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The rapid development of e-learning has drawn increasing attention to the issue of how learners’ learning activities can be better structured using technologies. This study focuses on how to improve e-learning performance by optimizing the structuring of learning sessions from the perspective of interleaving (i.e., mixing different topics in a learning session). Following the design science paradigm, this study chooses cognitive load theory as the kernel theory and proposes a new interleaving design—related-interleaving —that populates an interleaved session with related topics as a way of reducing cognitive load during an interleaved session. Drawing on the theoretical predictions, we design and instantiate a personalized learning system with the related-interleaving strategy by fusing educational strategies and machine learning techniques. The results from a two-month field experiment confirm that related-interleaving outperforms non-interleaving and unrelated-interleaving. Our findings also reveal that compared with unrelated-interleaving, related-interleaving benefits weak learners more and thus helps reduce learning performance disparities. This study demonstrates how personalized e-learning systems can be further improved from the perspective of interleaving. [ABSTRACT FROM AUTHOR]

Federated learning (FL) is a decentralized approach to training machine learning model. In the traditional architecture, the training requires getting the whole data what causes a threat to the privacy of the sensitive data. FL was proposed to overcome the cited limits. The principal of FL revolves around training machine learning models locally on individual devices instead of gathering all the data in a central server, and only the updated models are shared and aggregated. Concerning e-learning, it is about using electronic/digital technology to deliver educational content in order to facilitate the learning. It becomes popular with the advancement of the internet and digital devices mainly after the COVID-19. In this work, we propose an e-learning recommendation system based on FL architecture where we can propose suitable courses to the learner. Because of the important number of connected learners looking for online courses, the FL encounters a problem: bottleneck communication. This situation can cause the increase of the computational load, the longer time of the aggregation, the saturation of the resources, etc. As solution, we propose using the edge computing potentials so that the aggregation will be performed first in the edge layer then in the central server, reducing hence, the need for continuous data transmission to the server and enabling a faster inference while keeping the security and privacy of the data. The experiments carried out prove the effectiveness of our approach in solving the problem addressed in this work. [ABSTRACT FROM AUTHOR]

The study aimed to investigate the impact of the COVID-19 pandemic on primary education in Cyprus and to discern the implications for the post-pandemic era, specifically focusing on the Emergency Remote Learning (ERL) experiences and reflections of upper primary students (ages 9-12). Grounded in socio-constructivist learning theory, which emphasizes the importance of active student engagement and social interaction in the learning process, the research explored the challenges students faced during the rapid shift to remote education. A mixed-methods design was employed, using an in-depth online survey that incorporated both quantitative and qualitative questions. Data were collected from a sample of 204 students selected through non-probability, convenience sampling. The analysis revealed that students experienced several challenges, including technology constraints, lack of interaction, and difficulty maintaining concentration, which are consistent with global findings on K-12 ERL. Among demographic factors, the type of school attended (public vs. private) had a significant influence on most aspects of students' ERL experience. Private school students reported more favourable conditions than their public school counterparts, which facilitated a smoother shift to both asynchronous and synchronous ERL, resulting in a more positive overall ERL experience. Regardless of the type of school attended, students overwhelmingly expressed a strong preference for face-to-face learning. Comparisons with other studies conducted in Cyprus during the same period involving older student age cohorts suggest significant age-related differences. The young students in our study encountered greater challenges during the transition to ERL, which can be attributed to their heightened need for scaffolding and external regulation to learn in the virtual space, as well as the higher importance they attached to the social aspects of school life taken away by ERL. Despite their largely negative experiences with ERL, a high proportion of the children advocated integrating the e-learning tools and technologies they got acquainted with during ERL into the normal context of schooling. These findings underscore the importance of further research into effective instructional strategies tailored to young learners in both online and blended learning settings. They also highlight the potential benefits of incorporating e-learning tools into conventional classrooms to enhance the teaching and learning process. [ABSTRACT FROM AUTHOR]

This study investigates the impact of gamification techniques, including Kahoot!, Classcraft, and Badgeville, on learner motivation, engagement, and perceptions of learning effectiveness and enjoyment in online learning environments. Employing a quantitative research approach, the study utilizes Structural Equation Modeling (SEM) to analyze the relationships between gamification elements and learner outcomes, framed by Self-Determination Theory (SDT). Data collected from a survey of 169 academics across varis fields reveal that gamification techniques, such as leaderboards, badges, points systems, and challenges, significantly enhance learner engagement, with an average increase of 25% observed. Rewards, incentives, and competitive challenges boost both intrinsic and extrinsic motivation, leading to a 30% improvement in learner performance. Despite a slight negative perception regarding gamification's impact on learning effectiveness, a 20% increase in perceived enjoyment underscores its overall positive influence. Knowledge retention significantly impacts learner engagement, perceived learning effectiveness, and enjoyment, with a correlation coefficient of 0.65 between retention rates and engagement levels. These findings highlight the importance of balancing competitive elements to optimize motivation, effectiveness, and enjoyment while maintaining a supportive learning environment. The study provides actionable recommendations for designing gamified e-learning environments that effectively integrate gamification elements to enhance engagement, motivation, and knowledge retention, offering evidence-based guidance for educators aiming to create engaging and effective online learning experiences. [ABSTRACT FROM AUTHOR]

The application of the concept of flow in the context of the e-learning environment has widespread benefits. Creating a sense of flow can result in a positive learner experience and continuance in the e-learning environment. However, in the past two decades, applying the flow concept in analysing continuance intention in an e-learning context has been vague and complicated due to the broad nature and learners' behaviour. This includes the lack of certainty in operationalising the flow framework, theories, multitude of methods, or delivery settings. More specifically, uncertainty persists regarding the association between flow experience and continuance in e-learning. Hence, we intend to systematically review, synthesise and appraise the literature on the operationalisation of flow experience, methods used to study the flow concept, and the relationship between flow experience and continuance intention. We reported this systematic review according to the guidance of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Electronic database searches on Scopus, Web of Science, JSTOR, and manual searches yielded 913 potential papers. Overall, n=20 peer-reviewed articles published between 2000 and 2021 satisfying the eligibility criteria were included. The synthesis identified that all the studies applied quantitative research design to examine the relationship between flow experience and continuance intention. While evidence also accumulated that no included studies have conceptualised flow experience considering all the nine dimensions, the lack of certainty in operationalising the flow framework applied in e-learning invites the attention of the researchers to validate the dimensions. Finally, most studies in the review exhibited a significant relationship between flow experience and continuance intention. The study provides a comprehensive synthesis and an in-depth analysis of the body of knowledge produced in the area of flow experience and continuance in the e-learning context, as it helps in providing implications for online marketers, learners, and academic institutions. The approach incorporated for synthesising evidence in this study lays a rigorous benchmark for conducting systematic reviews. This research study will be an asset for researchers and methodologists undertaking systematic reviews in e-learning. [ABSTRACT FROM AUTHOR]

The study evaluated the effectiveness of e-learning platforms in improving Science achievement among Grade VI pupils at Southville Elementary School. A total of 54 pupils were divided equally into traditional instruction and elearning groups. The research used matched pairing and statistical methods, including mean, standard deviation, paired t-tests, and Cohen's d. Initial findings revealed that both groups had the same mean pre-test score of 7.52 (SD = 1.87), indicating a satisfactory performance. During the formative tests, the e-learning group outperformed the Traditional Instruction Group, with mean scores of 50.41 (SD = 3.92) and 46.70 (SD = 4.42), respectively. In the post-test, the elearning group again showed superior performance, with a mean score of 15.44 (SD = 1.72) compared to the traditional instruction group's 14.15 (SD = 2.05), both of which were at a very satisfactory level. Statistical analysis confirmed a significant difference between the groups in both formative tests [(t(52) = 3.26; p<0.01], with a moderate effect size (d = 0.88), and post-tests [(t(52) = 2.52; p<0.05], with a moderate effect size (d = 0.68). Furthermore, the within-group analysis revealed significant differences between pre- and post-test scores. For the traditional instruction group, the post-test scores were significantly higher than the pre-test scores [(t(26) = 12.17; p<0.01], with a large effect size (d = 4.41). Similarly, the e-learning group showed significant improvement [(t(26) = 15.66; p<0.01], with a large effect size (d = 3.38). It is concluded that e-learning platforms significantly enhance pupil performance in Science. Also, both null hypotheses in the study were rejected. [ABSTRACT FROM AUTHOR]

Introduction: Due to the chronic nature of the diabetes, patients who suffer from this disease need education to take care of themselves and increase self-care. Therefore, the present study was conducted with the aim of comparing the effect of e-learning and teach-back methods on the performance of diabetic patients. Methods: In this study, 144 patients with type 2 diabetes were selected based on purposive sampling. Considering the inclusion and exclusion criteria, the subjects were divided into two groups of intervention (n = 48) and control (n = 48) by simple randomization. The two intervention groups included the e-learning group whose subjects were trained by entering the training site for three months and the teach-back group whose subjects were trained during four 60-minute sessions for three months. The control group was followed up according to routine care. Before and one month after the intervention, data were collected using self-care questionnaires in the areas of knowledge and performance based on interviews and blood glucose tests and self-reporting. The data were analyzed using SPSS 21 and statistical tests of ANOVA, independent t and Pearson's correlation coefficient. Results: The results showed that both e-learning (P = 0.001) and teach-back training (P = 0.008) methods were associated with a significant increase in self-care compared to before the intervention, but only in the teach-back group, this increase was significant compared to control group(P = 0.002) and the training methods showed no significant effect on blood sugar level and BMI of the patients (P > 0.05). Conclusion: The results of the present study showed that both electronic and teach-back training methods have been effective on the level of self-care of diabetic patients. However, the teach-back method had a greater impact on the level of self-care. [ABSTRACT FROM AUTHOR]

Background: While previous research has emphasized the importance of personal beliefs (expectancy‐value theories) for achievement‐motivated behaviour, it lacks the integration of temporal factors that are also discussed as important drivers of achievement‐motivated behaviour. Temporal Motivation Theory (TMT) combines both approaches in a formalized manner. Aims: Although TMT is supported by empirical studies with self‐reported academic procrastination, it has not been tested on actual achievement‐motivated behaviour. Materials & Methods: We evaluated the predictive power of the TMT on N = 2351 learning days of 127 psychology students' self‐regulated examination preparation for statistics over the course of one semester using logfile data of an e‐learning system. Results: The proposed TMT score, incorporating expectancy and value beliefs, sensivitiy to delay, and actual time till examination predicted students' achievement‐motivated behaviour significantly. Discussion: Further analyses revealed that not the trait compositions of the TMT, but the temporal proximity of the statistics examination was the main driver of this association. Conclusion: The results have important implications for understanding the factors that shape students' motivation to learn and subsequent academic success in actual learning situations. Thus, research should continue to take situational aspects, especially the temporal proximity of goals more into account. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to explore novice ESL teachers experiences with e-learning. Technology has changed education, and it is an integral part of learning and teaching. The students taught these days are not the same as those taught before the pandemic, as current students are 'digital natives' surrounded by computers, smartphones, and other digital devices. The learning that occurs online or through the internet or intranet is e-learning or online education. Since the outbreak of pandemic COVID-19, e-learning has been central to education in India in general and in Kerala in particular. This paper examines what novice ESL teachers experience with online education or e-learning. Since this study focuses on generating individual teachers's personal experiences, an interpretative qualitative approach is used. Participants are ten newly appointed English language teachers who teach English as a second language to undergraduate students in the department of English. The participants are from three Arts and Science colleges in Kannur district, Kerala, India. The data is collected using an open-ended questionnaire and it is analyzed and interpreted thematically. The result indicates that they had challenges and difficulties while implementing e-learning to teach English. It also demonstrates e-learning has had effects on their students. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) has led many colleges and students to use online learning. In educational databases with so much data, evaluating student development is difficult. E-learning is essential for egalitarian education since it uses technology and contemporary learning techniques. This review research found three ways for predicting online course performance: i) To choose the best features to raise student performance; ii) The most effective algorithms for transforming unbalanced data into balanced data; and iii) The best machine learning algorithms to predict online course performance. This study also offered insights into using hybrid techniques and optimization algorithms to educational data sets to improve student performance prediction. The utilization of data from independent e-learning products to enhance education today requires data processing to ensure quality. In addition to these techniques, our abstract highlights the effectiveness of hybrid feature selection methods like L2 regularization (Ridge) and recursive feature elimination (RFE) and ensemble learning models like random forest, gradient boosting, and AdaBoost. These approaches considerably improve prediction accuracy and tackle huge and sophisticated educational dataset challenges. Our work uses advanced machine-learning approaches to optimize e-learning settings and boost academic achievements in the shifting online education landscape caused by the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic forced universities into emergency remote learning. For universities situated in a country where internet connectivity prices are high, network coverage is low, and most students live in rural areas, this presented a unique set of problems. One of the issues is that traditional orientations were face-to-face for first-time entering students (FTENs) at universities, and they had to be moved online due to lockdown restrictions and the desire to save the academic year. For the university concerned, this presented challenges in accessing students due to their low digital literacy skills and infrastructure limitations. The study employed a quantitative exploratory research approach to assess whether WhatsApp, a low-cost communication tool offering features like affordable data bundles, group creation, and accessibility, could facilitate student engagement and support during the COVID-19 lockdown at a rural university campus. The aim was to investigate if utilizing WhatsApp could foster a sense of belonging among students, potentially mitigating dropout rates and preventing students from falling behind. The hypothesis posited a positive correlation between using WhatsApp for academic support and student retention, ultimately leading to enhanced success rates. The study used the 'Academic Dropout Wheel, a theoretical framework developed by Naaman (2021), which identifies key factors contributing to academic dropout and provides strategies for intervention. The results of a quantitative questionnaire on 181 of the 2022 cohort of FTENS at the campus revealed that students felt more at ease, had a feeling of belonging and ownership of the university, and knew where to ask for help through the effective use of WhatsApp. This paper concludes that if professionally managed, WhatsApp can be an effective tool to facilitate continued adjustment and integration of FTENs into the university. [ABSTRACT FROM AUTHOR]

AbstractThis study presents a novel framework to evaluate the usability and user experience of e-learning platforms, focusing on the Duolingo language learning app. By integrating advanced Natural Language Processing (NLP) techniques such as Large Language Models (LLMs), Latent Dirichlet Allocation (LDA), and sentence embedding models, we identified thirteen key usability and user experience topics from a large dataset of user reviews. Our findings reveal that Duolingo is highly rated since users value its enjoyable learning experiences and effectiveness. However, technical issues, lack of explanations, and frustrating features were identified as areas for improvement. The study demonstrates the effectiveness of our framework in analyzing user feedback at scale, offering valuable insights for improving user experience in e-learning platforms and other domains. [ABSTRACT FROM AUTHOR]

Satisfaction of education programmes is fundamental to accomplishing a professional identity of the graduates especially in programmes where clinical practicum forms a core element in the education process. This study aimed to detect the overall SLP students’ level of satisfaction with online instruction of clinical practicum during the COVID-19 pandemic. A questionnaire was administered for a convenience sample of two cohorts of students (n = 186). The number of participants who responded to the questionnaire, n = 149. The questionnaire was based on a construct of 30 questions, developed on a basis to reflect the components of key points such as student-patient-supervisor interaction, assessment, and treatment plans, the success of treatment, infection control measures, student skills, and training outcomes, student evaluation, use of instruments and tools, as well as report writing. Students rated their online instruction as very low. Only 30.7% agreed or strongly agreed that they were satisfied and fulfiled the expected training outcomes. ‘Self-reliance in searching for information from different resources’ was the most cited motivation for satisfaction. ‘Deprivation from exposure to instrumentation’ was the most cited motivation for dissatisfaction. The findings support the literature in the area of student satisfaction with e-learning methods of instruction in speech pathology programmes and reveal several implications regarding the satisfaction/dissatisfaction balance. [ABSTRACT FROM AUTHOR]

The development of green technology (GT) and green innovation (GI) in green management practices (GMP) is an important key in today's digital and sustainable era. This article discusses how e-learning (EL) acts as an antecedent variable in strengthening green innovation (GI) and the application of green technology (GT) to green management practices(GMP). This study analyzes whether e-learning influences green management practices by mediating green technology and green innovation. This study uses cross-sectional data that collects population data at one point to analyze the prevalence of variables or relationships between variables in the sample. The population consisted of lecturers in higher education in Indonesia. The results show that e-learning influences green innovation, technology, and management practices. Similarly, green innovation and green technology significantly affect green management practices. It is also firmly established that green innovation and technology are effective mediator variables for e-learning and green management practices. Therefore, green management practices in universities cannot ignore the important role of e-learning, investing in green innovation and green technology to support the achievement of sustainable education. [ABSTRACT FROM AUTHOR]

The study aimed to explore the repercussions of cyberbullying on students on educational platforms. This descriptive study depends on a social survey for a sample of male and female students in their high school. The sample is 824 people, and data was collected through a questionnaire. The paper studies the repercussions of cyberbullying on students and the educational atmosphere. The study's outcome is that most of the sample's participants agree on these repercussions on both, students and the educational atmosphere. The study recommended holding conferences, webinars, and workshops, handling the repercussions of cyberbullying and regulations for bullies on educational platforms to deter this cyberbullying, to raise awareness among students. [ABSTRACT FROM AUTHOR]

In response to the COVID-19 crisis, higher education institutions increasingly rely on e-learning systems. Indeed, the higher education market has become increasingly competitive with the addition of open education models. However, the abundance of accessible online courses makes it challenging to deliver education that meets student needs. Learners have diverse profiles based on their traits, motivations, prior knowledge, and learning preferences. Recently, much research has given attention to the importance of using the contextual parameters to perform more accurate recommendations. In this context, context-aware recommendation of pedagogical resources can deal with the issue of information overload, cold start problem and meeting the learner's preferences. This paper describes a context-aware recommender system that harness the learner's contextual information. Our proposed approach is called Context Embedding Deep Collaborative Filtering (CEDCF), which enriches the learner profile with extracted sentiments from previous interactions. The proposed approach comprises three models, called Generalized Matrix Factorzation (GMF) , Multilayer Perceptron (MLP) and Neural Matrix Factorization (NeuMF). The GMF and the MLP are respectively applied to the rating matrix and the contextual parameters. The outputs of these models are then fed into a neural network to perform rating prediction. To put our proposal into shape, we model a real-world application of a merged coursera dataset to recommend courses. The experimental evaluation shows relevant results attesting the efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

Introduction: Unilateral biportal endoscopy (UBE) is a minimally invasive surgical (MIS) technique utilized for lumbar decompression, which has recently gained popularity in Europe. We aimed to explore the value of sequential adaptive e-learning, followed by simulator-based hands-on training modules for UBE at the occasion of the 2024 EANS Young Neurosurgeons meeting. Materials and methods: An adaptive e-learning was designed by learning engineers (Area 9 Lyceum), based on theoretical content provided by two endoscopic spine surgeons. A two-module simulator training, consisting of an insight-the-box model (basic tasks for eye-hand coordination), followed by a realistic lumbar spine model (execution of an endoscopic decompression) was developed. Course participants completed the e-learning before the hands-on training course. Course experience was evaluated through a standardized self-assessment questionnaire containing a 5-point Likert scale and a 10-point numeric rating scale. Results: Eleven of eighteen (61%) participants with different levels of professional education (62.5% residents in 1st -6th year of training, 37.5% board-certified) completed both trainings. Thirteen participants (72%) had no prior experience with UBE. The perception of knowledge after the e-learning module increased from 2.5 (SD 2) to 6.5 (SD 1.8; p = 0.039). The usefulness, enjoyment, and efficiency of the courses averaged a score of 8.0 (SD 1.8). Regarding the hands-on training, participants estimated an average increase in their skills from 2.9 (SD 1.8) to 6.8 (SD 2, p = 0.028). The overall rating of the two-module course was 7.9 (SD 2.2). Discussion and conclusion: Sequential e-learning and simulator training appear to be an effective educational adjunct to establish novel, MIS-techniques such as UBE. [ABSTRACT FROM AUTHOR]

The evaluation of quality in education has gained greater relevance, especially after the COVID-19 pandemic, which enhanced virtual learning and further highlighted the need for inclusive, equitable, and quality education in line with SDG 4. It has become indispensable to have evaluation models and tools supported by empirical validation to ensure their applicability and reliability in diverse educational contexts. This study addresses this need by validating a self-assessment guide designed to evaluate the quality of virtual education from an accessibility perspective. The validation process involved three phases: a preliminary phase with 4 experts to identify areas for improvement in the structure, clarity, and relevance of the content; an extended phase with 20 experts to evaluate reliability and validity; and a pilot study implemented in four higher-education institutions to verify the guide's applicability in real environments. Reliability and validity were assessed using standard psychometric techniques, confirming high internal consistency and content validity, although some areas required clarity adjustments. The findings indicate that this guide can serve as a robust tool for institutions aiming to advance accessible and high-quality virtual education, directly supporting SDG 4's commitment to inclusive education. [ABSTRACT FROM AUTHOR]

The integration of digital competences into higher education is essential for the promotion of effective and sustainable teaching and learning environments. The aim of this study was to develop and validate the Digital Competence Scale for University Teachers (DCS-UT), an instrument to assess key digital competences of teachers. The development of the scale involved the creation of items based on an extensive literature review, followed by rigorous testing for content and face validity. The psychometric properties of the scale were assessed using data from 411 university teachers, with confirmatory factor analysis (CFA) and structural equation modelling (SEM) to examine the underlying structure of the scale. Reliability was assessed using Cronbach's alpha, which confirmed the internal consistency of the instrument (0.974). The analysis revealed a robust four-factor structure: digital literacy, digital skills, digital interaction, and technology integration, which together explained 70.284% of the variance. These findings underscore the value of the DCS-UT as a tool to promote sustainable teaching practises by assessing digital competences. By equipping teachers with essential digital competences, the scale supports the long-term adaptability and effectiveness of higher education institutions in an increasingly digital field. [ABSTRACT FROM AUTHOR]

This study investigates the relationship between elementary school teachers' attitudes towards e-learning and their mental wellbeing in the Division of Quezon. Based in the Technology Acceptance Model (TAM) by Fred Davis and Seligman's PERMAH theory of wellbeing, the research explores how teachers' perceptions of the usefulness, ease of use, and overall acceptance of e-learning impact their emotional and psychological states. The data for this study were collected using a descriptive-correlational method from a randomly selected sample of 346 classroom teachers. The findings of this study reveal that teachers generally have positive attitudes towards e-learning, especially regarding personalized learning and flexibility. However, concerns about accessibility and affordability still exist. The scores for mental wellbeing indicate that teachers are generally coping well, showing high levels of positive emotions, engagement, meaning, relationships, and continuous personal growth. The study also found significant positive correlations between attitudes towards e-learning and mental wellbeing, particularly in relation to personalized learning and engagement. In conclusion, this study emphasizes the need for improved accessibility and engaging resources in e-learning. It recommends projects aimed at enhancing attitudes towards e-learning, comprehensive wellness programs, and ongoing technical support for teachers. Additionally, further research on barriers to effective e-learning implementation is suggested to enhance teacher training programs. Overall, this research highlights the importance of supporting teachers in both their adoption of e-learning and their mental wellbeing. It advocates for integrated approaches that can improve educational and personal outcomes. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic accelerated e-learning adoption, presenting both opportunities and challenges for educational development, particularly in the context of Information Technology for Development (ITD). This study profiles public sentiments on e-learning to identify key factors influencing IT-enabled education. A text analysis of Tweets from the United States and India posted from March 2020 to January 2022 was conducted using a computer-aided text analysis and natural language processing alongside a content analysis using a machine learning technique. Findings show positive sentiments towards e-learning from both countries, with trust, anticipation, and joy as predominant emotion categories. Themes of strongest importance are students, schools, and education as central to e-learning discussions. The study also uncovers challenges such as the need for internet infrastructure and teacher training in digital pedagogy. These findings contribute to the broader understanding of how information technologies can address educational challenges and promote development in diverse global contexts. [ABSTRACT FROM AUTHOR]

Machine learning (ML) methods are among the most promising technologies with wide-ranging research opportunities, particularly in the field of education, where they can be used to enhance student learning outcomes. This study explores the potential of machine learning algorithms to build and train models using log data from the "3D Modeling" e-course on the Moodle platform at TTK University of Applied Sciences, Tallinn, Estonia. By predicting trends, identifying patterns, and optimizing resource allocation, machine learning can improve the efficiency of e-learning and provide students with tailored recommendations for acquiring relevant knowledge and skills. The results of the study show that machine learning algorithms can be used to process the available e-course log data, using the clickstream of e-course resources and for their automated processing. The results suggest potential applications in personalized course recommendations, prediction and dropout prevention strategies, resulting in a more effective and personalized educational experience. Future research will focus on improving models of available registration data, exploring and using advanced machine learning techniques to improve the accuracy and usefulness of predictions, and providing faster recommendations to help students navigate their studies more effectively. [ABSTRACT FROM AUTHOR]

Introduction: Chronic kidney disease (CKD) affects a significant portion of the global population, with peritoneal dialysis (PD) being a common treatment option for end-stage renal disease. In Chile, the Metropolitan Region has a high prevalence of PD patients, necessitating the need for intraperitoneal catheter (IPC) installation. However, knowledge and training in minimally invasive techniques for IPC installation are lacking in the country. Objective: The objective of this study is to promote the use of a minimally invasive technique for IPC installation using a visual e-learning platform. Material and Method: A descriptive study was conducted, creating visual material illustrating the step-by-step process of IPC installation and removal. This visual material was detailed according to the surgical technique and linked to a QR code for easy access to further information. Results: The detailed description of the surgical technique, along with accompanying visual support through QR codes, provided efficient accessibility to information for IPC installation and removal. Conclusion: The use of a minimally invasive technique for IPC installation, coupled with e-learning methodology, can enhance the learning process for medical professionals seeking to perform laparoscopic peritoneal dialysis catheter insertions. [ABSTRACT FROM AUTHOR]

The study aims to capture and analyse the perception among students whether they perceive gamification in e-learning to significantly influence the learning parameters motivation to learn, student engagement, and perceived quality of learning and thereby subsequently impacting perceived satisfaction considering direct and mediation paths. The design adopts a two-step approach. Firstly, the constructs are identified through a rigorous literature review, and a conceptual framework is developed. Secondly, the instrument is developed, and data are collected through online form . The data from 409 respondents are collected, and the framework is tested using a Partial Least Square based Structural Equation Modelling (PLS-SEM). The findings demonstrated the importance of gamification in improving quality of learning, thereby enhancing perceived satisfaction (mediation). Also, the direct relationship between gamification on motivation and engagement on satisfaction was proved critical. Furthermore, student–faculty interaction significantly moderated the relationship between gamification and engagement. Empirical studies on learning parameters based on gamification have not been thoroughly investigated previously. The understanding of how gamification affects perceived satisfaction via direct and indirect pathways involving motivation, engagement, and learning quality adds a great deal to the body of knowledge. Decision-makers can rely on these insights to plan effective implementation of gamified e-learning systems. [ABSTRACT FROM AUTHOR]

Our critical historiography of e-learning policy in Ontario, Canada, traces the policy's trajectory through three settlements (2006-2022) and shows how successive governments have mobilized neoliberal discourses of personalization, access, and choice to justify new arrangements with private actors, within a broader sociopolitical context that includes increased privatization and commodification of public institutions, cuts to public spending, and imagines individuals as rational subjects driven to maximize their economic potential. This context exacerbates challenges students marginalized by schooling already face. Findings from our critical discourse analyses of government documents and news media reports also demonstrate that online learning in Ontario is neither personalized nor customizable but instead is centralized, standardized and, by design, operates independent of rather than interdependent with community. Further, our findings highlight the interdependence of schools – online and in-person – with social processes that create and perpetuate inequality, including gendered and racialized poverty, locally and abroad. [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]

In the context of 21st-century educational transformation, Massive Open Online Courses have emerged as a global and flexible learning opportunity. This study explores the impact of MOOC implemented at Instituto Super Técnico on student engagement and attendance, focusing on their effectiveness in higher education. A descriptive approach was applied, selecting three MOOC as the empirical field, combining quantitative data from participation logs and qualitative feedback from student surveys. The key characteristics, the challenges, and the effectiveness of educational resources were evaluated, particularly concerning student interaction and perceptions of course quality. The pedagogical analysis highlighted both successful strategies and areas for improvement. The findings offer valuable insights into the influence of MOOC on students and the institution, contributing to the broader understanding of Portugal's educational landscape. This study also proposes a framework for enhancing MOOC strategies in higher education globally, considering the potential of technological innovations in the 21st century. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to examine the effect of gamification on students' e-learning adoption. In addition, this paper examines the effect of two mediations, that is, flow and engagement between gamification and e-learning adoption by using sequential mediation analysis. Design/methodology/approach: The authors used the online survey method to collect the 570 responses through convenience sampling procedure. Sequential mediation analysis technique was used to test the mediation hypothesis. Findings: The findings of this paper revealed that gamification elements are an important feature of flow, engagement in e-learning adoption process. Also, the paper found that engagement in the learning process is a key element for students to adopt e-learning. Research limitations/implications: This paper makes its contribution to the literature related to gamification and e-learning adoption. The paper signifies the importance of gamification as an educational application in e-learning environment and its contribution in designing an interactive learning environment. Originality/value: Empirically, to the best of the authors' knowledge, it is the first paper to examine the sequential mediation model of gamification in the education sector in a developing nation like India. Furthermore, this paper also extends engagement and flow theory related to e-learning process by showing how students' engagement and flow impact the e-learning adoption in the gamified environment. [ABSTRACT FROM AUTHOR]

This pilot study is part of a larger "Decolonization of Digital Learning Spaces" project, which aims to develop research tools for communities that are remote and/or excluded geographically, politically, economically, socially, culturally, and linguistically. The project's ultimate goal is to work alongside these communities to design their own digital learning tools, networks, and online educational environments by accessing and leveraging their knowledge and skills. Testing the single-criterion card sorting method is the first step toward this goal. Card sorting is an easy, enjoyable, and cost-effective method for data collection and analysis, particularly for researchers working in remote areas with limited access to electricity or the Internet. The pilot explored singlecriterion card sorting as a method to elicit knowledge from two diverse cultural and linguistic groups engaged in learning activities within their communities. These groups were from a Deaf and Hard of Hearing (DHH) community in Canada (engaged in a bowmaking workshop) and a rural Kabyle community in Algeria (engaged in a traditional cooking lesson). Despite low participant numbers, distinct patterns emerged, indicating the method's effectiveness. The results, though anticipated, were non-random, demonstrating the potential of card sorting in producing patterns indicative of how individuals and/or communities categorize their world(s). Kabyle sortings focused on ingredients, highlighting older individuals as teachers passing along knowledge, while the DHH sortings emphasized face-to-face contact and hand movements in communication. The findings, though modest, established relationships, provided insights into the research context and offered logistical understanding, paving the way for further work with DHH and Kabyle communities towards the design of digital learning spaces. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal 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.)

The combination of face-to-face and online teaching, also called Blended learning (BL) has practically become one of the prevalent models of teaching and learning all over the world. Particularly, it has been applied as a new trend of using technology to concurrently combine in-class and out-of-class learning to optimize the educational impacts on students. However, BL is still quite a new learning model and has not been applied widely in teaching English in Vietnam. The current study was conducted to explore students’ perceptions of BL, the difficulties students think they have, and the percentage of face-to-face and online learning they prefer when learning in the BL environment. Sixty civil engineering students participating in the survey filled out a questionnaire after the forms of BL and the Learning Management System (LMS) Moodle had been introduced to them. The findings indicated that more than half of the participants were stimulated by BL and willing to take on the challenges. Nevertheless, some concerns about the lack of IT skills to fulfill the requirements of the BL course cannot be ignored. [ABSTRACT FROM AUTHOR]

Copyright of Arab Journal for Scientific Publishing is the property of Research & Development of Human Recourses Center (REMAH) 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 Djoussour El-maarefa is the property of Association of Arab Universities 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.)

Currently, online learning systems in the education sector are widely used and have become a new trend, generating large amounts of educational data based on students' activities. In order to improve online learning experiences, sophisticated data analysis techniques are required. Adding value to E-learning platforms through the efficient processing of big learning data is possible with Big Data. With time, the E-learning management system's repository expands and becomes a rich source of learning materials. Subject matter experts may benefit from using E-learning resources to reuse previously created content when creating online content. In addition, it might be beneficial to the students by giving them access to the pertinent documents for achieving their learning objectives effectively. An improved intelligent information retrieval and reliable storage (OIIRS) scheme is proposed for E-learning using hybrid deep learning techniques. Assume that relevant E-learning documents are stored in cloud and dynamically updated according to users' status. First, we present a highly robust and lightweight crypto, i.e., optimized CLEFIA, for securely storing data in local repositories that improve the reliability of data loading. We develop an improved butterfly optimization algorithm to provide an optimal solution for CLEFIA that selects private keys. In addition, a hybrid deep learning method, i.e., backward diagonal search-based deep recurrent neural network (BD-DRNN) is introduced for optimal intelligent information retrieval based on keywords rather than semantics. Here, feature extraction and key feature matching are performed by the modified Hungarian optimization (MHO) algorithm that improves searching accuracy. Finally, we test our proposed OIIRS scheme with different benchmark datasets and use simulation results to test the performance. [ABSTRACT FROM AUTHOR]

The importance of using accessible learning objects in order to ensure access to education for all students is notable. The present work sought to bring an overview of the research on accessible learning objects for the visually impaired based on the systematic literature review methodology. Then, 620 articles from five scientific databases were retrieved, of which 44 were considered for analysis. The results showed that the research question and sub-question were answered, and it was possible to perceive the support that distance education tools can provide if they are accessible. Finally, the various ways in which the researchers approached the accessibility of each learning object were identified and the more specific models, techniques and computational tools that exist and are used in the context of education were detected in order to promote accessibility for people with visual impairments. [ABSTRACT FROM AUTHOR]

The Indonesian Student Micro-Credentials Program implemented by Universitas Muhammadiyah Sumatera Utara (UMSU) carries 5 courses, all of which are carried out online, in a relatively short time within 2 months. The learning objectives, which are intended to create practical skills, require students to master the courses they follow, thus causing many problems, which have an impact on the satisfaction of the participants of this program. This study aims to measure the customer satisfaction index (CSI) of participants in this program. Of the 514 participants who were used as respondents, 279 respondents filled out the google formula, and the response rate was 54%. The results showed that the CSI value of the program was 0.85, which means that the participants were very satisfied with the implementation of this program at UMSU. Based on the assessment of it is quality, the dimension assessment is carried out in order of the highest average value, namely this program (4.48), interaction and flexibility (4.33), managers (4.24), lecturers (4.23), students (4.20), assessment (4.16), process (4.14), content design (4.15), partners (4.11), and technology (4.05). Based on the assessment of the level of importance or expectation of this program, the dimension assessment is carried out in order of the highest average value, namely this program (4.47), interaction and flexibility (4.38), managers (4.23), lecturers (4.22), process (4.17), content design (4.17), students (4.13), peer (4.13), assessment (4.11) and technology (4.04). [ABSTRACT FROM AUTHOR]

Using e-learning in higher education has many important benefits and advantages in todays world of education. Therefore, this research aims to develop e-learning based on the introduction, connection, application, reflection, extend (ICARE) learning model for developing teaching materials courses in the Faculty of Education, Universitas Pendidikan Ganesha. The Hannafin and Peck development model was adopted as a foundational method, and the digital content developed was subjected to formative evaluation methods, including i) expert validation, ii) individual assessment, and iii) small group evaluation. To ascertain the quality of the developed content, the research engaged 3 expert evaluators, each specializing in media, instructional design, and content. Concurrently, individual evaluation was carried out with 3 students, followed by a small group evaluation involving 9 additional students. Data collection techniques involved both observational measures and questionnaire-based inquiries. The expert assessment showed that the design, media, and content dimensions all fell within the "very good" category. Student reactions, as measured through both individual and small group evaluations, consistently aligned with the "very good" category. Therefore, the attractiveness and practicality of electronic learning (e-learning) fell under the "very good" classification, due to the implementation of the ICARE learning model as the foundational design principle. [ABSTRACT FROM AUTHOR]

This article describes the implementation of a digital case-exploration tool and its use in teacher education. The cases were constructed according to empirically based psychological theories and represent school-related scenarios in which the students could choose among options for action. After selecting an action, its psychological consequences are presented in text or video including theoretical explanations how and why the selected action would lead to the presented consequences. We present first quasi-experimental evaluation data demonstrating the tool's usefulness regarding learning outcomes, students' active participation, and motivation. [ABSTRACT FROM AUTHOR]

An online e-learning platform known as a learning management system (LMS) provides an interface between trainers, students, and administrators toward a common objective of learning. In the market, diverse LMSs with extensive functionalities are available to facilitate e-learning. In this article, we selected some popular LMSs majorly used by most schools and institutions for their teaching-learning process. We compared these LMSs in a discussion based on their technical specifications, technical features, administrative features, general features, and course management-related features. This comparative analysis could help users decide which LMS suits them best, according to their requirements. We also attempted to identify the limitations of these learning management systems so that users and organizations can determine which one is best suited to their needs. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has created a great challenge for educational systems worldwide. During this time, educational centers have been encouraged to use e-learning programs to protect the population against infection. Online teaching has the greatest effect on the process of teaching-learning for certain topics, including professional behavior and commitment, which has prompted educational systems to use creative strategies for a greater effect on learners. The present study aims to determine the effects of e-learning using educational multimedia on the ethical decision-making and professionalism of nursing students during the COVID-19 pandemic. Methods: This study was conducted using a quasi-experimental design with a control group. The statistical population comprised second-semester nursing students in a first-rank nursing school in north western Iran. The samples were selected using simple random sampling and were divided into experimental (n = 40) and control (n = 40) groups. In the first stage of teaching, the conventional training method of the COVID-19 pandemic was used in both groups. In the second stage of teaching, an in-person workshop was organized for the control group and an e-learning workshop using educational multimedia for the experimental group. Data were collected by a tool with three parts: Demographic information, the Nursing Dilemma Test (NDT) by Crisham based on the Nurse Principled Thinking, and the Nursing Students Professional Behaviors Scale (NSPBS) designed by Goz. Data were analyzed in SPSS 25 software. Results: There was a statistically significant increase in the post-test mean score of professionalism (125.70 ± 6.20 vs. 120.95 ± 9.28) and ethical decision-making (46.17 ± 3.81 vs. 44.02 ± 3.21) in the experimental group compared to the control group (P < 0.05). Conclusion: The learning environment affects learning, and e-learning using educational multimedia has a greater impact than in-person workshops on improved learning outcomes with regard to ethical decision-making and professionalism. [ABSTRACT FROM AUTHOR]

Information technology advancements have facilitated the widespread adoption of online education, providing learners with more flexible and convenient means of accessing educational resources and completing learning tasks. To improve the quality of online education and promote collaborative learning, online assessment is crucial in this transition. However, there are concerns about the transparency of the existing online assessment system. Centralized control by educational authorities restricts user access to the assessment process, resulting in a lack of user trust in assessment outcomes. Moreover, the abundance of online users also raises concerns about the reliability of assessors. In this paper, we present AssessChain, a decentralized system that integrates hybrid blockchains to make all assessment procedures, including set criteria, feedback, calculation, and moderation, visible and verifiable to users. Besides, AssessChain introduces an assessor selection scheme (ASEL) employing an enhanced density clustering algorithm to ensure the reliability of assessors, avoiding low-quality feedback. We have implemented the system and proved that the performance is reasonable in terms of throughput and latency, and the proposed ASEL can generally identify malicious assessors with more than 95% accuracy. By integrating information technology, the system encourages all educational participants to trust the assessment process and results, which helps promote equity in educational assessment. [ABSTRACT FROM AUTHOR]

The integration of digital technologies into educational practices has reshaped traditional learning models, creating a dynamic and accessible global landscape for higher education. This paradigm shift transcends geographical boundaries, fostering a more interconnected and inclusive educational environment. This comprehensive literature analysis explores the impact of e-learning on higher education students in the digital era. A meticulous review of 53 studies, sourced from reputable databases including Web of Science, Taylor & Francis, Springer Link, ProQuest, Elsevier, and Scopus, was conducted. Employing the content analysis method, the selected studies spanning from November 2012 to April 2023 were systematically examined. Predominantly utilizing quantitative methods, the studies, largely originating from the United States, China, Malaysia, and India, focused on university students. Key variables such as student engagement, perception, and academic performance were consistently employed across diverse educational settings. The synthesis of findings revealed that e-learning technologies positively impacted academic achievement, student satisfaction, and collaborative efforts. Moreover, challenges associated with technology usage and internet access were identified, which impact e-learning implementation. The study proposes further investigation through a mixed-methods approach to explore students' interactions with the educational environment while utilizing e-learning technology in institutions of higher education. [ABSTRACT FROM AUTHOR]

This study analyzes the effectiveness of a chatbot in enhancing online learning, addressing the lack of support in traditional online courses. Two questionnaires were administered to participants, providing qualitative data on various aspects of the learning experience. The first questionnaire measured satisfaction, engagement, self-regulation and usefulness in three different groups of participants. The second questionnaire included open-ended questions and Likert scale items, gathering qualitative feedback and perceptions specifically from the group that used the chatbot. Additionally, this study incorporates quantitative analysis to evaluate the chatbot's impact on learning outcomes and student engagement. We used ANOVA to test whether there is a significant difference in learning outcomes among the three experimental groups. To determine which groups have significantly different means, we performed the Tukey post hoc test. Analysis of the data collected aims to measure the impact of chatbot integration on learner satisfaction, engagement, self-regulation, learning outcomes, usefulness and usability. The results contribute to the understanding of chatbots as support tools in e-learning environments, and indicate that the integration of chatbots within e-learning platforms aims to improve the learning experience and foster learner success. [ABSTRACT FROM AUTHOR]

AbstractThe COVID-19 pandemic has disrupted traditional classroom learning in Nigerian universities and prompted the adoption of e-learning as an alternative means of delivering academic content. This research paper aimed to explore the experience of undergraduate students in Nigerian universities during the post-COVID era, with a specific focus on the effectiveness of e-learning. This study employed a quantitative approach. The study population consisted of 237 undergraduate students from seven selected universities in Nigeria. The data was collected using a structured questionnaire. The findings of this study showed that while e-learning has its advantages, it also presents several challenges to undergraduate students in Nigerian universities. Some of the challenges include poor internet connectivity, lack of access to electronic devices, and insufficient training on how to use e-learning platforms. The study recommends that Nigerian universities and the government should invest in improving internet connectivity and power supply to support e-learning; and institutions should provide consistent and comprehensive technical support to all students, ensuring they have the necessary resources and assistance. [ABSTRACT FROM AUTHOR]

This study investigates user satisfaction with e-learning systems in higher education institutions, examining the perspectives of students, lecturers, and elearning officers and heads of the department of Information Technology as key informants. A total of 375 student respondents from Diploma, Bachelor, and Masters levels, 51 lecturers, and 15 key informants across different Ugandan institutions of higher learning participated in the study, providing insights into platform usage, system usability, stability, and support mechanisms. Rigorous analysis techniques, including means, correlation coefficient calculations, were employed to explore factors influencing satisfaction. Findings revealed positive correlations between satisfaction and variables such as ease of use, ease of access, system reliability, system stability, and prompt response to queries, among others. Recommendations include improving system stability, enhancing response time to queries, providing ongoing training, addressing connectivity issues, and developing customized mobile applications. The study highlights the need for institutions to optimize e-learning experiences by leveraging feedback from users and implementing targeted interventions. [ABSTRACT FROM AUTHOR]