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Добірка наукової літератури з теми "Online learning methods"

Автор: Grafiati

Опубліковано: 26 квітня 2025

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Статті в журналах з теми "Online learning methods"

Tarasenko, M. "ONLINE LEARNING: INTERACTIVE METHODS." Pedagogy of the formation of a creative person in higher and secondary schools 2, no. 77 (2021): 49–53. http://dx.doi.org/10.32840/1992-5786.2021.77-2.9.

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Tekin, Cem, and Mingyan Liu. "Online Learning Methods for Networking." Foundations and Trends® in Networking 8, no. 4 (2013): 281–409. http://dx.doi.org/10.1561/1300000050.

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Salmons, Janet. "Case methods for online learning." eLearn 2003, no. 6 (June 2003): 2. http://dx.doi.org/10.1145/863928.863932.

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PRASETYA, Prita, and Sekar Wulan PRASETYANINGTYAS. "LEARNING STATISTICAL METHODES WITH ONLINE ONLINE COURSE." ICCD 3, no. 1 (October 27, 2021): 312–15. http://dx.doi.org/10.33068/iccd.vol3.iss1.368.

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Анотація:

Today's business has become something complex. Various factors interact with each other and make business unpredictable. Research is an effort to develop knowledge, develop and test theories. The research objective is an effort to develop knowledge, develop and test the theory. Research activities in practice are likely to include multidisciplinary research and a combination of the application of multiple research methods. In practice, research can be carried out in multi-disciplinary and is a combination of several research methods. The function of research is to find explanations and answers to problems and to provide alternatives to the possibilities that can be used to solve the problem. On that basis, a systematic method is needed in overcoming various problems that arise in the business. The business research method is a systematic method that is useful for researching various aspects related to business. Statistics and research methods training aims to provide a better understanding of business research. The research methods discussed in this training are Structural Equation Modeling (SEM) and Soft System Methodology (SSM). This community service activity produces changes following the set output targets, increasing participant knowledge to help compile business research. The results of the evaluation of the implementation of training in business research methods for students, lecturers, researchers, and practitioners, show that the level of understanding becomes better after attending the training and has the motivation to conduct research with quantitative and qualitative approaches. Participants can also run the SEM LISREL application independently.

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Vilkhovchenko, Nadiia P. "ESP distance learning methods At technical universities." Bulletin of Alfred Nobel University Series "Pedagogy and Psychology» 1, no. 23 (June 2022): 116–23. http://dx.doi.org/10.32342/2522-4115-2022-1-23-14.

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The paper focuses on the urgent problems of linguadidactics caused by Covid-19 pandemic and the need to implement online learning at all Ukrainian institutions of higher learning. English for Specific Purposes online learning involves modern methods that are constantly being improved. They are aimed at effective interaction of all participants in the learning process. The Department of Foreign Languages in Lviv polytechnic national university analyzed the feedback from the teaching staff and students concerning methods applied in online classes which were held during the quarantine period in 2020–2021. Observations of teaching experience, as well as the positive feedback from students proved that online learning English for specific purposes can be as effective as the offline one. The study considers a number of important principles that should be followed in order to succeed in distance learning. English for Specific Purposes online tools involved both synchronous and asynchronous methods. The former methods included videoconferences held with the help of various applications, e.g. Zoom, Microsoft Teams, Google Meet etc. Asynchronous means consisted of using instant messengers, email, educational platforms, i.e. virtual learning environment of the university based on the Moodle platform. We conducted a survey among students of five groups of different technical specialties. The survey aimed at finding out their opinion concerning effectiveness of ESP online lessons. It helped to discover what kind of difficulties the students had faced. The survey also allowed us to understand which types of activities were better perceived during video conferences in comparison with lessons in the classroom (i.e. listening and watching video). The analysis of the results obtained brought us to a conclusion about the most efficient way of conducting online classes. Thus, a combination of asynchronous and synchronous methods appeared to be the most effective tool for online mastering of ESP. On the one hand, the asynchronous method can be effective to consolidate lexical and grammar material, as well as develop reading skills. On the other hand, synchronous method provides direct communication in the «student-teacher» format and is the most effective means of transmission and acquiring new knowledge in the discipline of English for Specific Purposes. It also develops speaking skills while involving students in work with breakout rooms. The paper also discusses the issue of students’ knowledge and skills assessment. The process of control has become automated and, thus, more convenient. Diagnostic and control works were performed in the form of current and final tests, hosted on the Moodle platform (virtual learning environment of Lviv Polytechnic National University). This greatly facilitates teacher’s work; as such tests contain a convenient option of automatic checking the correctness of students’ answers to the tests.

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Rini, Hesty Prima, and Dewi Khrisna Sawitri. "Effectiveness of Online Learning: The Learning Methods and Media." Ilomata International Journal of Social Science 3, no. 1 (February 10, 2022): 330–39. http://dx.doi.org/10.52728/ijss.v3i1.389.

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Online distance learning has been implemented as the most possible alternative at this time for continuous learning while maintaining a distance to prevent the spread of the corona virus and obeying the rules not to gather in one place. Research was conducted to investigate the effectiveness of online learning by distributing questionnaire through the google form link. Data were obtained from 112 students related to media and learning methods that support the implementation of effective online learning . The result showed that 71% or 80 students mentioned that online learning at their university is effective. Blended Learning which is a combination of system synchronous learning and asynchronous learning is chosen by the majority of respondents. Related with the learning media, the use of google meet is the most popular learning media because apart from being able to be used as a medium in synchronous learning, it can also be used in the synchronous learning through Google classroom.

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Tîrziu, Andreea-Maria, and Cătălin I. Vrabie. "NET Generation. Thinking outside the box by using online learning methods." New Trends and Issues Proceedings on Humanities and Social Sciences 2, no. 7 (January 27, 2016): 41–47. http://dx.doi.org/10.18844/gjhss.v2i7.1178.

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Sampe, Maria Zefanya, and Syafrudi Syafrudi. "ONLINE MATHEMATICS LEARNING STRATEGY APPROACH: TEACHING METHODS AND LEARNING ASSESSMENT." Jurnal Pendidikan Matematika (JUPITEK) 7, no. 1 (July 7, 2024): 42–55. http://dx.doi.org/10.30598/jupitekvol7iss1pp42-55.

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The primary focus of this research is to develop strategies aimed at identifying effective methods applicable to online mathematics instruction and assessment. Teaching through distance education has many challenges, requiring educators' adeptness in utilizing e-learning platforms for both instructional delivery and assessment purposes. This study adopts a literature review methodology, drawing upon various previous studies relevant to this subject matter. The research findings reveal several online mathematical strategies and assessment techniques envisioned to adequately measures students' capacity to discern complex issues and employ critical thinking to resolve mathematical problems. The important role of the educator as a facilitator is underscored in crafting learning materials synchronized to the needs of students navigating the online platform. In this context, online mathematics instructional strategies are intricately intertwined with pedagogical dimensions and the appropriateness of utilized media and assessment modalities. Emphasizing interactive, creative, and innovative learning emerges as a critically important characteristic, particularly within the realm of online mathematics instruction

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Loi, Chek Kim, Jason Miin Hwa Lim, Norazah Mohd Suki, and Hock Ann Lee. "Exploring University Students’ Online Learning Readiness: A Mixed Methods Study of Forced Online Learning." Journal of Language and Education 10, no. 1 (March 30, 2024): 49–67. http://dx.doi.org/10.17323/jle.2024.16016.

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Background: Despite the advancement achieved in previous research into online learning, few studies have used both quantitative and qualitative data to examine how students’ readiness to learn online is affected by three different external factors, comprising (i) the degrees to which technology is available to students, (ii) the support provided by the institutions of learning, and (iii) the social influence affecting the students engaged in forced online learning in a pandemic situation. Purpose: To fill this research gap, this study explored university students’ forced online learning readiness in relation to technological accessibility, institutional support and social influence during a pandemic, in an attempt to furnish insights into how educators can maximize the benefits of adopting online learning methods. Method: A mixed methods research design was employed in this study. Quantitative data, elicited via self-administered questionnaires completed by 211 participants, was analyzed using the frequencies, means, standard deviations and Pearson correlation analysis involving the Statistical Package for the Social Sciences (SPSS) software version 27. Qualitative data, elicited via 11 open-ended questions posed to 41 students through in-depth interviews, was then studied using a thematic analysis of the participants’ feedback concerning the three constructs in online learning. Results: Our quantitative analysis showed that institutional support had the strongest positive correlation with online learning readiness, and this was followed by technology accessibility and social influence in relation to students’ readiness to learn online. Qualitative findings further indicated that students were largely concerned about Internet accessibility and the setting where their roles were restricted to being mere listeners in online sessions. Apart from being apprehensive about excessive online assignments, students also acknowledged that their online interactions were influenced by their friends and family members, and they would prefer practical work that could inspire them to reflect and engage actively with the course material given during the pandemic. Conclusion: While lecturers can make online classes more interactive and discussion-generative, university administrators need to aptly facilitate their institution’s transition to the forced online learning mode, moderate social influence, improve the learning management system, and provide training to teachers and students on the use of emerging technology.

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NF, Jhoanita, and Siti Khadijah. "PARENTS’ PERCEPTIONS OF ONLINE LEARNING METHODS: A QUANTITATIVE STUDY." Makna: Jurnal Kajian Komunikasi, Bahasa, dan Budaya 10, no. 1 (March 9, 2022): 21–30. http://dx.doi.org/10.33558/makna.v10i1.3242.

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Online learning may alienate some students as they may be not familiar with it or face some problems such as students’ lack of concentration during online learning, poor internet services, the lack of suitable gadgets to access online learning. Parents, as ones who are responsible for the learning process of their children during online learning may be burdened with online learning approach. Therefore, it seems important to analyze the parents’ perceptions toward online learning to understand their concerns on the efficacy of online learning process. The present study uses a quantitative approach by distributing a set of questionnaires to 90 parents from a private school in Cirebon, Indonesia. The results of present study show that parents have relatively positive perceptions toward online learning. It can be said that online learning may have some merits toward students’ learning progress.

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Більше джерел

Дисертації з теми "Online learning methods"

Qin, Lei. "Online machine learning methods for visual tracking." Thesis, Troyes, 2014. http://www.theses.fr/2014TROY0017/document.

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Nous étudions le problème de suivi de cible dans une séquence vidéo sans aucune connaissance préalable autre qu'une référence annotée dans la première image. Pour résoudre ce problème, nous proposons une nouvelle méthode de suivi temps-réel se basant sur à la fois une représentation originale de l’objet à suivre (descripteur) et sur un algorithme adaptatif capable de suivre la cible même dans les conditions les plus difficiles comme le cas où la cible disparaît et réapparait dans le scène (ré-identification). Tout d'abord, pour la représentation d’une région de l’image à suivre dans le temps, nous proposons des améliorations au descripteur de covariance. Ce nouveau descripteur est capable d’extraire des caractéristiques spécifiques à la cible, tout en ayant la capacité à s’adapter aux variations de l’apparence de la cible. Ensuite, l’étape algorithmique consiste à mettre en cascade des modèles génératifs et des modèles discriminatoires afin d’exploiter conjointement leurs capacités à distinguer la cible des autres objets présents dans la scène. Les modèles génératifs sont déployés dans les premières couches afin d’éliminer les candidats les plus faciles alors que les modèles discriminatoires sont déployés dans les couches suivantes afin de distinguer la cibles des autres objets qui lui sont très similaires. L’analyse discriminante des moindres carrés partiels (AD-MCP) est employée pour la construction des modèles discriminatoires. Enfin, un nouvel algorithme d'apprentissage en ligne AD-MCP a été proposé pour la mise à jour incrémentale des modèles discriminatoires
We study the challenging problem of tracking an arbitrary object in video sequences with no prior knowledge other than a template annotated in the first frame. To tackle this problem, we build a robust tracking system consisting of the following components. First, for image region representation, we propose some improvements to the region covariance descriptor. Characteristics of a specific object are taken into consideration, before constructing the covariance descriptor. Second, for building the object appearance model, we propose to combine the merits of both generative models and discriminative models by organizing them in a detection cascade. Specifically, generative models are deployed in the early layers for eliminating most easy candidates whereas discriminative models are in the later layers for distinguishing the object from a few similar "distracters". The Partial Least Squares Discriminant Analysis (PLS-DA) is employed for building the discriminative object appearance models. Third, for updating the generative models, we propose a weakly-supervised model updating method, which is based on cluster analysis using the mean-shift gradient density estimation procedure. Fourth, a novel online PLS-DA learning algorithm is developed for incrementally updating the discriminative models. The final tracking system that integrates all these building blocks exhibits good robustness for most challenges in visual tracking. Comparing results conducted in challenging video sequences showed that the proposed tracking system performs favorably with respect to a number of state-of-the-art methods

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Kovanovic, Vitomir. "Assessing cognitive presence using automated learning analytics methods." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/28759.

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Анотація:

With the increasing pace of technological changes in the modern society, there has been a growing interest from educators, business leaders, and policymakers in teaching important higher-order skills which were identified as necessary for thriving in the present-day globalized economy. In this regard, one of the most widely discussed higher order skills is critical thinking, whose importance in shaping problem solving, decision making, and logical thinking has been recognized. Within the domain of distance and online education, the Community of Inquiry (CoI) model provides a pedagogical framework for understanding the critical dimensions of student learning and factors which impact the development of student critical thinking. The CoI model follows the social-constructivist perspective on learning in which learning is seen as happening in both individual minds of learners and through the discourse within the group of learners. Central to the CoI model is the construct of cognitive presence, which captures the student cognitive engagement and the development of critical thinking and deep thinking skills. However, the assessment of cognitive presence is challenging task, particularly given its latent nature and the inherent physical and time separation between students and instructors in distance education settings. One way to address this problem is to make use of the vast amounts of learning data being collected by learning systems. This thesis presents novel methods for understanding and assessing the levels of cognitive presence based on learning analytics techniques and the data collected by learning environments. We first outline a comprehensive model for cognitive presence assessment which builds on the well-established evidence-cantered design (ECD) assessment framework. The proposed assessment model provides a foundation of the thesis, showing how the developed analytical models and their components fit together and how they can be adjusted for new learning contexts. The thesis shows two distinct and complementary analytical methods for assessing students’ cognitive presence and its development. The first method is based on the automated classification of student discussion messages and captures learning as it is observed in the student dialogue. The second analytics method relies on the analysis of log data of students’ use of the learning platform and captures the individual dimension of the learning process. The developed analytics also extend current theoretical understanding of the cognitive presence construct through data-informed operationalization of cognitive presence with different quantitative measures extracted from the student use of online discussions. We also examine methodological challenges of assessing cognitive presence and other forms of cognitive engagement through the analysis of trace data. Finally, with the intent of enabling for the wider adoption of the CoI model for new online learning modalities, the last two chapters examine the use of developed analytics within the context of Massive Open Online Courses (MOOCs). Given the substantial differences between traditional online and MOOC contexts, we first evaluate the suitability of the CoI model for MOOC settings and then assess students’ cognitive presence using the data collected by the MOOC platform. We conclude the thesis with the discussion of practical application and impact of the present work and the directions for the future research.

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Johnson, Alicia Leinaala. "Exploration of Factors Affecting the Self-Efficacy of Asynchronous Online Learners: a Mixed Methods Study." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/77518.

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Анотація:

This study explored former and current graduate and undergraduate online students' self-efficacy perceptions for asynchronous online coursework. Self-efficacy is described as a person's judgment of his or her ability to successfully complete a learning or performance task (Bandura, 1997). Using an exploratory sequential mixed methods approach, this study explored the research question in three phases: 1) Conducted interviews and analyzed transcripts of 11 current and previous asynchronous online learners; 2) Created and enlisted the expert review of a survey instrument developed from the interview data analysis; and 3) Collected and analyzed survey responses from current and previous asynchronous online learners. The findings from this research show, based on 215 participant responses, several factors present or absent in asynchronous online learning experiences have positive, negative or no effects on perceived self-efficacy to complete online course requirements. Findings, limitations, practical implications and future research ideas are discussed in Chapter Six of this document.
Ph. D.

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Conesa, Gago Agustin. "Methods to combine predictions from ensemble learning in multivariate forecasting." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-103600.

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Making predictions nowadays is of high importance for any company, whether small or large, as thanks to the possibility to analyze the data available, new market opportunities can be found, risks and costs can be reduced, among others. Machine learning algorithms for time series can be used for predicting future values of interest. However, choosing the appropriate algorithm and tuning its metaparameters require a great level of expertise. This creates an adoption barrier for small and medium enterprises which could not afford hiring a machine learning expert to their IT team. For these reasons, this project studies different possibilities to make good predictions based on machine learning algorithms, but without requiring great theoretical knowledge from the users. Moreover, a software package that implements the prediction process has been developed. The software is an ensemble method that first predicts a value taking into account different algorithms at the same time, and then it combines their results considering also the previous performance of each algorithm to obtain a final prediction of the value. Moreover, the solution proposed and implemented in this project can also predict according to a concrete objective (e.g., optimize the prediction, or do not exceed the real value) because not every prediction problem is subject to the same constraints. We have experimented and validated the implementation with three different cases. In all of them, a better performance has been obtained in comparison with each of the algorithms involved, reaching improvements of 45 to 95%.

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Häglund, Emil. "Estimating Prediction Intervals with Machine Learning and Monte Carlo Methods in Online Advertising." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-282826.

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Online advertising presents a complex environment. The vast amount of available websites, platforms and formats as well as the trend of programmatic adpurchasing makes assessing a proposed advertisement in terms of cost and expected return challenging. This paper uses machine learning to predict cost per thousand impressions (CPM), a measure of advertising efficiency, for a planned purchase. Feedforward neural networks and random forest models were compared on their ability to produce CPM point estimates and prediction intervals. To estimate prediction intervals, Monte Carlo dropout and noise estimation was employed for the neural network models. For random forest, a Monte Carlo approach where a large number of models were parameterized using bootstrap sampling was employed. Implemented algorithms were compared using the 5x2cv test. Random forest and neural network models produced similar point estimation accuracy. To obtain valid prediction intervals in terms of coverage probability for the random forest algorithm, hyperparameters had to be adjusted to increase the tree-level variance. This negatively affected the accuracy of point estimates and the random forest prediction intervals were less optimal than those produced by the neural network algorithm. This difference in performance was statistically supported by the 5x2cv test. It is concluded that both evaluated random forest and neural network algorithms for prediction intervals produced valid intervals although neural network estimates were more optimal.
Reklam på nätet är en komplex miljö. Mängden hemsidor, plattformar och format såväl som trenden med programmatiska reklamköp gör det svårt att utvärdera planerad reklam beträffande förväntad kostnad och värde. Den här rapporten använder maskininlärning för att prediktera kostnaden för tusen visningar (CPM), ett mått på annonseringseffektivitet, för ett planerat reklamköp. Random forest och neurala nätverksmodeller jämfördes med avseende på deras förmåga att producera punktskattningar och prediktionsintervall. För att skatta prediktionsintervall för neurala nätverk användes Monte Carlo dropout och skattning av datamängdens brusnivå. För random forest användes en Monte Carlo metod där ett stort antal modeller parametriseras med bootstrapping. Implementerade algoritmer jämfördes med 5x2cv test. Random forest och neural nätverksmodellerna producerade liknande precision för punktskattningar. För att erhålla giltiga prediktionsintervall avseende täckningssannolikhet för random forest krävdes det att parametrar justerades för att öka de enskilda beslutsträdens varians. Detta påverkade precisionen för punktskattningar negativt och prediktionsintervallen för random forest var mindre optimala än de som skattades av neurala nätverksalgoritmen. Denna skillnad i förmåga att skatta prediktionsintervall bekräftades statistiskt av 5x2cv testet.

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Wright, Robert Demmon. "Students' Attitudes Towards Rapport-building Traits and Practices in Online Learning Environments." Thesis, University of North Texas, 2012. https://digital.library.unt.edu/ark:/67531/metadc177265/.

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This research was a triangulated study of student attitudes towards instructors' rapport-building traits and their preferences amongst instructors' rapport-building practices in online learning environments. Participants were undergraduate and graduate students enrolled in courses within an educational technology program at a central Texas university. The study employed a mixed-methods approach involving the Likert-item assessment of learners' attitudes, the identification and prioritization of learner preferences through pairwise comparisons, and semi-structured interviews that provided richer, more detailed information. Findings indicated a strong preference for instructor-based traits and practices over pedagogically-based ones. These traits and practices loaded into the components of social presence, enjoyable interaction, and personal connection.

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Luca, Joseph. "Developing generic skills for tertiary students in an online learning environment." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2002. https://ro.ecu.edu.au/theses/713.

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Анотація:

Increasingly, higher education institutions are being asked by industry, government and funding bodies to produce graduates with versatile generic skills as well as subject knowledge and expertise. This is causing a major reappraisal of higher education institutions purpose, learning outcomes and research activities. Many institutions are experiencing problems in implementing effective teaching and learning strategies to promote the development of these skills. The study sought to investigate ways of developing students' generic skills through the design and implementation of a learning environment that incorporated three key learning principles - authenticity, self-regulation and reflection. These were integrated into a course design methodology that focused on creating appropriate learning tasks for the given course objectives. The development of learning resources and supports was considered only after key learning tasks had been established for the given context. Using this instructional strategy, a learning environment was created using both face-to- face and online delivery, and tested with a class of final year higher education students. Eleven generic skills were identified as being important for these students. These included - time management, learning-to-learn, self-assessment, leadership, collaboration, communication, peer-assessment, research, analysis/ synthesis, problem solving and task management. A range of data was collected and analysed by triangulating various qualitative and quantitative research methodologies that provided a rich representation of how the students engaged with the learning activities. Results showed that the design of the learning environment was effective in promoting the development of these generic skills, and that the authentic activities were instrumental in motivating students. Once motivated, students then actively engaged with self-directed and reflective activities, which helped construct knowledge and promote generic skill development. The major implication of the study is that generic skill development and deep approaches to learning can be achieved without having to take extra time to specifically teach these skills. Developing generic skills becomes a natural consequence of students actively engaging with learning tasks that are authentic, student-centred and reflective. Using this approach to teaching and learning, course coordinators need to consider which generic skills should be targeted at different year levels to cover the necessary skills.

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Cunningham, E. Ann. "Comparison of Student Success by Course Delivery Methods at an Eastern Tennessee Community College." Digital Commons @ East Tennessee State University, 2015. https://dc.etsu.edu/etd/2585.

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Анотація:

The purpose of this study was to compare academic success based on methods of course delivery for students in a computer applications course at an East Tennessee community college. Additionally, the researcher examined demographic relationships of age, gender, and race to student academic performance in the different delivery methods. The researcher used final course grades as a determinant of academic success. The study was focused on students who took the INFS 1010 Computer Applications course during the academic years, 2011-12, 2012-13, and 2013-14 at a southeast Tennessee community college. The population consisted of 1,177 students who took the INFS 1010 Computer Applications course over a 3-year period. The independent variable method of course delivery is generally defined as traditional, online, or blended. The dependent variable academic success is generally defined as final course grade. A student was considered an academically successful completer of the course by attaining a final course grade of A, B, C, or D. It should be noted that if a student is transferring to another institution, the receiving institution may or may not accept the course credit of a student who received a D grade in this course. However, at the studied institution students receiving final course grades of A, B, C, or D in INFS 1010 are considered successful course completers. The research questions in this study were addressed through data analysis with Chi-Square 2-way contingency table analysis testing procedures. When areas of significance were identified, follow-up pairwise comparisons were conducted to evaluate relationships between the proportions. The quantitative findings revealed no significant overall relationships in final course grades among the 3 delivery methods. However, some relationships were noted within delivery methods by demographic characteristics. The findings of the online delivery method indicated significant relationships among all 3 demographic categories (gender, age, and race) studied. Significant grade relationships were identified in the gender and race categories within the blended delivery method. However, within the traditionally delivered sections of this course the only demographic area with significant findings was the age category.

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Joshi, Apoorva. "Trajectory-based methods to predict user churn in online health communities." Thesis, University of Iowa, 2018. https://ir.uiowa.edu/etd/6152.

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Online Health Communities (OHCs) have positively disrupted the modern global healthcare system as patients and caregivers are interacting online with similar peers to improve quality of their life. Social support is the pillar of OHCs and, hence, analyzing the different types of social support activities contributes to a better understanding and prediction of future user engagement in OHCs. This thesis used data from a popular OHC, called Breastcancer.org, to first classify user posts in the community into the different categories of social support using Word2Vec for language processing and six different classifiers were explored, resulting in the conclusion that Random Forest was the best approach for classification of the user posts. This exercise helped identify the different types of social support activities that users participate in and also detect the most common type of social support activity among users in the community. Thereafter, three trajectory-based methods were proposed and implemented to predict user churn (attrition) from the OHC. Comparison of the proposed trajectory-based methods with two non-trajectory-based benchmark methods helped establish that user trajectories, which represent the month-to-month change in the type of social support activity of users are effective pointers for user churn from the community. The results and findings from this thesis could help OHC managers better understand the needs of users in the community and take necessary steps to improve user retention and community management.

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Tunningley, Joan M. "Self-Regulated Learning and Reflective Journaling in an Online Interprofessional Course: A Mixed Methods Study." University of Cincinnati / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1511799445626182.

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Книги з теми "Online learning methods"

plc, Epic Group, ed. Methods: A practical guide to the methods used in online learning. Brighton: Epic Group, 1999.

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A, Fisher Cheryl, and Rietschel Matthew J, eds. Developing online learning environments in nursing education. 3rd ed. New York, NY: Springer, 2014.

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1966-, Lindberg J. Ola, and Olofsson Anders D. 1973-, eds. Online learning communities and teacher professional development: Methods for improved education delivery. Hershey, PA: Information Science Reference, 2010.

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1966-, Lambropoulos Niki, and Romero Margarido 1980-, eds. Educational social software for context-aware learning: Collaborative methods and human interaction. Hershey, PA: Information Science Reference, 2010.

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Loke, Jennifer C. F. Critical discourse analysis of interprofessional online learning in health care education. Hauppauge, N.Y: Nova Science Publishers, 2011.

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Conceição, Simone C. O., 1963-, ed. Motivating and retaining online students: Research-based strategies that work. San Francisco, CA: Jossey-Bass, a Wiley brand, 2014.

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Tekin and Mingyan Liu. Online Learning Methods for Networking. Now Publishers, 2015.

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LOK, Johnny Ch. Advantages Comparision Between Classroom and Online Learning Methods. Independently Published, 2020.

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Частини книг з теми "Online learning methods"

Bartz-Beielstein, Thomas. "Special Requirements for Online Machine Learning Methods." In Online Machine Learning, 63–69. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-7007-0_6.

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Conceição, Simone C. O., and Susan M. Yelich Biniecki. "Closed and Open Online Discussion Forums." In Methods for Facilitating Adult Learning, 316–32. New York: Routledge, 2024. http://dx.doi.org/10.4324/9781003446019-25.

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Mittelman, Rachel J. "Overcoming Resistance to Teaching History Online and Methods of Engagement." In Teaching and Learning History Online, 7–14. New York: Routledge, 2023. http://dx.doi.org/10.4324/9781003258414-3.

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Gunawardena, Charlotte Nirmalani, Nick V. Flor, and Damien M. Sánchez. "Social Construction of Knowledge (SCK) Platforms, Scraping, and Methods." In Knowledge Co-Construction in Online Learning, 70–77. New York: Routledge, 2025. https://doi.org/10.4324/9781003324461-7.

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Ray, Asmita, Vishal Goyal, and Samir Kumar Bandyopadhyay. "Student Stress Detection in Online Learning During Outbreak." In Computational Methods in Psychiatry, 259–81. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6637-0_13.

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Gunawardena, Charlotte Nirmalani, Nick V. Flor, and Damien M. Sánchez. "Social Learning Analytic Methods (SLAM) for Examining Online Social Dynamics." In Knowledge Co-Construction in Online Learning, 57–69. New York: Routledge, 2025. https://doi.org/10.4324/9781003324461-6.

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Park, Sunyoung, Boreum (Jenny) Ju, and Shinhee Jeong. "Adopting Massive Open Online Courses (MOOCs) in Adult Learning Contexts." In Methods for Facilitating Adult Learning, 333–49. New York: Routledge, 2024. http://dx.doi.org/10.4324/9781003446019-26.

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Siska, Jumiati, Meydia Afrina, Sudarwan Danim, and Agus Susanta. "The Effectiveness of Demonstrative Learning Methods in Improving Students’ Learning Outcomes." In Online Conference of Education Research International (OCERI 2023), 319–25. Paris: Atlantis Press SARL, 2023. http://dx.doi.org/10.2991/978-2-38476-108-1_31.

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Katiyar, Kalpana, Hera Fatma, and Simran Singh. "Student’s Stress Detection in Online Learning During the Outbreak." In Computational Methods in Psychiatry, 335–48. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6637-0_16.

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Oiwa, Hidekazu, Shin Matsushima, and Hiroshi Nakagawa. "Frequency-Aware Truncated Methods for Sparse Online Learning." In Machine Learning and Knowledge Discovery in Databases, 533–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23783-6_34.

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Тези доповідей конференцій з теми "Online learning methods"

Atia, Hend Abdelbakey, Magdy Aboul-Ela, Christina Albert Reyad, and Nancy Awadallah Awad. "Online Payments Fraud Detection Using Machine Learning Techniques." In 2024 Intelligent Methods, Systems, and Applications (IMSA), 402–9. IEEE, 2024. http://dx.doi.org/10.1109/imsa61967.2024.10652834.

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Zhang, Hao, Liang Huang, Kai Zhao, and Ryan McDonald. "Online Learning for Inexact Hypergraph Search." In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, 908–13. Stroudsburg, PA, USA: Association for Computational Linguistics, 2013. http://dx.doi.org/10.18653/v1/d13-1093.

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Jung, Hoin, and Xiaoqian Wang. "Fairness-Aware Online Positive-Unlabeled Learning." In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: Industry Track, 170–85. Stroudsburg, PA, USA: Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.emnlp-industry.14.

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Shdefat, Ahmed Younes, Mennatallah Mohamed, Shahd Khaled, Farrah Hany, Hanaa Fathi, and Diaa Salama AbdElminaam. "Comparative Analysis of Machine Learning Models in Online Payment Fraud Prediction." In 2024 Intelligent Methods, Systems, and Applications (IMSA), 243–50. IEEE, 2024. http://dx.doi.org/10.1109/imsa61967.2024.10652861.

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De Silva, D. I., and K. S. N. Athukorala. "Advancing Online Education: An Interactive Framework for Aligning Teaching Methods with Learning Styles." In 2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), 1–7. IEEE, 2024. https://doi.org/10.1109/icses63760.2024.10910891.

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Hillier, Michael, Florian Wellmann, Boyan Brodaric, Eric de Kemp, and Ernst Schetselaar. "MACHINE LEARNING METHODS FOR 3D GEOLOGICAL MODEL CONSTRUCTION." In GSA 2020 Connects Online. Geological Society of America, 2020. http://dx.doi.org/10.1130/abs/2020am-355922.

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Saenal, Selfiana, Syakhruni Syakhruni, and Muh Kurniawan Adi Kusuma Wiharja. "Online Learning Methods for Learning Dance at School." In 1st World Conference on Social and Humanities Research (W-SHARE 2021). Paris, France: Atlantis Press, 2022. http://dx.doi.org/10.2991/assehr.k.220402.056.

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Lu, Lyujian, Hua Wang, Hua Wang, Yaoguo Li, Yaoguo Li, Thomas Monecke, Thomas Monecke, Hoon Seo, and Hoon Seo. "PREDICTING 3D GEOSPATIAL DATA USING MACHINE LEARNING-BASED IMPUTATION METHODS." In GSA 2020 Connects Online. Geological Society of America, 2020. http://dx.doi.org/10.1130/abs/2020am-356905.

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Lui, Timothy, Daniel Gregory, Sharon A. Cowling, and Well-Shen Lee. "APPLYING MACHINE LEARNING METHODS TO PREDICT GEOLOGY USING SOIL SAMPLE GEOCHEMISTRY." In GSA 2020 Connects Online. Geological Society of America, 2020. http://dx.doi.org/10.1130/abs/2020am-359454.

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Luo, Hongyin, Zhiyuan Liu, Huanbo Luan, and Maosong Sun. "Online Learning of Interpretable Word Embeddings." In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2015. http://dx.doi.org/10.18653/v1/d15-1196.

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Звіти організацій з теми "Online learning methods"

Stanley, April Elisha, and Arienne McCracken. Methods for increasing student learning in an online undergraduate analysis of apparel and production course. Ames: Iowa State University, Digital Repository, 2017. http://dx.doi.org/10.31274/itaa_proceedings-180814-353.

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Yatsenko, Halyna, та Andriy Yatsenko. Використання креативних методів навчання під час викладання дисциплін «Історія української журналістики» і «Креативний текст». Ivan Franko National University of Lviv, березень 2023. http://dx.doi.org/10.30970/vjo.2023.52-53.11736.

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It is emphasized on the use of creative methods in teaching journalism disciplines at the Faculty of Journalism of the Ivan Franko National University of Lviv. The main creative teaching methods are described: the brainstorming method, the «circle of ideas» method, the alternative history method, the morphological analysis method, the hyperbolization method, the «Skamper» method, the Synectics methods. It has been demonstrated that creative teaching methods improve the learning effectiveness and new competencies obtaining. Key words: creative teaching methods; online platform; project work; training courses; personality; learning effectiveness.

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Tusiime, Hilary Mukwenda, and Nahom Eyasu Alemu. Embracing E-Learning in Public Universities in Ethiopia and Uganda. Mary Lou Fulton Teachers College, December 2023. http://dx.doi.org/10.14507/mcf-eli.j2.

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Most of Higher Education Institutions (HEIs) in Ethiopia and Uganda are adopting e-learning to increased demand for, and to widen access to higher education. However, e-learning has not yet been fully embraced. Adoption of e-learning technologies in many universities in Ethiopia and Uganda is still ad hoc; and efforts towards full utilization of e-learning in HEIs are still undermined by many factors. This study has been conducted to explore institutional policy challenges, strategies, and reforms required to embrace all-inclusive online academic programmes. Guided by explanatory-sequential mixed design, data were collected from 765 participants using key informant interviews(KII), survey questionnaire, and documentary review methods. The study findings revealed that glitches from policy agents, mandate, purpose, publics, effectiveness, fairness, desirability, and affordability of the eLearning policies; as well as responsiveness and policy sustainability were the most critical institutional challenges to implementation of online academic programmes at Gondar and Makerere University. The study also revealed that provision of appropriate student support services, setting realistic assignments, emphasizing staff self-direction, having effective attendance policy, sharing of learning/information materials, professional development, technological, and maintenance of effective communication with students, and maintaining social presence were the key eLearning policy strategies used in implementation of online academic programmes at Makerere University. The study results further revealed that widening access to online programmes, mobilisation of adequate financial resources, engaging in national wide policy reforms, organisational restructuring, employment of adequate qualified staff, curriculum reform and entrenching online courses in the university system are key policy reforms required to embrace implementation of all-inclusive online academic programmes. Hence, it was recommended that something had to be done to: overcome institutional policy challenges; improve eLearning policy strategies used; and to effect inevitable policy reforms required to embrace implementation of all-inclusive online academic programmes at Gondar and Makerere University.

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Clement, Timothy, and Brett Vaughan. Evaluation of a mobile learning platform for clinical supervision. University of Melbourne, 2021. http://dx.doi.org/10.46580/124369.

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Context: This report details a formative evaluation of the Clinical Supervision Online (CSO) course, a fee-paying, fully online ‘light touch’ program of study for clinical supervisors offered by the Melbourne Medical School, which was developed in conjunction with the University’s Mobile Learning Unit. The course requires between six to ten hours of self-directed study and is designed for any clinicians who teach. Methods: Evaluation of the course was guided by Rossi, Lipsey and Freeman’s (2004) approach to program evaluation, addressing the need for the course, its design, implementation, impact, and return on investment. Data were collected through interviews with key informants, document analysis, an embedded student survey, learning analytics data, financial data, and an audit against ‘best practice’ standards for online course design. Findings: The findings suggest that course development was driven by both a financial imperative and genuine concern to meet training needs of clinical supervisors. Two hundred and four students enrolled on the course in its first 18 months. This has been enough to cover its developmental costs. In relation to 64 quality standards for online course design, the level of performance was rated as ‘meets’ for 44 items; ‘exceeds’ for one item; ‘developing for 13 items’; and, ‘non-existent’ for six items. An additional 33 items were identified as ‘not applicable’ for the ‘light touch’ course design. Significance: From a learning design perspective there is much to like about the CSO course and the outcome of assessing it against the standards for ‘best practice’ online course design suggests that an evolutionary approach - making incremental changes - could improve the course whilst retaining its existing ‘light touch’ format. The CSO course on its own is unlikely to realise the depth of achievement implied in the course aims and learning outcomes. The CSO course may best be seen as an entrée into the art of clinical supervision.

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Akhmedjanova, Diana, and Komiljon Karimov. Covid-19’s Effects on Higher Education in Uzbekistan: The Case of Westminster International University in Tashkent. TOSHKENT SHAHRIDAGI XALQARO VESTMINSTER UNIVERSITETI, November 2020. https://doi.org/10.70735/azco9450.

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Higher education (HE) in Uzbekistan moved to distance learning since the beginning of the pandemic with uneven results. Universities responded with different approaches to ensure safety of their communities and continue teaching and learning, often online. Westminster International University in Tashkent (WIUT) faced considerable challenges with distance learning including access to technology and the Internet, lack of skills for teaching online and understanding how students learn best in the new mode. Only 14% of faculty used this approach before. Based on WIUT’s initial experience, we recommend: Universities and educational leaders analyze the technology, software, and skills of academic staff and students—can they access and feel comfortable with online learning? Use a learning management system (LMS) that will meet the requirements and needs of academic staff and students. Teachers should supplement with other tools or methods as useful. Design and deliver professional development workshops and trainings for academic staff and students for effective online learning and use of technologies.

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Nahorniak, Maya. Occupation of profession: Methodology of laboratory classes from practically-oriented courses under distance learning (on an example of discipline «Radioproduction»). Ivan Franko National University of Lviv, February 2022. http://dx.doi.org/10.30970/vjo.2022.51.11412.

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The article deals with the peculiarities of the use of verbal, visual and practical methods in the distance learning of professional practically-oriented discipline «Radioproduction», are offered new techniques for the use of these methods during the presentation of theoretical material and the creation of a media product (audiovisual content), due to the acquisition of a specialty in conditions online. It is proved that in distance learning, this discipline is inadmissible to absolutize the significance of verbal methods (narrative, explanation, conversation, discussion, lecture) and that all varieties of verbal methods require the intensification of an interactive factor. Based on its own experience, it has been demonstrated, as with the help of various educational platforms, the most appropriate use of visual learning methods. Particular attention is paid to the fact that practical teaching methods based on professional activities of students acquire priority in their professional training. It has been established that only when parity application of new receptions of verbal, visual and practical methods of online learning may have a proper pedagogical effect and will ensure the qualitative acquisition of the specialty. Training methods – verbal, visual, practical – are intended to provide all levels of assimilation of knowledge and skills to promote the full master of the radiojournalist specialist.

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Schmidt-Sane, Megan, Tabitha Hrynick, Erica Nelson, and Tom Barker. Mutual Learning for Policy Impact: Insights from CORE. Adapting research methods in the context of Covid-19. Institute of Development Studies (IDS), December 2021. http://dx.doi.org/10.19088/core.2021.008.

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On 25 November 2021, the CORE Knowledge Translation Services team at the Institute of Development Studies, UK, hosted an online clinic session to facilitate the sharing of experiences and mutual learning on how CORE projects have or can adapt their research activities in the context of the Covid-19 pandemic. The clinic was attended by 22 CORE members from 12 projects and featured contributions from two CORE projects: The Youth Question in Africa: Impact, Response and Protection Measures in the IGAD Region and A New Digital Deal for an Inclusive Post-Covid-19 Social Compact: Developing Digital Strategies for Social and Economic Reconstruction. This learning guide captures the practical insights and advice from the event, to help inform the practice of participants and other projects across the portfolio.

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Falfushynska, Halina I., Bogdan B. Buyak, Hryhorii V. Tereshchuk, Grygoriy M. Torbin, and Mykhailo M. Kasianchuk. Strengthening of e-learning at the leading Ukrainian pedagogical universities in the time of COVID-19 pandemic. [б. в.], June 2021. http://dx.doi.org/10.31812/123456789/4442.

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Distance education has become the mandatory component of higher education establishments all over the world including Ukraine regarding COVID-19 lockdown and intentions of Universities to render valuable knowledge and provide safe educational experience for students. The present study aimed to explore the student’s and academic staff’s attitude towards e-learning and the most complicated challenges regarding online learning and distance education. Our findings disclosed that the online learning using Zoom, Moodle, Google Meet, BigBlueButton and Cisco has become quite popular among the students and academic staff in Ukraine in time of the lockdown period and beyond. Based on the Principal Component Analysis data processing we can conclude that students’ satisfaction and positive e-learning perception are in a good correlation with quality of e-learning resources and set of apps which are used while e-learning and distance education. Also, education style, methods, and manner predict willingness of students to self-study. The self-motivation, time-management, lack of practice, digital alienation, positive attitude towards ICT, and instruction strategy belong to the most important challenges of COVID-19 lockdown based on the students and academic staff interviews. Online learning on daily purpose should be used in the favor of strengthening of classical higher education rather than replacing the former. Blended education is the best alternative to face-to-face education, because the communication with mentor in a live environmental even virtual should have ushered the learners to complete online learning and improve its results.

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Дирда, Ірина Анатоліївна, Марина Вікторівна Малоіван, and Анна Олександрівна Томіліна. Innovative online teaching tools for students who major in english philology: challenges and opportinutuies. Видавнича група «Наукові перспективи», 2023. http://dx.doi.org/10.31812/123456789/7078.

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The paper in question outlines the possibilities of using modern teaching methods and tools in the process of teaching English to students who major in English Philology. The rapid changes which this process is undergoing are predetermined by the constant development and new demands which it has to meet. In view of Ukrainian education this process is shaped not only by the factors mentioned but as well by the fact that our country is still facing post-pandemic consequences and now those of war conflict when students are deprived of the possibility of gaining offline education in physical classrooms and many other essential educational items. The paper examines the effectiveness of various approaches and tools in promoting language acquisition and proficiency, as well as their impact on students’ engagement, motivation, and learning outcomes during the challenges posed by war and pandemic. The paper is an overview of the latest tools available for the implementation in the process of teaching English including online resources and activities, as well as the use of different platforms, applications, virtual reality, gamification and artificial intelligence. It is aimed at highlighting the advantages and drawbacks of these approaches which may be faced both by educators and students and providing examples of the successful implementations of these approaches in different educational environments. It may be summed up that while the implementation of the teaching methods and tools in question can boost and enhance the quality and accessibility of language education but it is next to impossible to reach successful learning outcomes without careful planning, training, and evaluation which ensure its effectiveness and sustainability.

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Danylchuk, Hanna B., and Serhiy O. Semerikov. Advances in machine learning for the innovation economy: in the shadow of war. Криворізький державний педагогічний університет, August 2023. http://dx.doi.org/10.31812/123456789/7732.

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This preface introduces the selected and revised papers presented at the 10th International Conference on Monitoring, Modeling & Management of Emergent Economy (M3E2 2022), held online in Ukraine, on November 17-18, 2022. The conference aimed to bring together researchers, practitioners, and students from various fields to exchange ideas, share experiences, and discuss challenges and opportunities in applying computational intelligence and data science for the innovation economy. The innovation economy is a term that describes the emerging paradigm of economic development that is driven by knowledge, creativity, and innovation. It requires new approaches and methods for solving complex problems, discovering new opportunities, and creating value in various domains of science, business,and society. Computational intelligence and data science are two key disciplines that can provide such approaches and methods by exploiting the power of data, algorithms, models, and systems to enable intelligent decision making, learning, adaptation, optimization, and discovery. The papers in this proceedings cover a wide range of topics related to computational intelligence and data science for the innovation economy. They include theoretical foundations, novel techniques, and innovative applications. The papers were selected and revised based on the feedback from the program committe members and reviewers who ensured their high quality. We would like to thank all the authors who submitted their papers to M3E2 2022. We also appreciate the keynote speakers who shared their insights and visions on the current trends and future directions of computational intelligence and data science for the innovation economy. We acknowledge the support of our sponsors, partners, and organizers who made this conference possible despite the challenging circumstances caused by the ongoing war in Ukraine. Finally, we thank all the participants who attended the conference online and contributed to its success.

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