demand for flexible automation in manufacturing has increased, incorporating vision-guided systems for object grasping. However, a key challenge is in-hand error, where discrepancies between the actual and estimated positions of an object in the robot's gripper impact not only the grasp but also subsequent assembly stages. Corrective strategies used to compensate for misalignment can increase cycle times or rely on pre-labeled datasets, offline training, and validation processes, delaying deployment and limiting adaptability in dynamic industrial environments. Our main contribution is an online self-supervised learning method that automates data collection, training, and evaluation in real time, eliminating the need for offline processes. Building on this, our system collects real-time data during each assembly cycle, using corrective strategies to adjust the data and autonomously labeling them via a self-supervised approach. It then builds and evaluates multiple regression models through an auto machine learning implementation. The system selects the best-performing model to correct the misalignment and dynamically chooses between corrective strategies and the learned model, optimizing the cycle times and improving the performance during the cycle, without halting the production process. Our experiments show a significant reduction in the cycle time while maintaining the performance. [ABSTRACT FROM AUTHOR]

Worldwide, social work educators' teaching and learning practices are founded on social justice principles and recognised for their evidence-based, interpersonal, cross-cultural, and problem-solving approaches. Placements are integral to social work education preparing students for practice. Learning experienced on such placements, particularly those involving research, can assist students to develop a broad understanding of diversity, inequality, and anti-oppressive practice in local, national, or international contexts. Technology-enhanced, online research opportunities have revolutionised research placements. This article offers a reflective dialogue on the insights gained from two transnational, technology-enhanced social work research-based placements. The first example reviews three student-led, rural-focused inquiries completed in Australia and Ireland; the second pertains to students physically situated in Ireland and who engaged in collaborative online projects while completing their USA-based social work placements online. The authors reflect on the experiences and the skills the students developed and how the application of technology helped meet an increasing need for environmentally sustainable practices in teaching, learning, and research on placement. Publicly available student reflections on significant knowledge and practice benefits gained from their transnational experiences are considered. The study highlights how reflective practice assisted in the enactment of research in online contexts. [ABSTRACT FROM AUTHOR]

Teaching that centers holistic understandings of humans and the natural environment is relatively new in Australian social work education. This position is purposefully embraced to embed ecological justice as a key consideration in day-to-day practice. Alongside the growing professional awareness of ecological concerns and emerging commitment to ecosocial work practice, field education is evolving and allowing students to engage in remote digitally facilitated field placements. This provides new opportunities for creatively embedding ecological learning and ecosocial work practices into student field education thus promoting incorporation of these into the students' emerging professional practice frameworks. This descriptive article examines the structure and pedagogical approach used in a series of such placements provided in partnership with environmental not-for-profit organizations. These digitally facilitated field education experiences can provide a powerful mechanism for transformational ecosocial learning, particularly when underpinned by Freirean ecopedagogy which resonates with social work's professional values and purpose. Additionally, there is opportunity for mutual benefit when these placements are hosted by environmental not-for-profit organizations. [ABSTRACT FROM AUTHOR]

Automated Compliance Checking (ACC) has emerged as a critical tool for enforcing legal regulations across various domains. This paper contributes to ongoing research in Semantic Web technologies, particularly focusing on the execution of SHACL-SPARQL rules on RDF data. The RDF, being one of the most widely used knowledge representation (KR) formats, serves as the foundation of our approach, ensuring compatibility with existing standards and enhancing interoperability. Our research enhances the aggregate and temporal aspects of ACC by addressing the limitations of traditional ACC methodologies, which often fall short in managing the nuanced temporal and aggregate requirements essential for legal reasoning. Through a case study analysis of selected regulations with aggregate and temporal facets in LI 2204, which regulates local content and participation in Ghana's upstream petroleum industry, this paper demonstrates the effectiveness of the proposed solution in achieving these dimensions of ACC. The findings underscore the potential of Semantic Web technologies to transform ACC practices by moving towards standardized, interoperable solutions. All source codes are freely available online together with instructions to locally reproduce the simulations. [ABSTRACT FROM AUTHOR]

Background: The purpose of this study was to compare the opinions of biomedical students from Russia and Central Serbia about learning methods in the time of the COVID-19 pandemic. Methods: This is a comparative questionnaire study that used the validated questionnaire tool eMedQ, conducted via the online platform Anketolog.ru from February to May 2022 at Sechenov University and the University of Kragujevac in the same period. At Sechenov University, 694 students took part in the survey, while at the University of Kragujevac, the total number of participants was 209. The eMedQ questionnaire, in Russian and Serbian, consists of 45 closed-ended questions with 7 domains: demographic characteristics, experience with online teaching, education process (teaching organization), aspects of mental functioning, clinical skills, technical aspects, and quality of life. Results: During the COVID-19 lockdown, in Serbian and Russian biomedical faculties, we observed the high flexibility of Russian students with greater experience when it comes to online education before the pandemic compared to students from Serbia. Also, the Russian students declared that they were strongly motivated to achieve clinical skills and to learn, while a larger number of Serbian students reported disrupted mental functioning and learning problems. Conclusions: At the time of isolation, at Serbian and Russian biomedical faculties, we noticed the higher flexibility of Russian students with more experience than students from Serbia. Also, the Russian students declared that they were strongly motivated both to acquire clinical skills and to learn, while a larger number of Serbian students reported reduced mental functioning and learning problems. [ABSTRACT FROM AUTHOR]

There is an ongoing debate in the halls of traditional universities about the effectiveness of course delivery modes other than face-to-face instruction. This paper reports on a natural experiment that we were able to conduct in Spring 2022 as we offered the same course to similar student populations in three different delivery modes (face-to-face, synchronously online via Teams, and asynchronously online). While about a quarter of the students who responded to a survey about their preferred delivery mode who were not enrolled in a face-to-face class indicated that they preferred a face-to-face class, the experiment did not find any differences between the three groups in terms of their assessment of teaching or in their performance both in the course overall or in the individual assignments in the course. While the experiment may suffer some shortcomings, the results indicate that a well-designed online course, delivered synchronously or asynchronously, may encourage student learning more effectively than a face-to-face course. [ABSTRACT FROM AUTHOR]

Adolescence is a developmental period of significant change and increasing independence, during which parents and caregivers play a critical role guiding their teen toward adulthood. Parents of adolescents with disability face heightened challenges managing their teens' growing independence and shift to adult-based services across health, recreation, and employment. Using a mixed-methods-treatment-group-only design, this study explored the implementation and outcomes of a program designed to build parenting capacity to support their adolescent with disability. Parents enrolled in one of ten groups were invited to attend three sessions covering content tailored to adolescent development including post-school opportunities, financial support, risk-taking and decision-making, future planning, relationships, and mental health. Surveys were administered pre-program, post-program, and six months after program participation (n = 160) to measure intervention outcomes including parenting self-efficacy, self-advocacy, adolescent self-advocacy, parent confidence to support their adolescent's growing independence, confidence to support their adolescent through sensitive developmental stages, parental hopes and aspirations, and parental empowerment. A subset of parents (n = 11) also participated in semi-structured interviews about the program's acceptability and usefulness, and their satisfaction with the program content and delivery. All outcome variables except parent hopes and aspirations increased significantly from pre- to post-program. Parent self-efficacy, self-advocacy, and parental empowerment remained higher 6 months after program completion. Thematic analysis identified program strengths as the co-facilitation model of program delivery, practical and actionable content, the use of narratives and the facilitator's lived experience as parents of adolescents with disability, the use of visualizations (video, pictures, diagrams), and the service provider's trusted reputation and credibility. In conclusion, an online co-facilitated group program for parents of adolescents with disability can contribute to positive change for families by improving parent confidence, self-advocacy, and parental empowerment. [ABSTRACT FROM AUTHOR]

This study analyzes the impact of interactive technologies on the motivation and engagement of university students in online courses. Through a systematic literature review and a comparative analysis of existing technologies, 64 articles published between 2020 and 2024 were examined. The results reveal a significant increase in student motivation (23%) and knowledge retention (31%) with the use of these tools. Augmented reality stands out with a mean effect size of 0.67 on academic performance. The bibliometric analysis shows a concentration of research in countries such as Spain, Colombia and China, suggesting the need for more diverse studies. Challenges such as the digital divide and lack of teacher training were identified, with 42% of teachers reporting difficulties in implementation. The findings underline the transformative potential of interactive technologies in online higher education, but emphasize the importance of a holistic approach that considers technical, pedagogical and socioeconomic aspects. It is recommended to invest in teacher professional development, promote equitable access policies and encourage research in diverse educational contexts to maximize the benefits of these technologies. [ABSTRACT FROM AUTHOR]

Synchronous Online Teaching (SOT) is becoming increasingly popular, but research shows many teachers are inadequately prepared, calling for greater investment in professional development (PD). Additionally, there is a significant gap in research systematically describing the design of evidence-based PD initiatives. Consequently, researchers and educators lack an understanding of the essential components of these interventions, which obstructs the replication, dissemination, and implementation of evidence-based PD programs for synchronous online teachers. This study presents the design of SOL-lab, an online PD program aimed at fostering teachers' technical and social SOT competences. A detailed overview of the online PD design is offered, encompassing the underlying theoretical and empirical foundations, macro-level design principles, and micro-level instructional and learning activities. More particularly, three key design principles guided the online PD development process: focused observation of SOT, providing and receiving feedback, and stimulating the transfer of learning. By integrating authentic learning experiences and fostering reflective practice, our program aims to empower teachers with the necessary competences to thrive in SOT environments. An analysis of teachers' perceptions indicates that they had a positive experience with the effective features of the PD program. This study offers valuable insights for the development of effective online PD initiatives for SOT. [ABSTRACT FROM AUTHOR]

The use of digital audio-based learning applications in classrooms is increasing. Thus, instructional technology professionals need to become more skilled in designing and developing these apps. To succeed in the future learning process, students studying instructional technology need to have mastered these skills. This study aims to examine the impact of a specialized platform proposed to cultivate students' skills in easily designing and producing online educational talking books (online ETBs). To improve the target abilities, we developed a new specialized platform as a web-based system for this investigation that includes several innovative tools and special learning content. The research design used was quasi-experimental. Thirty-two undergraduate students majoring in instructional technology who were in the third grade examined the proposed platform. With the pre-and post-test design, all participants were placed into one group. Three online instruments were used to gather the data: a performance observation card; a product evaluation card; and a usability questionnaire. According to the results, the suggested platform considerably increased the practical skills required to design and create an online ETB. Additionally, the proposed platform positively impacted the production of online ETB products with an acceptable proficiency level across various educational subjects. The customized platform has also proven to be a comfortable learning environment for the participating instructional technology students. This platform may be utilized as an ICT teaching tool to enhance instructional technology departments as it is appropriate for constructing online ETBs in various educational areas without coding barriers. [ABSTRACT FROM AUTHOR]

Digital competencies are critical to success in higher education, and yet these skills are often not explicitly taught to students. We have previously designed and evaluated a university-wide digital skills programme using quantitative methods. In the current study, we aim to better understand the student experience of this programme by conducting semi-structured interviews with those completing the programme. Twelve students were interviewed, and data were thematically analysed to reveal five themes. Firstly, students defined digital competencies in line with tridimensional models but also noted that these competencies were deployed in a goal-directed fashion. Secondly, prior learning was explored, with some students noting they had received training as part of specific qualifications at school but many relying on self and peer-teaching. This fed into the third theme, which related to motivations for training in which students noted the appeal of a comprehensive programme with certification on completion but also a need to address their lack of skills or confidence and maximise their university experience. The fourth theme revealed that the student learning journey through the programme varied considerably. Online learning was perceived as having strengths and weaknesses and whilst the diversity of resources was welcomed, pacing was mixed. Finally, the data demonstrated training was impactful, both in terms of teaching and learning and the wider student experience, allowing students to be more digitally aware and proficient in all areas of digital competency. The findings of the current study indicate that there is value in offering university-wide digital skills training. [ABSTRACT FROM AUTHOR]

ICT has opened opportunities for innovations in pedagogical approaches. Online learning is increasingly becoming popular in education and attractive because of the diverse benefits not only to educators and students but also to institutions. However, there is a continuous rise in debates on teacher educators competence in adopting online learning. Critics of online learning argue that using ICT to transform face-to-face courses into online courses brings issues, especially to some educators. This study aimed to investigate teacher educators experiences using ICT to transform and manage a virtual face-to-face course during and after the COVID-19 pandemic. A qualitative technique with semi-structured interviews was used to collect data from six college education teachers in Ghana who had taught the same courses between the 2020 and 2022 academic years. The findings showed that ICT integration has easily facilitated online learning and positively impacted teacher educators classroom practices. However, due to insufficient technical and infrastructural support from institutions and socio-cultural perspectives, educators exhibit low competence in managing their teaching and learning activities on time. This study's results provide policymakers with unique insights for a better, sustainable, and equitable ICT integration in Ghana's teacher education. [ABSTRACT FROM AUTHOR]

This study evaluated the impact of a voluntary international online course in industrial design, which applied a Project-Based Learning approach, on the acquisition of competencies among second-year students in the Robotic Engineering program at the University of Alicante (UA). The course, which included participants from two other European universities, aimed to enhance both generic and specific competencies. This study measured the acquisition of nine generic and four specific competencies through two types of analysis: qualitative and quantitative. The qualitative analysis involved a survey assessing students' self-perceived competency gains, while the quantitative analysis consisted of a written objective test that evaluated the acquisition of specific competencies. The results were compared between 43 students who did not participate in the course and 22 who did. The survey responses indicated that, for 10 out of 13 competencies, students reported an improvement in skills as a result of the course. Additionally, the average test score for participants was 77.2%, significantly higher than the 37.7% score for non-participants. These findings suggest a strong correlation between course participation and competency development, highlighting the potential benefits of international online courses in enhancing student learning outcomes in robotic engineering. [ABSTRACT FROM AUTHOR]

(1) Background: General nutrition knowledge is a fundamental pillar of well-being and healthy lifestyles. This study aimed to measure the general nutrition knowledge questionnaire (GNKQ) scores of overweight and obese participants who joined a pilot randomized controlled trial (RCT) and the association between changes in GNKQ scores and changes in anthropometric measures. (2) Methods: A total of 30 and 25 participants had completed the trial at the 3- and 6-month visits, respectively. All participants enrolled in a randomized controlled trial (RCT) and received a hypocaloric-tailored diet and three online nutrition education sessions over 6 months. The participants were randomly divided into two groups: an intervention group supported with weekly telemonitoring and monthly telehealth coaching vs. a control group. The Arabic-validated GNKQ was used, covering four sections: dietary recommendations; food groups and nutrient sources; healthy food choices; and associations between the diet–disease relationship and weight. (3) Results: The findings show that both the intervention and control groups showed improvements in GNKQ scores over time, with the intervention group demonstrating significant increases in overall nutrition knowledge and specific areas, such as the diet–disease relationship and weight management, at 3 months. In addition, changes in GNKQ scores had a significant negative association with BMI and visceral fat percentage. The findings underline the benefits of supporting dietary weight loss interventions with telemonitoring and telehealth coaching, suggesting that an increase in nutrition knowledge may relate to lower body fat metrics. Nevertheless, the small sample size and high attrition rate of participants were the main limitations of this study, such that large populations are required to confirm the reliability of the obtained findings. [ABSTRACT FROM AUTHOR]

Digitalization in healthcare education has shifted simulation learning methods to distanced implementations. Successful transition to distance education requires effective communication and the teacher's good ability to use digital learning methods, as well as students' active interaction and motivation throughout the entire educational process. This study explores participants' experiences of online large group simulations as an approach for learning about interprofessional collaboration. A mixed method design was used in this study. Data from health and social care students and qualified professionals were collected using a questionnaire which contained statements presented on a five-point Likert scale and open-ended questions. The questionnaire was filled online by 100 students and professionals. The quantitative data were analyzed using descriptive statistical methods, and the open-ended questions were analyzed with inductive content analysis. As a result, the participants were satisfied with the large group simulation intended for learning interprofessional collaboration (mean = 4.42, SD = 0.759). The majority viewed it as a good learning method (95%) that is suitable for interprofessional collaboration learning (90%) and for promoting working together (82%). Digitally activated communication tools promoted interactive discussion and activated joint learning. However, only one activation tool was preferred instead of using two methods simultaneously. In conclusion, distanced large group simulations were evaluated to be a good method for learning interprofessional collaboration. This study was not registered. [ABSTRACT FROM AUTHOR]

Background/Objectives: In the UK, significant and rising numbers of children arrive in schools with marked deficits in key skills such as oral language. This rise has been further negatively impacted by the COVID-19 pandemic. Given this, the foundation phase of primary school education is a necessary environment for targeting language deficits. There is evidence to suggest that teaching assistant (TA)-led interventions can be effective when adequate training and support are provided. This study explored the feasibility of providing a brief, online dialogic book-sharing training to TAs, and whether this training would be effective in upskilling TAs and enable them to improve the language outcomes of children aged 3–7 years in a school context. Methods: North Wales primary schools were invited to nominate TAs for the two half-day training sessions. Five schools responded, and eleven TA–child dyads participated. Data were collected on recruitment, training acceptability and baseline, and post-training measures from TAs and children (2–3 weeks after the final training session) and 4–6 weeks after the first follow-up. Measures of TA competence and behavior were collected, along with measures of child language and behavior. Results: Schools and TAs were recruited; TAs reported positively to the training, and the results showed small to large effect size benefits on all TA skills and child expressive language with significant positive post-training effects on TAs' use of reflections and child language abilities. However, these effects were somewhat reduced at follow-up. Conclusions: Overall, the results of this feasibility study provide positive evidence for this training as an accessible way for schools to strengthen their prevention infrastructures by professionalizing a growing, but relatively untrained, group within the school workforce. [ABSTRACT FROM AUTHOR]

Background/Objectives: Women's health represents an integral component of public health. With breast cancer being the first worldwide and cervical cancer the fourth most common cancer among women, and while habits of intimate hygiene remain mediocre, it is crucial to address these issues. We aimed to evaluate the efficacy of a community-based intervention on the knowledge and preventive measures (K&P) of women toward breast cancer, cervical cancer, and intimate hygiene. Methods: This longitudinal multicentric prospective interventional study was conducted on women residing in Lebanon aged 18–83 years old. The awareness sessions took place either in person or online to address these three topics, covering the eight governorates of Lebanon. Our sample included women both from the general population and from Order of Malta Lebanon (OML)'s centers and mobile medical units. A stratified randomized sampling method was implemented using age and governorates. Women were interviewed before (pre-test) and after (post-test) the awareness session. The K&P score and the improvement post-intervention were represented in a function of all the study variables. A p ˂ 0.05 was found statistically significant. Results: A total of 657 women, with the majority being nonsmokers and having a bachelor's degree as their highest level of education, completed surveys before and after the intervention, showcasing a significant overall K&P mean score improvement of 50.48% in the pre- vs. post-test (an average score of 22.01 ± 5.95 over 38 (57.93% of correct answers) vs. 33.12 ± 3.41 over 38 (89.58% of correct answers), respectively, p < 0.001). A significant difference was also noted between pre- and post-test (p < 0.001) in each of the three topics individually, with improvements of 52.39% for breast cancer, 60.00% for cervical cancer, and 22.27% for intimate hygiene. Conclusions: National awareness campaigns are key to shedding light on breast and cervical cancer matters and improving women's reproductive health and intimate hygiene in Lebanon. Addressing the knowledge gaps and promoting early screening and healthy habits through national public health policies can empower women to protect their health and well-being. [ABSTRACT FROM AUTHOR]

Inactivity during pregnancy and postpartum is largely a result of women's attitudes and misunderstandings of physical activity, especially in Iran. This scoping review critically assesses the barriers and facilitators influencing physical activity among pregnant and postpartum Iranian women to provide the basis for future physical activity interventions. Ten databases and platforms were searched up to 1 June 2024: Medline, SportDISCUS, PsycINFO, EMBASE, CINAHL, Cochrane Review Database, Clinical Trial, SID, ISC, and Web of Science. Grey literature sources were included to retrieve original publications on barriers and facilitators during pregnancy and postpartum among Iranian women. The search resulted in 2470 identified studies screened for inclusion criteria. After screening both abstracts and full texts, 33 of the studies were included, and data were extracted and charted. Findings were summarized in alignment with the objectives. The results show that the basic physical activity barriers are intrapersonal, interpersonal, and environmental factors. Facilitating factors include using E-learning resources and combined interventions to educate women and provide awareness of the existence of exercise classes. Social and emotional support by family members and other women in the same situation can be effective. Overall, the study of obstacles to and enablers of physical activity during pregnancy and postpartum is ongoing. In addition to highlighting the present situation in Iran, this study identifies further opportunities for future research on the development of appropriate interventions to reduce the barriers and strengthen the facilitators for physical activity among pregnant and postpartum Iranian women with trained groups, including skilled healthcare providers. [ABSTRACT FROM AUTHOR]

In large-scale, distributed high-performance computing systems, the increasing complexity of job scheduling has expanded along with the growth of computational resources and job diversity. While heuristic scheduling strategies with various optimization objectives have shown promising results, their effectiveness is often limited in real-world applications due to the dynamic nature of workloads and system configurations. Deep reinforcement learning (DRL) methods offer the potential to address scheduling challenges. However, their trial-and-error learning approach can lead to suboptimal performance or resource wastage in the early stages. To mitigate these risks, this paper introduces an offline reinforcement learning-based job scheduling method. By training on historical data, the method avoids the pitfalls of deploying immature strategies in live environments. We constructed an offline dataset by combining expert scheduling trajectories with early-stage trial data from online reinforcement learning. This enables the development of more robust scheduling policies. Experimental results demonstrate that, compared to heuristic and online DRL algorithms, the proposed approach achieves more efficient scheduling performance across various workloads and optimization goals, showcasing its practicality and broad applicability. [ABSTRACT FROM AUTHOR]

Temporal difference (TD) learning is a powerful framework for value function approximation in reinforcement learning. However, standard TD methods often struggle with feature representation and off-policy learning challenges. In this paper, we propose a novel framework, online attentive kernel-based off-policy TD learning, and in combination with well-known algorithms, introduce OAKGTD2, OAKTDC, and OAKETD. This framework uses two-timescale optimization. In the slow-timescale, a sparse representation of state features is learned using an online attentive kernel-based method. In the fast-timescale, auxiliary variables are used to update the value function parameters under the off-policy setting. We theoretically prove the convergence of all three algorithms. Through experiments conducted in several standard reinforcement learning environments, we demonstrate the effectiveness of the improved algorithms and compare their performance with existing algorithms. Specifically, from the perspective of cumulative rewards, the proposed algorithm achieves an average improvement of 15% compared to on-policy algorithms and an average improvement of 25% compared to common off-policy algorithms. [ABSTRACT FROM AUTHOR]

Featured Application: This work can be applied to an online education platform to predict students' current learning states. In response to the challenge of low predictive accuracy in scenarios with limited data, we propose a few adjustable parameters prediction model based on lightweight prefix-tuning (FAP-Prefix). Prefix-tuning is an efficient fine-tuning method that only adjusts prefix vectors while keeping the model's original parameters frozen. In each transformer layer, the prefix vectors are connected with the internal key-value pair of the transformer structure. By training on the synthesized sequence of the prefix and original input with masked learning, the transformer model learns the features of individual learning behaviors. In addition, it can also discover hidden connections of continuous learning behaviors. During fine-tuning, all parameters of the pre-trained model are frozen, and downstream task learning is accomplished by adjusting the prefix parameters. Continuous trainable prefix vectors can influence subsequent vector representations, leading to the generation of session dropout prediction results. The experiments show that FAP-Prefix significantly outperforms traditional methods in data-limited settings, with AUC improvements of +4.58%, +3.53%, and +8.49% under 30%, 10%, and 1% data conditions, respectively. It also surpasses state-of-the-art models in prediction performance (AUC +5.42%, ACC +5.3%, F1 score +5.68%). [ABSTRACT FROM AUTHOR]

In this paper, we develop momentum-based adaptive update laws for parameter identification and control to improve parameter estimation error convergence and control system performance for uncertain dynamical systems. Specifically, we introduce three novel continuous-time, momentum-based adaptive estimation and control algorithms and evaluate their effectiveness via several numerical examples. Our proposed adaptive architectures show faster parameter convergence rates as compared to the classical gradient descent and model reference adaptive control methods. [ABSTRACT FROM AUTHOR]

Moving target detection is one of the most important tasks of radar systems. The clutter echo received by radar is usually strong and heterogeneous when the radar works in a complex terrain environment, resulting in performance degradation in moving target detection. Utilizing prior knowledge of the clutter distribution in the space–time domain, this paper proposes a novel moving target detection network based on small-sample transfer learning and attention mechanism. The proposed network first utilizes offline data to train the feature extraction network and reduce the online training time. Meanwhile, the attention mechanism used for feature extraction is applied in the beam-Doppler domain to improve classification accuracy of targets. Then, a small amount of real-time data are applied to a small-sample transfer network to fine-tune the feature extraction network. Finally, the target detection can be realized by the fine-tuned network. Simulation experiments show that the proposed network can eliminate the influence of heterogeneous clutter on moving target detection, and the attention mechanism can improve clutter suppression under a low signal-to-noise ratio regime. The proposed network has a lower computational load compared to conventional neural networks, enabling its use in real-time applications on space-borne/airborne radars. [ABSTRACT FROM AUTHOR]

Multi-object tracking faces critical challenges, including occlusions, ID switches, and erroneous detection boxes, which significantly hinder tracking accuracy in complex environments. To address these issues, this study proposes a single-task joint learning (STJL) model integrated into an online multi-object tracking framework to enhance feature extraction and model robustness across diverse scenarios. Employing cross-dataset training, the model has improved generalization capabilities and can effectively handle various tracking conditions. A key innovation is the refined tracker initialization strategy that combines detection and tracklet confidence, which significantly reduces the number of false positives and ID switches. Additionally, the framework employs a combination of Mahalanobis and cosine distances to optimize data association, further improving tracking accuracy. The experimental results demonstrate that the proposed model outperformed state-of-the-art methods on standard benchmark datasets, achieving superior MOTA and reduced ID switches, confirming its effectiveness in dynamic and occlusion-heavy environments. [ABSTRACT FROM AUTHOR]

We propose a method for automatically extracting new trends and best practices from the recent literature on online learning, aligned with the learning cycle perspective. Using titles and abstracts of research articles published in high ranked educational journals, we assign topic proportions to the articles, where the topics are aligned with the components of the learning cycle: engagement, exploration, explanation, elaboration, evaluation, and evolution. The topic analysis is conducted using keyword-based Latent Dirichlet allocation, and the topic keywords are chosen to reflect the nature of the learning cycle components. Our analysis reveals the time dynamics of research topics aligned on learning cycle components, component weights, and interconnections between them in the current research focus. Connections between the topics and user-defined learning elements are discovered. Concretely, we examine how effective learning elements such as virtual reality, multimedia, gamification, and problem-based learning are related to the learning cycle components in the literature. In this way, any innovative learning strategy or learning element can be placed in the landscape of the learning cycle topics. The analysis can be helpful to other researches when designing effective learning activities that address particular components of the learning cycle. [ABSTRACT FROM AUTHOR]

The rapid growth of e-learning increased the use of digital reviews to influence consumer purchases. In a pioneering approach, we employed AI-powered eye tracking to evaluate the accuracy of predictions in forecasting purchasing patterns. This study examined customer perceptions of negative, positive, and neutral reviews by analysing emotional valence, review content, and perceived credibility. We measured 'Attention', 'Engagement', 'Clarity', 'Cognitive Demand', 'Time Spent', 'Percentage Seen', and 'Focus', focusing on differences across review categories to understand their effects on customers and the correlation between these metrics and navigation to other screen areas, indicating purchasing intent. Our goal was to assess the predictive power of online reviews on future buying behaviour. We selected Udemy courses, a platform with over 70 million learners. Predict (version 1.0.), developed by Stanford University, was used with the algorithm on the consumer neuroscience database (n = 180,000) from Tobii eye tracking (Tobii X2-30, Tobii Pro AB, Danderyd, Sweden). We utilised R programming, ANOVA, and t-tests for analysis. The study concludes that AI neuromarketing techniques in digital feedback analysis offer valuable insights for educators to tailor strategies based on review susceptibility, thereby sparking interest in the innovative possibilities of using AI technology in neuromarketing. [ABSTRACT FROM AUTHOR]

Spatial abilities, which are sources of our capacity to understand visual and spatial relations among objects, as well as the abilities to generate, retain, retrieve, and transform well-structured visual information are important in several scientific fields and workplaces. Various tests have already been prepared to measure these abilities, including the Mental Cutting Test, which is considered the golden standard of measurement. However, much less attention is paid to how to prepare students for this test, as well as how to develop these skills most effectively. The purpose of this research is to study the multimodal approach of improving these skills and its effectiveness, i.e., the mixed use of 2D tools similar to the paper-based test, and 3D tools, including augmented reality and web-based interfaces in training students for those kinds of tasks. We want to demonstrate and prove with tests that multimodal modes of training can significantly affect the effectiveness of developing these skills. Moreover, through appropriately combining these methods, they can reinforce each other to form a multimodal approach, which is the most effective way for developing spatial skills and improving students' performance related to the Mental Cutting Test. [ABSTRACT FROM AUTHOR]

Teachers' professional learning often includes online components. This study examined how a case of 37 teachers utilized a specific online asynchronous professional learning platform designed to support teachers' growth in learning to teach statistics and data science in secondary schools in the United States. The platform's features and learning materials were designed based on effective online learning designs, supports for self-guided learning, and research on the teaching and learning of statistics and data science. We paid particular attention to the features we designed into the platform to support self-regulation and personalizing the experiences to meet their preferred learning goals such as allowing for free choice of learning materials, flexibility of when and how long to engage, providing personal recommendations based on user input, internal systems to track progress, and generating certificates of completion. In this study, we used a case study with both quantitative and qualitative data to examine whether teachers had gains in meeting learning goals related to their development in teaching statistics and data science, had sustained engagement, and found the features for personalization supportive for their learning. Results showed, overall, positive growth towards meeting learning goals and making small changes towards improved classroom practice. Most teachers were generally engaged in sustained ways across the study period, though we found six different patterns of completion that highlight ways in which teachers' goal-directed and self-regulated learning occurred within the busy schedules of educators. Several personalized features, especially the recommendations and tracking system, were highly utilized and perceived as supportive of teachers' learning. [ABSTRACT FROM AUTHOR]

This systematic review investigates the integration of interactive technologies in online teacher education across Africa from 2014 to 2024. The study aims to identify the types of interactive technologies employed, the leading countries in regard to their adoption, and the outcomes of their usage on teacher training programs. Despite significant advancements, particularly in countries like Kenya and South Africa, the effectiveness of these technologies varies widely due to infrastructural, socio-economic, and policy-related challenges. The findings highlight the critical role of reliable information communication technology (ICT) infrastructure, culturally relevant content, and comprehensive training for educators in optimizing the use of interactive technologies. Additionally, the study emphasizes the need for greater policy coordination and collaboration among African nations to fully leverage these technologies. The review concludes that, while interactive technologies hold substantial potential in terms of transforming teacher education in Africa, sustained efforts are required to overcome the existing barriers and ensure equitable access to quality education across the continent. [ABSTRACT FROM AUTHOR]

The integration of technology in higher education increased online courses available to students, although traditional face-to-face interaction remains dominant. The COVID-19 pandemic forced a rapid transition to emergency remote teaching (ERT), impacting public health nursing (PHN) education in Norway, which primarily consists of adult learners. The impact of the transition to online-only lectures on these students remains largely unexplored. The aim of this study is to examine how Norwegian PHN students experienced the transition from traditional classroom lectures to online-only lectures during the global pandemic. It also identifies the self-reported advantages and challenges associated with online-only lectures and whether this transition affected their perceived learning outcome. A cross-sectional sample of public health nursing (PHN) students (n = 275) participated in a survey in from May to November 2020. The questionnaire was specifically developed for this study and covers student motivation, perceived benefits and challenges of transitioning to online lectures, peer collaboration, and self-assessed learning outcomes. It was distributed to the PHN students via their respective education's LMS system. Most PHN students managed the technical aspects of the abrupt transition to online-only lectures effectively. They reported high digital competence, found the transition relatively easy, and remained motivated to continue their studies. Despite these positives, students reported a reduction in learning outcomes compared to classroom lectures. Challenges included the missing face-to-face interaction with peers, difficulties in managing childcare, and issues with structuring their studies. [ABSTRACT FROM AUTHOR]

The advancement of technology has led to the creation of numerous platforms that could potentially be used for remote education. For example, the recent development of the English Diploma Programme at a top university in the Kingdom of Saudi Arabia (KSA) deploys a new platform known as Area9 Lyceum (Area9). Because the English Diploma Programme is a recent development, and especially given its use of a new platform, this proposed research will investigate learners' attitudes to and acceptance of using the platform. Furthermore, it will look at how other universities could benefit from this experience to develop their own English as a Foreign Language (EFL) programmes along technological lines, specifically by deploying a survey tool based on the unified theory of acceptance and use of technology (UTAUT). The results reflect the positive attitude of the participants. Recommendations can be drawn from this study to help persuade stakeholders in higher education to adopt such platforms in the teaching of EFL or English as a Second Language (ESL). [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) is increasingly used in online education platforms to provide valuable insights into students' performance and success. However, the complexity of AI models makes it challenging for educators to interpret the specific factors that influence whether a student is going to pass or fail. Utilizing the Open University Learning Analytics Dataset (OULAD), this study employs various machine learning and deep learning techniques for predicting students' success, along with SHapley Additive exPlanations (SHAP) as an Explainable Artificial Intelligence (XAI) technique, to understand the key factors behind success or failure. Unlike traditional statistical methods that explore variable relationships, this AI-driven approach uses advanced deep learning techniques to identify patterns and insights, allowing for a better understanding of the factors influencing student success. Additionally, this study focuses on identifying students at risk of failure using XAI techniques, specifically SHAP, to interpret model outputs by breaking down how specific factors contribute to a student's success. This method enables targeted interventions to support their success. Results reveal that student engagement and registration timelines are critical factors affecting performance. The customized models achieve up to 94% accuracy for the designed tasks, outperforming traditional approaches. This study contributes to the use of AI in education and offers practical insights not only for educators but also for administrators and policymakers to enhance the quality and effectiveness of online learning. [ABSTRACT FROM AUTHOR]

(1) learning efficiency is recognized as the ultimate goal of online education, as it is related to the quality of online education and the cognitive development of students and is influenced by social interactions. This study explores the mediating roles of social presence and learning engagement in the relationship between social interaction and online learning efficiency, addressing gaps in prior studies that have not yet identified the underlying mechanisms. (2) students from three middle schools (N = 344; Mage = 13.61; 56.68% women) completed self-report questionnaires regarding social interaction, social presence, learning engagement, and learning efficiency. (3) the study findings reveal significant serial mediation effects of social presence and learning engagement in the relationship between learner–instructor and learner–learner interactions and learning efficiency. Specifically, while the indirect effect of learner–instructor interaction through social presence alone (indirect effect = 0.08, 95% CI = [−0.00, 0.17]) was not significant, the pathways through learning engagement (indirect effect = 0.18, 95% CI = [0.11, 0.26]) and the combined mediation through both social presence and learning engagement (indirect effect = 0.06, 95% CI = [0.03, 0.09]) were statistically significant. Similarly, for learner–learner interaction, the indirect effects through social presence (indirect effect = 0.09, 0.17) and learning engagement (indirect effect = 0.17, 95% CI = [0.11, 0.24]) were significant, as was the serial mediation through both mediators (indirect effect = 0.07, 95% CI = [0.04, 0.11]). (4) social presence and learning engagement played crucial mediating roles in the links between social interactions and online learning efficiency, and the predictive efficacy of learner–learner and learner–instructor interactions on online learning efficiency was found to be unequal. [ABSTRACT FROM AUTHOR]

A hierarchical consensus control algorithm based on value function decomposition is proposed for hierarchical multi-agent systems. To implement the consensus control algorithm, the reward function of the multi-agent systems can be decomposed, and two value functions can be obtained by analyzing the communication content and the corresponding control objective of each layer in the hierarchical multi-agent systems. Therefore, for each agent in the systems, a dual-critic network and a single-actor network structure are applied to realize the objective of each layer. In addition, the target network is introduced to prevent overfitting in the critic network and improve the stability of the online learning process. During the updating of network parameters, a soft updating mechanism and experience replay buffer are introduced to slow down the update rate of the network and improve the utilization rate of training data. The convergence and stability of the consensus control algorithm with the soft updating mechanism are analyzed theoretically. Finally, the correctness of the theoretical analysis and the effectiveness of the algorithm were verified by two experiments. [ABSTRACT FROM AUTHOR]