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This study sheds light on the existing void regarding wartime and online education in Africa. Over three-quarters of African nations have experienced various forms of conflict over the past three decades, resulting in a significant loss of life and immense suffering for African citizens striving for education. The African continent has witnessed nearly 88% of conflict-related fatalities worldwide. The widespread destruction of schools and universities, from primary to higher education, has worsened the problem of limited technology resources. This lack of technology makes it even harder for educational institutions to function effectively. Recent insecurity poses a formidable challenge to many African higher education institutions, impeding efficient administration and management, disrupting academic calendars, claiming student lives, and damaging the critical infrastructure for teaching and learning. In addition, African higher education institutions still lag behind their counterparts on other continents in embracing digital transformation. Using the Scopus database, this study conducted a bibliometric analysis of publications from 2000 to 2024, focusing on wartime and online education. The gathered documents were meticulously analysed using visualisation tools like VOS Viewer. The findings highlight a significant research gap regarding the intersection of wartime conditions and online education in African institutions, as there are no publications on wartime and online learning from the African continent. The findings highlight that the publications are mainly from a Western perspective, marginalising African higher education institutions in the global knowledge production and dissemination landscape. The paper identifies promising areas for further research on improving education during African conflicts to guide future efforts. [ABSTRACT FROM AUTHOR]

COVID-19 has forced universities around the world to adopt online learning. A learning management system (LMS) is a platform for online teaching. Educational institutes are facing difficulties in adopting LMS teaching and learning methods. Research on LMS adoption is still needed for effective implementation. Studying LMS adoption can help universities to understand their teacher's needs better. This review attempted to determine the factors that influence the adoption and effectiveness of the LMS with respect to teachers' perspectives. We planned search strategy, inclusion and exclusion criteria, data extraction, and data analysis. Manual search of articles from indexed journals using Google Scholar, Scopus, and PubMed Central electronic databases. The keywords used were "LMS and Adoption", "Factors affecting LMS Adoption", and "LMS and teacher's perspective". Inclusion/exclusion criteria: Only full-text journal articles published in peer-reviewed journals, in the English language, were selected. Articles with only abstracts and not full texts were excluded. Data extraction was conducted using the following themes: author name, year of publication, research approach, factors affecting adoption according to teacher's perspective, and research context. Only qualitative information is presented from the extracted data. Anxiety and knowledge about the use of the LMS, time factors, technical challenges, perceived usefulness, efficiency payoffs, student feedback, and faculty training were important factors affecting LMS use. Factors affecting the attitude of teachers considering individual values and virtues were not well documented in the literature until 2023. Attitude depends on the values and virtues of the individual. [ABSTRACT FROM AUTHOR]

Copyright of Arcos: Design, Cultura e Visualidade is the property of Editora da Universidade do Estado do Rio de Janeiro (EdUERJ) 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.)

Copyright of Profile: Issues in Teachers' Professional Development is the property of Universidad Nacional de Colombia, Facultad de Ciencias Humanas 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.)

Learning from data are critical across applications. However, in many applications, past data only gives partial information about the future. In "Contextual Inverse Optimization: Offline and Online Learning," Besbes, Fonseca, and Lobel study a general setting in which historical data are associated with observations of past optimal actions from experts in specific contexts but without the underlying rewards associated with these actions. To what extent can one "reverse engineer" the underlying decision-making process of experts and mimic them? The authors develop results that quantify the performance that is achievable given the data at hand in two types of settings: the offline setting in which data have already been collected and the online setting in which data are collected "on the fly." We study the problems of offline and online contextual optimization with feedback information, where instead of observing the loss, we observe, after the fact, the optimal action an oracle with full knowledge of the objective function would have taken. We aim to minimize regret, which is defined as the difference between our losses and the ones incurred by an all-knowing oracle. In the offline setting, the decision maker has information available from past periods and needs to make one decision, whereas in the online setting, the decision maker optimizes decisions dynamically over time based a new set of feasible actions and contextual functions in each period. For the offline setting, we characterize the optimal minimax policy, establishing the performance that can be achieved as a function of the underlying geometry of the information induced by the data. In the online setting, we leverage this geometric characterization to optimize the cumulative regret. We develop an algorithm that yields the first regret bound for this problem that is logarithmic in the time horizon. Finally, we show via simulation that our proposed algorithms outperform previous methods from the literature. Supplemental Material: The online appendices are available at https://doi.org/10.1287/opre.2021.0369. [ABSTRACT FROM AUTHOR]

In "Optimal No-Regret Learning in Repeated First-Price Auctions," Y. Han, W. Tsachy, and Z. Zhou study online learning in repeated first-price auctions where a bidder, only observing the winning bid at the end of each auction, learns to adaptively bid to maximize her cumulative payoff. To achieve this goal, the bidder faces censored feedback: If she wins the bid, then she is not able to observe the highest bid of the other bidders, which we assume is i.i.d. drawn from an unknown distribution. In this paper, they develop the first learning algorithm that achieves a near-optimal regret bound, by exploiting two structural properties of first-price auctions, that is, the specific feedback structure and payoff function. We study online learning in repeated first-price auctions where a bidder, only observing the winning bid at the end of each auction, learns to adaptively bid to maximize the cumulative payoff. To achieve this goal, the bidder faces censored feedback: If the bidder wins the bid, then the bidder is not able to observe the highest bid of the other bidders, which we assume is i.i.d. drawn from an unknown distribution. In this paper, we develop the first learning algorithm that achieves a near-optimal O˜(T) regret bound, by exploiting two structural properties of first-price auctions, that is, the specific feedback structure and payoff function. We first formulate the feedback structure in first-price auctions as partially ordered contextual bandits, a combination of the graph feedback across actions (bids), the cross-learning across contexts (private values), and a partial order over the contexts. We establish both strengths and weaknesses of this framework by showing a curious separation that a regret nearly independent of the action/context sizes is possible under stochastic contexts but is impossible under adversarial contexts. In particular, this framework leads to an O(T log2.5T) regret for first-price auctions when the bidder's private values are independent and identically distributed. Despite the limitation of this framework, we further exploit the special payoff function of first-price auctions to develop a sample-efficient algorithm even in the presence of adversarially generated private values. We establish an O(T log3T) regret bound for this algorithm, hence providing a complete characterization of optimal learning guarantees for first-price auctions. Funding: This project was supported in part by the National Science Foundation [Awards CCF-2106467 and CCF-2106508]. Y. Han and T. Weissman were partially supported by the Yahoo Faculty Research and Engagement Program. [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]

Despite a reasonably long history in university teaching, the discussion board is relatively underreported on in Political Science courses. As instructors contemplate which online tools should be carried forward after the pandemic, the discussion board bears closer scrutiny. Commenting is a skill that improves through practice and discussion boards help students develop transferrable skills to settings beyond school, especially online settings. Discussion boards have a track record of being long assignments that, as a result, risk instructor and student fatigue. This article, in response, presents a scaled-back discussion board exercise of five weeks. In this assignment, students take on set posting and commenting responsibilities. Interestingly, students reported that they learned less when placed in structured roles and when writing on less known topics, when, in fact, their grades were stronger in each case. Questionnaire and focus group data are clear: some structure is essential on discussion boards but not too much. Another key element of the discussion board template is that students practice different methodologies. Here that includes an interview, textual analysis, a simulation, and a policy recommendation. Designed this way, discussion boards develop the ability of students to participate in mature conversations, digesting critiques and responding appropriately to peers. [ABSTRACT FROM AUTHOR]

TODO comments are widely used by developers to remind themselves or others about incomplete tasks. In other words, TODO comments are usually associated with temporary or suboptimal solutions. In practice, all the equivalent suboptimal implementations should be updated (e.g., adding TODOs) simultaneously. However, due to various reasons (e.g., time constraints or carelessness), developers may forget or even are unaware of adding TODO comments to all necessary places, which results in the TODO-missed methods. These "hidden" suboptimal implementations in TODO-missed methods may hurt the software quality and maintainability in the long-term. Therefore, in this article, we propose the novel task of TODO-missed methods detection and patching and develop a novel model, namely TODO-comment Patcher (TDPatcher), to automatically patch TODO comments to the TODO-missed methods in software projects. Our model has two main stages: offline learning and online inference. During the offline learning stage, TDPatcher employs the GraphCodeBERT and contrastive learning for encoding the TODO comment (natural language) and its suboptimal implementation (code fragment) into vector representations. For the online inference stage, we can identify the TODO-missed methods and further determine their patching position by leveraging the offline trained model. We built our dataset by collecting TODO-introduced methods from the top-10,000 Python GitHub repositories and evaluated TDPatcher on them. Extensive experimental results show the promising performance of our model over a set of benchmarks. We further conduct an in-the-wild evaluation that successfully detects 26 TODO-missed methods from 50 GitHub repositories. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to analyze the spatiotemporal evolution of public attention to "adult education" over the past decade. Methods: Using Baidu Index data from January 1, 2014, to November 1, 2024, we examined search trends, demand distribution, and user characteristics through trend research, demand mapping, and user profiling. Results: The online search index for adult education shows a fluctuating upward trend, with peaks in April and October each year. Demand mapping indicates interest in areas such as adult college entrance exams, self-study exams, educational institutions, exam schedules, registration, major selection, tuition, and application procedures. User profiling reveals higher attention from males aged 30~39 in Guangdong Province. Conclusion: Changes in online attention to adult education correlate closely with career aspirations, policy announcements, and social contexts. [ABSTRACT FROM AUTHOR]

Since China boasts the highest numbers of online education institutions and users relative to other countries in the world, it has also been blessed with sufficient materials that may be used for empirical research. Although some studies have revealed the potential underlying legal risks in online education, there is still a paucity of scholars who set out to explore how the issues arose during legal practice via written judgments. This paper sifts through and extracts key information from hundreds of judgments provided by Chinese courts, based on which its typical issues were discussed. Through the findings acquired, this research has provided favourable empirical support for subsequent studies. [ABSTRACT FROM AUTHOR]

In the rapidly evolving landscape of online education, understanding what drives student satisfaction is crucial for designing effective learning experiences. The study examines the factors influencing English as a foreign language (EFL) students' satisfaction with online cooperative learning (CL) in massive open online courses (MOOCs). Employing a mixed-methods approach, the research investigates how different aspects of CL contribute to student satisfaction and identifies challenges students face in such environments. Quantitative data were gathered from 374 students through a structured survey, while qualitative insights were derived from semi-structured interviews with 16 participants. The findings suggest that CL enhances academic performance, engagement, and social interaction among students. However, challenges such as language barriers, unequal participation, and technological issues were also highlighted. The study emphasizes the importance of clear task assignments, effective leadership, and structured collaboration to mitigate these challenges. The research underscores the need for further exploration into the nuanced experiences of EFL students in MOOCs, particularly concerning cultural and linguistic factors that may influence their learning outcomes. These insights contribute to the broader understanding of how CL can be optimized in online education settings to enhance student satisfaction. [ABSTRACT FROM AUTHOR]

Blended massive open online courses (bMOOCs) have emerged as a potential educational model that combines conventional in-person instruction with online learning. The investigation into students' level of interaction in bMOOCs is significant to the effective implementation of bMOOCs in higher education. This study investigates the perceived level of student interaction with their peers, instructors, content, and technology in bMOOC environments, the relationship between their interaction and satisfaction, and ways of enhancing student interaction. This research employs a mixed-method data collection approach, including qualitative semistructured interviews and quantitative data analysis, with the participation of 339 students at a higher education institution in Vietnam. The findings reveal that students' perceived level of interaction was quite high. Student interaction in offline classes was preferred to the massive open online courses environment. Besides, student interaction types and their satisfaction were positively correlated. The paper also addresses possible suggestions for maximizing student interaction in bMOOC environments and practical implications for educational practices in higher education. [ABSTRACT FROM AUTHOR]

This paper investigates how five elementary school teachers established trust and recreated community for their online learners via cultural responsivity during the COVID-19 lockdowns in St. John's, NL. The study adopts the Cultural Historical Activity Theory as a theoretical lens for this qualitative case study. The elementary school teachers in this sub-study are part of the Canadian section of the larger ADVOST project that promotes young children's inclusion and agency via culturally relevant arts and digital media. The research findings from analyzed interviews show that the elementary school teachers successfully fostered trust and emotional connections with their online students by creating inclusive, culturally responsive environments that foster collaboration, communication, and family involvement. Consequently, the researchers recommend adopting culturally responsive pedagogical practices and undertaking professional training on Equity, Diversity and Inclusion (EDI) with provisions for building trust and connection among online learners. [ABSTRACT FROM AUTHOR]

This study examines the influences of learners' motivation, self-monitoring, and self-management on learning satisfaction in online learning environments. The participants were 185 undergraduates and 99 graduate students majoring in computer science and engineering. The participants' motivation, self-monitoring, self-management, and learning satisfaction were measured using a questionnaire. Results indicated that motivation, self-monitoring, and self-management significantly influenced learning satisfaction and the three factors together accounted for approximately 60% of the variance in learning satisfaction. Motivation was the most influential factor on learning engagement. Group differences emerged between undergraduates and graduate students in the influences of motivation, self-monitoring, and self-management on learning satisfaction. Compared to undergraduate students, graduate students had statistically higher scores in motivation, self-monitoring, and self-management, but not in learning satisfaction. The three factors also influenced undergraduate and graduate students differently in the regression analysis results. Motivation and self-monitoring, but not self-management influenced undergraduates' learning satisfaction, whereas motivation and self-management, but not self-monitoring influenced graduates' learning satisfaction. Further studies are needed to investigate the reasons for the group differences. The implications are that instructors need to utilize SDL strategies extensively to enhance learning satisfaction in online learning. In addition, designers, instructors, and institutions should tailor the learning strategies more effectively for their target audience given the differences in the influence of SDL on learning satisfaction between undergraduates and graduates. [ABSTRACT FROM AUTHOR]

The introduction of online homework has revolutionized traditional assignment formats, providing students with access to abundant learning resources, a convenient platform for completing assignments, real-time interactive learning opportunities, and accurate feedback. However, there is a paucity of research exploring the perspectives of elementary school students on the use of online homework platforms. This study, rooted in the online learning experiences of elementary school users, introduces three variables—perceived playfulness, perceived interactivity, and flow experience—to extend the UTAUT model. The investigation explores the behavioral intention of elementary school students to use online homework platforms. Data were collected through a questionnaire survey involving 312 elementary school students, and structural equation modeling was employed to analyze 289 valid responses. The results indicate that flow experience, social influence, performance expectancy, and effort expectancy significantly influence the behavioral intention of elementary school students to use online homework platforms. Additionally, perceived playfulness and perceived interactivity indirectly impact students' behavioral intention through the mediation of flow experience. Furthermore, it was observed that students' effort expectancy affects their performance expectancy. In conclusion, this research contributes to a deeper understanding of Chinese elementary school students' behavioral intention to use online homework platforms by reflecting their status and requirements within the context of online homework. The findings provide valuable insight for optimizing and upgrading online homework platforms as well as their pedagogical application. [ABSTRACT FROM AUTHOR]

Motivated by emerging applications, such as live-streaming e-commerce, promotions, and recommendations, we introduce and solve a general class of nonstationary multi-armed bandit problems that have the following two features: (i) the decision maker can pull and collect rewards from up to K(≥1) out of N different arms in each time period and (ii) the expected reward of an arm immediately drops after it is pulled and then nonparametrically recovers as the arm's idle time increases. With the objective of maximizing the expected cumulative reward over T time periods, we design a class of purely periodic policies that jointly set a period to pull each arm. For the proposed policies, we prove performance guarantees for both the offline and the online problems. For the offline problem when all model parameters are known, the proposed periodic policy obtains a long-run approximation ratio that is at the order of 1−O(1/K) , which is asymptotically optimal when K grows to infinity. For the online problem when the model parameters are unknown and need to be dynamically learned, we integrate the offline periodic policy with the upper confidence bound procedure to construct on online policy. The proposed online policy is proved to approximately have O˜(NT) regret against the offline benchmark. Our framework and policy design may shed light on broader offline planning and online learning applications with nonstationary and recovering rewards. This paper was accepted by J. George Shanthikumar, data science. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.04202. [ABSTRACT FROM AUTHOR]

Blended learning in ESL contexts has attracted substantial scholarly attention recently. However, the impact of various online input modes on English grammar learning outcomes, particularly for speaking skills, has not been extensively studied. This study evaluates how bi- and multi-modal online inputs impact blended speech training in a primary school. Using a quasi-experimental, between-subjects design over 20 weeks, the study categorized participants into two groups: the bi-modal group (BG, N=32), which utilized online text-and-audio materials, and the multi-modal group (MG, N=32), which engaged with online videos. The assessment of learning achievement was conducted through two speaking tests, a pretest and a posttest. The results revealed enhancements in grammar and overall speaking skills for both groups, with significant performance differences. The study enriches academic literature by providing empirical insights into how different online input modes could optimize blended learning environments and support explicit speaking instruction to improve grammar in primary students' speaking skills. [ABSTRACT FROM AUTHOR]

This study explores the impact of using Blackboard on improving the English writing skills of Saudi EFL learners. The research employs a qualitative approach, implementing semi-structured interviews with eight participants--four instructors and four students. A comparative analysis between online instruction via the Blackboard platform and traditional face-to-face methods revealed a variety of preferences among the participants. The findings indicate that most instructors and students prefer a blended-learning approach, combining online learning through Blackboard with in-person sessions. Furthermore, the instructors highlighted several challenges associated with online teaching, including issues such as limited student engagement, reduced feedback opportunities due to large class sizes, and diminished interpersonal interaction. Conversely, online platforms were recognized for their strengths in preventing plagiarism, facilitating efficient content delivery, and ensuring continuous access to educational resources. Students particularly valued the immediate feedback on grammar and spelling provided by the Blackboard platform, which they believe significantly contributes to ongoing improvement in their writing skills. The study suggests that integrating Blackboard as a supplementary tool for teaching English writing could optimize EFL instruction. This approach acknowledges and addresses the diverse preferences and challenges encountered in online learning environments. Moreover, it provides valuable insights into effectively leveraging online platforms to enhance EFL writing, navigating the variations in educational preferences among instructors and students alike. [ABSTRACT FROM AUTHOR]

Online applications in teaching and learning have been widely used in recent years. Pigai.org has become extremely popular for second language learning in China, and the study aims to examine its application to enhance students' college English writing competency. Despite numerous studies on the use of Pigai.org, there has been rare research on its effects on college English writing competency in Chinese polytechnics. The current study investigates the effectiveness of its application over five weeks in a polytechnic college. Pigai.org has been applied in a College English Test-oriented writing class with 30 second-year students majoring in English. Sixty writing samples are collected in the first and fifth weeks, respectively, as the data analysis to evaluate writing complexity, accuracy, and fluency in pre-and post-tests. The study utilises a quantitative research approach, incorporating descriptive statistics, paired samples t-tests, and repeated measures ANOVA. The results show that the complexity, accuracy, and fluency significantly increased after applying Pigai.org in writing. Despite the decreases in very few items, most items measured in the study had higher scores in the post-test than in the pretest. The findings indicate that the use of Pigai.org positively affected college English writing and shed light on the pedagogical implications. [ABSTRACT FROM AUTHOR]

Online second language (L2) learning classes at the university level have been increasing in Japan and around the world. Self-regulated learning (SRL) and language learning strategies (LLS) have shown efficacy in increasing L2 learning achievement and skills acquisition, but how students selfregulate and what strategies are necessary in online classes have yet to receive much attention in the literature. To fill this gap, the current study examined SRL and LLS use in an asynchronous EFL classroom at a Japanese university utilizing a survey (N = 17) and interviews (n = 7) with secondyear students between the ages of 19-20 years old. This study builds on previous research that indicated environmental structuring, goal setting, task strategies and classmate communication were important factors in online L2 learning contexts. Findings showed that strategies were selected based on individual course objectives (task completion, quality, or L2 learning focus) and that individual preferences impacted strategy choice. Additionally, deliberate establishment of social presence could have potentially enhanced classmate communication, and self-reflection and the SRL cycle can be impacted by individual learning goals. These findings can be useful for researchers and instructors investigating training methods for online L2 students and the promotion of more effective online L2 learning strategies. [ABSTRACT FROM AUTHOR]

The present study aims to address the research gap by investigating the relationships among students' metacognitive strategies (MS), self-efficacy belief (SEB), language learning motivation (LLM), and perceived progress in online English learning. Utilizing a cross-lagged analysis approach, the study analyzed survey data collected twice from a sample of 627 university students in China. The findings provide new insights into the changes in learners' metacognition, motivation, and self-efficacy belief over time. The findings suggested that there is a reciprocal relationship between SEB and MS, indicating that they influence each other. MS predicts LLM and perceived progress in online English learning, suggesting that metacognitive strategies have a causal effect on motivation and learning outcomes. LLM predicts SEB and perceived progress in English learning, indicating that motivation plays a causal role in shaping self-efficacy belief and learning outcomes. Perceived progress in English learning is influenced by other variables but does not act as a cause among the factors examined in this study. These findings highlight the potential to enhance online English learning by fostering learners' awareness of metacognition, self-efficacy belief, and motivation. [ABSTRACT FROM AUTHOR]

This study aims to examine tourists' experience evaluation on the fast-growing but understudied peer-to-peer (P2P) tour/activity experiences provided by sharing economy platforms and non-professional local guides. The P2P tours are unique in providing guests with a personalized and immersive experience of local culture, derived from the expertise and charm of the local hosts. A total of 211,610 online reviews were retrieved and analyzed using a topic modeling approach. Fourteen key topics were identified; tourists highlighted their personal feelings during interactions, sensory experience, and achievements derived from the customized experience in their storytelling approach of the reviews. Tourists highly valued hosts' personality and expertise, as well as the learning experience and comfortability of the tours. However, reviews with lower ratings primarily emphasized the issue of group interaction. The findings advanced the literature of P2P tourist experience in the sharing economy and provided new insights into tourists' pursuit for industry practitioners. [ABSTRACT FROM AUTHOR]

Traditionally, return demonstrations of clinical procedures in nursing education were conducted face-toface, providing students with hands-on experience crucial for clinical practice. However, due to COVID-19 restrictions, these demonstrations have been shifted to an online or virtual mode. This study explores nursing students' perceptions of performing online return demonstrations, focusing on their educational impact and the challenges encountered. Using a descriptive-correlational design, the study involved 94 purposively selected level three and four students from Mindanao State University – Buug Campus. Data were collected through validity and reliability-tested questionnaires and analyzed using Pearson correlation. Results indicate that while students viewed online return demonstrations positively in terms of content comprehension, they faced significant challenges, including lack of equipment, environmental distractions, suboptimal devices, and time-consuming resource searches. Additionally, insufficient student-teacher interaction and individual assessment further impeded students' performance. A significant correlation (p-value < 0.05) between educational impact and the student’s year level was identified, highlighting that the student’s academic standing influenced perceptions of educational effectiveness. While return demonstrations are now resuming on a face-to-face basis, future crises may necessitate a return to online methods. Therefore, it is crucial to strengthen online teaching-learning approaches to ensure better transfer of learning in similar situations. [ABSTRACT FROM AUTHOR]

This research aims to analyze students' problem solving ability in linear equations of three variables contextual problem solving in the terms of habits of mind of students at class X MA Muhammadiyah 2 Al-Furqan in contextual problem solving in online learning. This research is a qualitative research with descriptive method. The researchers used problem-solving ability test and habits of mind questionnaire as well as in-depth interviews with research subjects as data collection method. The subjects of this research were 3 students of class X IPA MA Muhammadiyah 2 Al-Furqan who came from high, medium, and low ability groups. These students participated in mathematics learning using blended learning. The results showed that the problem solving ability and habit of mind were interrelated and support each other. Students with high habits of mind have high problem solving ability, students with medium habits of mind have medium problem solving ability, and students with low habits of mind have low problem solving ability. Students' problem solving ability is high on the indicator of understanding the problem and low on the indicators of making plans and implementing plans. Students' habits of mind are classified as moderate to high on the indicator of perseverance or never giving up, and moderate to low on the indicator of enthusiasm in responding and the indicator of daring to take responsibility and face risks. The main finding of this study confirms that effective problem solving skills require good habits of mind. The research result shows the importance of developing positive thinking habits in learning mathematics can improve students' problem-solving skills. Thus, the integration of online learning with approaches that pay attention to aspects of habits of mind can be an effective strategy in improving students' mathematics achievement. [ABSTRACT FROM AUTHOR]

Since the COVID-19 pandemic, nursing education has shifted to more online learning. This shift may cause some problems with musculoskeletal pain and fatigue. This cross-sectional study investigated the prevalence of musculoskeletal pain, fatigue, and associated factors from online learning among 234 nursing students in Bangkok, with data collected from January to March 2023. The instruments used were the Personal Data Sheet, the Health Status Form, the Online Learning Risk Assessment, the Single-Item Visual Analogue Scale for Fatigue, and the Nordic Musculoskeletal Questionnaire. Data were analyzed using a chi-square test, t-test, and logistic regression. Of the 234 participants, 222 (94.9%) were women, averaging 20.6 ± 1.3 years. They spent an average of 7.5 hours per day on online learning, with 87.6% sitting in chairs without armrests and backrests. Additionally, 86.3% spent over three hours online daily, 61.5% using tablets without separate keyboards as their main device, and 33.3% using mobile phones. Over the past six months, 80.8% of participants experienced musculoskeletal pain, and 79.9% experienced moderate to severe fatigue. Sitting with the head down for over 2 hours daily was the strongest predictor for musculoskeletal pain, while sitting in the same spot for over two hours predicted fatigue. During online learning, mus- culoskeletal pain and fatigue can be prevented through targeted interventions that encourage regular breaks to reduce prolonged sitting and ergonomic adjustments for healthier sitting posture. The study recommends adding ergonomic and self-care education to nursing curricula to prevent discomfort from prolonged sitting and poor posture, especially in online learning. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press 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.)

It is known that teacher noticing skills improve through different interventions such as video clubs, lesson study, and short-term professional development programs. However, it is not known whether this improvement is permanent and whether teachers can transfer their noticing skills into the classroom. It is extremely important to provide an enduring change in teacher noticing skills. Rather than short-term programs, implementing long-running professional development programs, which last almost 2 years, enables teachers to maintain their noticing skills. At this point, the current study aims to develop in-service middle school mathematics teachers' professional noticing of students' mathematical thinking on pattern generalization during their involvement in a 2-year online professional development program enriched with collaborative discussion. Accordingly, the study was built on the professional noticing of children's mathematical thinking framework, including three noticing skills: attending, interpreting, and deciding how to respond. Participants comprised 31 in-service middle school mathematics teachers with up to 15 years of professional experience working in public schools in seven different provinces of Türkiye. The teachers participated in the online PDP, including scenarios involving student strategies of particular mathematics content. The analysis of the data gathered from the pre-test and post-test let us conclude that the three noticing skills of the in-service middle school teachers exhibited incredible progress through their involvement in collaborative discussion in a long-running online PDP. Based on this result, the characteristics of the online PDP are put forth to develop teachers' noticing skills. [ABSTRACT FROM AUTHOR]

The objective of this article is to investigate the viewpoints of both undergraduate and graduate students of English regarding online education in the aftermath of the Corona virus pandemic, which commenced in March 2020 and resulted in immediate, hit-or-miss changes within the higher education sector. To realize this aim, the study examines the perspectives of graduate and undergraduate students in the English Department at The Hashemite University in the fields of literary, cultural, and critical studies. Consequently, fifty graduate students were asked to write a well-thought essay in which they express their opinion about their experience in online education. On the other hand, eighty-four undergraduate students had to respond to a questionnaire designed to express their opinion within a scale of different responses. The results for both groups show that there is no significant difference between their attitudes. In general, there is a propensity to endorse a novel educational approach that integrates the traditional on-campus education with the most recent online off-campus education. [ABSTRACT FROM AUTHOR]

This era of revolution has influenced all sectors of society, including education, where technological advancements are now integral to online teaching and learning. However, not everyone fully understands the potential negative impacts of internet usage. The purpose of this research was to investigate and analyze cybersecurity awareness. The study focused on students at Aerospace Air Marshal Suryadarma University. The research employed a quantitative design, either descriptive (where subjects are typically measured once) or experimental (where subjects are measured multiple times). A descriptive study establishes a relationship between variables, while an experimental study determines causation. To analyze the collected data, SEM AMOS was utilized to measure students' awareness of cybersecurity. The study focused on five key areas: (a) regulation, (b) internet usage, (c) password security, (d) data security, and (e) cyberattacks. Based on the research framework and these focus areas, several indicators were developed for the study. The findings concluded that students are aware of cybersecurity issues. [ABSTRACT FROM AUTHOR]

Previous research has established that children's experiences of language during in-person interactions (e.g. individual and cumulative experiences of structural choices) implicitly shape language learning. We investigated whether children also implicitly learn structural choices during online interactions, and whether this is affected by the visual co-presence of a partner. During an online conference call, three- and five-year-olds alternated describing pictures with an experimenter who produced active ("a cat chased the dog") and passive ("the dog was chased by a cat") prime descriptions; half the participants had video+audio calls, and half had audio-only. Children in both age groups produced more passives after passive than active primes, both immediately and with accumulating input across trials; neither effect was influenced by call format (video+audio vs audio-only). These results demonstrate that implicit grammar learning mechanisms, as evidenced by syntactic priming effects, operate during socially contingent online interactions. They also highlight the potential of online methodologies for developmental language production research. [ABSTRACT FROM AUTHOR]

Purpose: People with intellectual disability face extensive health inequality and premature mortality. Medical students have reported that they lack the skills, knowledge and confidence to work with those with intellectual disability and autism. This emphasises the need for tomorrow's doctors to be adequately trained. This study aims to investigate students' knowledge, skills and attitudes towards people with intellectual disability and autism, examining whether these outcomes change following curricula re-design and with implementation of an e-learning module. Design/methodology/approach: The university curricula in intellectual disability and autism were re-designed and an e-learning module developed using co-production. This was delivered to fourth-year medical students with a subgroup receiving the additional e-learning. A controlled trial evaluated students' knowledge, skills and attitudes using pre- and post-questionnaires. Statistical tests of difference were used to the scores obtained. Findings: This study showed an improvement in knowledge, skills and attitudes with intellectual disability and autism after curricula engagement, with an incremental benefit observed for students also completing the e-learning module. There was significant difference in pre-and-post placement scores assessing student attitudes towards intellectual disability and autism teaching. Originality/value: This study highlights the importance of a multi-faceted, co-produced curricula re-design in intellectual disability and autism. The benefit of the e-learning module holds hope that the newly introduced mandatory Oliver McGowan training will be beneficial in the development of tomorrow's doctors. Effective training in intellectual disability and autism is vital to improve the care and support delivered and reduce unnecessary deaths. [ABSTRACT FROM AUTHOR]

Background: As the intersection of artificial intelligence (AI) and education deepens, predictive analytics using machine learning (ML) and deep learning (DL) models offer novel approaches to assessing student performance in online environments. However, challenges remain in accurately predicting high achievers and identifying students at risk due to limitations in traditional assessment models. This study explores the capabilities of these models in predicting academic achievement and highlights their potential role in reshaping educational assessment paradigms. Objectives: To evaluate the efficacy of various AI models—including Random Forest, XGBoost, and recurrent neural networks (RNNs)—in identifying at-risk students and differentiating levels of academic achievement, with an emphasis on inclusive and adaptive educational assessments. A key focus is on leveraging these models to create more inclusive and adaptive educational assessments. Methods: We analyzed a dataset comprising interaction data from the Open University Learning Analytics Dataset (OULAD), which includes clickstream data on student interactions with course materials from over 32,000 students. The models were trained and evaluated using performance metrics such as accuracy, precision, recall, and F1-scores, specifically targeting predictions of student withdrawals and distinctions. Results: The models effectively identified students at risk of withdrawing, with the Random Forest model achieving an accuracy of 78.68% and deep learning models approximately 77%. However, accurately predicting high achievers posed challenges, suggesting a complex relationship between interaction data and academic success. This limitation underscores the need for more nuanced modeling approaches to improve predictions for top-performing students. Conclusion: This research demonstrates the promise of AI-driven models in enhancing educational assessments while also highlighting current limitations in capturing academic excellence. Our findings indicate a need for ongoing development of AI tools that are ethically designed and capable of supporting dynamic, inclusive assessment strategies. Future research should focus on incorporating additional factors, such as student motivation and study behaviors, to enhance predictive accuracy, particularly for high achievers. Such advancements can contribute to a more equitable and effective educational landscape. [ABSTRACT FROM AUTHOR]

This study investigates the readiness for online education of the active employees of the Independent Authority for Public Revenue (IAPR) of the Hellenic Republic and its relationship with their level of emotional intelligence. The aim of the present work is to provide usable data to the designers of online programmes as well as to the trainers, and contribute to the planning and organisation of effective online training programmes. The Online Learning Readiness Scale (OLRS) and the Trait Emotional Intelligence Questionnaire—Short Form (TEIQue-SF) were adapted and used in this study. The statistical analysis of the results revealed that the largest percentage of the IAPR's employees are ready for distance learning with the use of online learning tools. Furthermore, the employees' level of emotional intelligence is an important factor that influences their readiness and should be considered in the design of the distance learning programmes. [ABSTRACT FROM AUTHOR]

Pushing the frontiers of time-series information processing in the ever-growing domain of edge devices with stringent resources has been impeded by the systems' ability to process information and learn locally on the device. Local processing and learning of time-series information typically demand intensive computations and massive storage as the process involves retrieving information and tuning hundreds of parameters back in time. In this work, we developed a memristor-based echo state network accelerator that features efficient temporal data processing and in situ online learning. The proposed design is benchmarked using various datasets involving real-world tasks, such as forecasting the load energy consumption and weather conditions. The experimental results illustrate that the hardware model experiences a marginal degradation in performance as compared to the software counterpart. This is mainly attributed to the limited precision and dynamic range of network parameters when emulated using memristor devices. The proposed system is evaluated for lifespan, robustness, and energy-delay product. It is observed that the system demonstrates reasonable robustness for device failure below 10%, which may occur due to stuck-at faults. Furthermore, 247× reduction in energy consumption is achieved when compared to a custom CMOS digital design implemented at the same technology node. [ABSTRACT FROM AUTHOR]

Optimizing charging protocols is critical for reducing battery charging time and decelerating battery degradation in applications such as electric vehicles. Recently, reinforcement learning (RL) methods have been adopted for such purposes. However, RL‐based methods may not ensure system (safety) constraints, which can cause irreversible damages to batteries and reduce their lifetime. To this end, this article proposes an adaptive and safe RL framework to optimize fast charging strategies while respecting safety constraints with a high probability. In our method, any unsafe action that the RL agent decides will be projected into a safety region by solving a constrained optimization problem. The safety region is constructed using adaptive Gaussian process (GP) models, consisting of static and dynamic GPs, that learn from online experience to adaptively account for any changes in battery dynamics. Simulation results show that our method can charge the batteries rapidly with constraint satisfaction under varying operating conditions. [ABSTRACT FROM AUTHOR]

The aim of this study was to pilot an adapted version of an online relationships program with residents in treatment for alcohol and other drugs (AOD). The OurRelationship (OR) Program, which is based on Integrative Behavioral Couples Therapy, was piloted in a group-based format to determine whether residents' participation in the program would result in decreases in residents' destructive responses and increases in constructive responses to relationship conflict scenarios as well as reductions in negative affect experienced during these conflict scenarios. Residents (N = 104) across six residential facilities participated in the pilot over 4 weeks. Pre and post program completion, residents read three vignettes in which they were asked to imagine themselves as experiencing each of the three relationship conflicts with a romantic partner. After reading each vignette, residents completed assessments related to their constructive and destructive behavioral responses to each vignette as well as the degree to which they experienced negative affect. Pre-post comparisons across the three vignettes revealed residents reported reductions in destructive behavioral responses and anger (d s −0.31 to −0.58) as well as increases in constructive responses (d s 0.33–0.77). The findings provide preliminary evidence regarding the application of programs to address the relationship difficulties experienced by those in AOD treatment. Future research into control trials of the OR program within the AOD sector can help to establish the effectiveness of relationship programs in helping to address the relationship problems of this vulnerable population. [ABSTRACT FROM AUTHOR]

Introduction The internet is an essential resource for patients and their loved ones to understand their medical conditions, and professional medical organizations have taken great strides to develop educational material targeting patients. The average American reads at a seventh to eighth grade reading level, hence it is important to understand the readability of this medical information to ensure patients comprehend what is being presented. Methods In January 2023, online patient education material was downloaded from major cerebrovascular healthcare organizations and assessed using eight assessments, including Bormuth Cloze Mean, Bormuth Grade Placement, Coleman--Liau (grade levels), Coleman--Liau (predictive cloze scores), Flesch Reading Ease (FRE), and Fry. Results A total of 32 files were extracted from six organizations and analyzed across 15 readability measures. None of the organizations met the federal government guidelines for grade-level readability. This held constant across all measured tests. Two organizations had above a postgraduate level. The FRE graphs do not identify any organizations with material below a ninth grade reading level, while the American Association of Neurological Surgeons (AANS) and the Society of Interventional Radiology (SIR) have a postgraduate readability level. The Fry graphs show similar results, with AANS/CNS Cerebrovascular Section, Society of NeuroInterventional Surgery (SNIS), SIR, and AANS having college-level readability. The lowest readability across all measures is only at an early seventh grade reading level. Conclusions Current health literacy content for cerebrovascular patients is far above the recommended readability level. We provide straightforward suggestions for how major professional organizations should improve their informational material on cerebrovascular diseases to improve patient understanding. [ABSTRACT FROM AUTHOR]

Copyright of RIED: Revista Iberoamericana de Educación a Distancia is the property of Revista Iberoamericana de Educacion a Distancia 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.)

Copyright of RIED: Revista Iberoamericana de Educación a Distancia is the property of Revista Iberoamericana de Educacion a Distancia 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.)

Food handler (FH) programs can improve knowledge among foodservice workers. Currently eight states require these programs for front-line foodservice workers. Although FH programs increase knowledge, their impact on the adoption of food safety behaviors within the United States is limited. This study was conducted using a retrospective post-then-pre approach to survey how often 141 foodservice employees in Texas were adhering to targeted food safety behaviors before and after completing an online FH program. Ten behaviors in the areas of temperature control, cleaning and sanitizing, and personal hygiene were assessed on a Likert scale (1 = always to 4 = never) before and after the foodservice employees completed the FH program. Change in behaviors was calculated with paired t tests, and effect size was measured with Cohen's d. Significant improvement in all but one behavior was observed, with a small to medium effect size. The one behavior that did not significantly change was coming to work with vomiting and/or diarrhea; however, the frequency of that behavior was close to "never" (mean = 3.9) before and after completing the program. Results suggest that the knowledge obtained from an online FH program may be helpful for improving targeted food safety behaviors that can reduce the risk for foodborne illness. [ABSTRACT FROM AUTHOR]

Adaptive iterated local search (AILS) is a recently proposed metaheuristic paradigm that focuses on adapting the diversity control of iterated local search by online learning mechanisms. It has been successfully applied to the capacitated vehicle routing problem (CVRP) and the heterogeneous vehicle routing problem. Hybridizing it with path relinking (PR) has further improved the intensification of the method for the CVRP, providing outstanding results. However, the potential of this metaheuristic has not yet been investigated on other combinatorial optimization problems, such as location problems. In this paper, we develop a version of AILS for the maximal covering location problem (MCLP). This problem consists of locating a number of facilities to maximize the covered customer demand, where a given facility location can meet the demand of customers located within a coverage radius. Experiments on large‐scale instances of the MCLP indicate that AILS hybridized with PR, called AILS‐PR, outperforms the state‐of‐the‐art metaheuristic. [ABSTRACT FROM AUTHOR]

The blended learning mode has attracted significant scholarly attention with students’ achievement emotions and teacher–student relationship (TSR) being key factors in the blended EFL context. However, empirical studies exploring these constructs in this context, particularly those involving Small Private Online Courses (SPOCs) are limited. Drawing on control-value theory (CVT), the present study adopted a mixed-method approach to examine the intricate relationship between students’ perceived TSR, their emotional experience (i.e. enjoyment and boredom) in the SPOC component, and those in the face-to-face classroom. Quantitative data were collected from 223 Chinese non-English major freshmen. Path analyses revealed that perceived TSR and emotional experience during SPOC learning jointly influenced their enjoyment and boredom in the flipped classroom. Specifically, SPOC enjoyment positively predicted both flipped classroom enjoyment and boredom, while SPOC boredom predicted flipped classroom boredom. Additionally, students’ perceived TSR had a moderate positive effect on their flipped classroom enjoyment, and a slight negative effect on their flipped classroom boredom. Qualitative data from interviews with six students supported these findings. These results provide valuable theoretical and pedagogical implications for educators in blended learning environments. [ABSTRACT FROM AUTHOR]

The growing mental health needs and constrained resources in low- and middle-income countries necessitate scalable solutions. Single Session Therapy (SST) is a global trend in brief and cost-effective options for mental health interventions. It involves a single planned session between mental health service provider and client. This study aims to present a protocol to develop and evaluate a culture specific web-based training program to equip mental health support providers with the skills and confidence to deliver SST. The study protocol uses a mixed-methods evaluation design through three phases—need assessment – where psychologists and social workers collaborate to identify training needs and co-create the program; development and expert validation of the web-based training program; and randomized control trial to evaluate the training, followed by in-depth discussions with participants. This study breaks new ground by empirically designing and evaluating a training program for SST. It uniquely co-designs and validates a culturally sensitive SST training program, leveraging the expertise of a renowned international panel. This protocol goes beyond a blueprint for replicating this study, it serves as a foundational guide for nations seeking to implement effective SST training for their mental health professionals, preventing duplication of efforts. [ABSTRACT FROM AUTHOR]