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Introduction: Amid the COVID-19 pandemic, the temporary closure of educational institutions led to the adoption of remote or online learning delivery. Challenges, especially for grade schools were evident. Objective: This study aimed to identify factors affecting the perceived online discussion experience of Filipino primary students through distance learning in the National Capital Region, Philippines. Method: Variables such as cognitive presence, teaching presence, social presence, and online discussion experience were investigated simultaneously by utilizing the structural equation modeling (SEM) and random forest classifier (RFC) approach. A total of 385 currently enrolled Filipino grade school student participants were surveyed. Results: Results show that cognitive presence has the most significant impact on the perceived online discussion experience, followed by teaching presence, and social presence. This study is the first study that analyzed the online discussion experience among grade school students in online education in the Philippines considering SEM and RFC. It was seen that highly significant factors such as teaching presence, cognitive presence, social presence, triggering events, and exploration will lead to high and very high learning experience with grade school students. Conclusion: The findings of this study would be significant for teachers, educational institutions, and government agencies to improve the online delivery of primary education in the country. In addition, this study presents a reliable model and results which can be extended and applied for academicians, educational institutions, and the education sector to develop ways in enhancing the online delivery of primary education worldwide.
Introduction: Au milieu de la pandémie de COVID-19, la fermeture temporaire des établissements d'enseignement a conduit à l'adoption de la prestation d'apprentissage à distance ou en ligne. Les défis, en particulier pour les écoles primaires, étaient évidents. Objectif: Cette étude visait à identifier les facteurs affectant l'expérience de discussion en ligne perçue des élèves philippins du primaire par le biais de l'apprentissage à distance dans la région de la capitale nationale, aux Philippines. Méthode: Des variables telles que la présence cognitive, la présence dans l'enseignement, la présence sociale et l'expérience de discussion en ligne ont été étudiées simultanément en utilisant l'approche de structural equation modeling (SEM) et de Random Forest classifier (RFC). Un total de 385 élèves philippins actuellement inscrits à l'école primaire ont été interrogés. Résultats: Les résultats montrent que la présence cognitive a l'impact le plus significatif sur l'expérience de discussion en ligne perçue, suivie de la présence pédagogique et de la présence sociale. Cette étude est la première étude qui a analysé l'expérience de discussion en ligne parmi les élèves du primaire dans l'éducation en ligne aux Philippines en tenant compte du SEM et du RFC. Il a été constaté que des facteurs très importants tels que la présence d'enseignement, la présence cognitive, la présence sociale, les événements déclencheurs et l'exploration conduiront à une expérience d'apprentissage élevée et très élevée avec les élèves du primaire. Conclusion: En outre, cette étude présente un modèle et des résultats fiables qui peuvent être étendus et appliqués aux universitaires, aux établissements d'enseignement et au secteur de l'éducation afin de développer des moyens d'améliorer la prestation en ligne de l'enseignement primaire dans le monde entier.
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In the recent, and ongoing, Covid-19 pandemic, remote or online K-12 schooling became the norm. Even if the pandemic tails off somewhat, remote K-12 schooling will likely remain more frequent than it was before the pandemic. A mainstay technique of online learning, at least at the college and graduate level, has been the online discussion. Since it does afford the potential for meaningful learner-learner and instructor-learner interaction, which are vital for distance learning, it is worth considering online discussions for K-12 remote schooling. One challenge with online learning in general, and online discussion in particular, is that it is labor intensive for teachers to moderate. Effective moderating of online discussions is vital for discussions to be nurturing, effective learning situations. Yet, moderating of online discussions is notoriously labor-intensive for teachers/instructors. Further, since younger learners are more likely to drift off topic, in general, but particularly in small group online discussions, automated early warning systems are helpful. The current study collected small group, "book club”, discussion data from fourth graders reading web-based eBooks in Slovenian primary schools, qualitatively coded the data and analyzed postings using computer-based natural language processing to predict when students went off-topic. One indicator that postings are on-topic is book relevance, i.e. that the posting is relevant to eBook content. The computer algorithm correctly predicted book relevance of postings 90 percent of the time, suggesting that automated computer algorithms could assist teachers with moderating online discussions, providing real-time notifications of problems in online discussions. Further, this study provided a proof-of-concept that small group online discussions, in web-based eBooks can be practical and educationally meaningful in fourth grade classes. [ FROM AUTHOR] Copyright of Interactive Learning Environments is the property of Routledge 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 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 . (Copyright applies to all s.)
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In the Covid-19 era, traditional lecture-based teaching has been undergoing changes in learning design, learners' engagement, and technology integration. Online learning has become an integral part of education around the globe due to its flexibility in learning with respect to place and time. These online courses are available to larger audiences and enable students to have more freedom over the study process. However, freedom also means that instructors have less control to keep students making progress on the course. The flexibility of online courses is encouraging the students to enrol with a few clicks but most of these students are dropping out due to losing interest in the course contents within a few weeks. On the contrary, online learning produces large amounts of data that can be used to follow the learning process and give useful insights for both teachers and students. Learning analytics algorithms utilize these data to identify the factors and parameters that can explain learners' dropout rate, learning performance, as well as suggest possible actions to intrigue learners' active engagement. To conduct further research on the parameters affecting learners' participation in an online course, it is essential to find out the previous research works, best practices, and research trends of learning analytics. In the scope of this work, the authors formulated a search query to generate a pool of most relevant papers from the Scopus database and, hence, identified seven clusters which illustrate the landscape of the learning analytics domain. The authors also employed the Latent Dirichlet allocation (LDA) topic modeling algorithm which is a form of text data mining and statistical machine learning approach to compare the similarities with the clusters generated as a part of literature review. The authors further analyzed the papers in each cluster to identify the parameters which are significant to build a predictive model on learners' dropout rate. This work not only provides a baseline to conduct further research to find out the parameters affecting learners' retention rate but also introduces a systematic methodology to validate the findings of the literature review with a data-driven algorithmic approach. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
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During Covid-19, most of the university courses have been transited to distance education and online teaching. It is unfortunate but true that most of this distance teaching lacks the active participation of learners, thus failing to keep their attention throughout the teaching time. According to "Dale's Cone of Learning,” students only remember 20 percent of the lecture without the involvement of any active participation. So it has become critical to find ways to engage these distance learners actively. The online discussion forum can be utilized as the primary tool to intrigue the active engagement of the learners. Therefore, it is also necessary to measure the students' active engagement in online course discussion forums. Digitalization of the teaching process allows access to a large amount of data representing learners' behavior. Every click can be observed and analyzed, which allows automating the assessment of the learning process. This paper aims to employ an existing approach introduced by the authors in previous work to translate learner's engagement quantitatively based on their online discussion activity, which can be further utilized for assessment and understanding the interaction dynamics within the course. The discussion forum data from three cohorts of an online course on "Systematic Creativity and TRIZ basics” at LUT University, Finland, is analyzed via employing Social Network Analysis and natural language processing (NLP). Learners' engagement in the discussion forums is assessed by focusing on two main criteria: the number of meaningful words used and the centrality measure of network analysis. As a result, the assessment of 50+ students' discussion forum activity depicts a strong correlation between the meaningful words used by the students and their interaction (degree centrality and eigenvector centrality). © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
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Procrastination is a behavioral feature in which a person chooses to delay a task or a decision. Academic procrastination is the tendency to postpone school-related obligations despite known negative consequences. In this paper, we examine how procrastination manifests in online discussion forum participation in a university in the Philippines during the COVID-19 pandemic. We visualize how high- and low-performing students differ in the rate at which they respond to discussion forum prompts. We also make use of association rule mining in order to determine which student behaviors are antecedents of procrastination. We find that most high-performing students tend to respond to discussion forum prompts much earlier than most low-performing students. This implies that they procrastinate less. We also found that making initial accesses or posts later or no graded posts at all makes the student at risk for poor performance. © ICCE 2022.All rights reserved.
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The COVID-19 pandemic precipitated the burgeoning of online learning and asynchronous online discussion forums in higher education due to restrictions on face-to-face teaching and learning interactions. Previous research on asynchronous online discussion forums focused on the processes that enhance or limit discussion threads and how discussion posts develop students' reflection and critical thinking skills. Although asynchronous online discussion forums are regarded as spaces for interactive learning, very little is known about how they facilitate epistemological access and enable collaborative peer learning interactions during periods of disruption such as the COVID-19 pandemic. The current study explores voluntary asynchronous online discussion forum participation in a non-credit bearing course from a unique angle of mediating epistemological access to online learning. This study draws on connectivist theory as a theoretical framework in a digital age where the student is in control of engagement interaction and information exchange. The central research question posed is how does an asynchronous online discussion forum mediate epistemological access to online learning and facilitate collaborative self-directed peer learning during the COVID-19 pandemic? The present study is underpinned by an inductive qualitative exploratory case study approach. A total of 2 146 discussion posts from 1 348 students across five faculties were downloaded from the learning management system and analysed using thematic analysis. This study indicates that epistemological access using a technology-mediated tool, is best facilitated through agency at the institutional, the instructor and the student level. The findings show that despite academic and technological challenges an online discussion forum enables epistemological access, interactive exchange of information and the formation of collaborative peer learning communities. In an age of digital inequalities, this study provides a starting point to uncover ontological barriers to epistemological access to online learning and signals the importance of integrating epistemological access, pedagogy and technology. This article concludes with implications for re-imagining the design of online multi -modal pedagogy to mediate online collaborative self-directed peer engagement and learning.
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In this contribution we examine social interaction and communication among students in a digital learning environment. Remote learning plays an increasingly central role in education. There are similarities between social interaction and communication in digital learning environments and face-to-face interaction, but also fundamental differences. We need to learn more about students’ perception of digital communication and their usage behaviour in order to adapt digital education to the needs of the learners. This contribution seeks to discuss the affordances and constraints of online discussion forums used in formal education in comparison to informal social media and face-to-face interaction. We present the results of an interview study with N = 19 student teachers who attended the presented e-learning course during the CoVid-19-pandemic. From the results, we derive recommendations for educators when it comes to implementing online discussion forums in their learning environments. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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In the context of the COVID-19 pandemic, the paper focuses on discussing this important teaching segment online in blended learning. Taking the junior as the research objects, the behavioral characteristics and interaction depth of different types of students are studied through Cluster Analysis and Lag Sequence Analysis. The purposes are to dig out the problems existing in the online discussion process and to propose teachers' intervention suggestions so as to improve the effect of the discussion. The research found that discussion behavior is mainly construction, and there is no discussion mechanism with communication and interaction as knowledge development. The behavior transformation is mainly based on the priming-single type and priming-arguing type, and there are fewer students who achieve the ideal state of the argumentative type. Most students integrate into the discussion atmosphere slowly, so teachers should take corresponding measures to help students enter the discussion quickly at the beginning of the discussion. © 2022 ACM.
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Students’ conversations in academic settings evolve over time and can be affected by events such as the COVID-19 pandemic. In this paper, we employ a Contextualized Topic Modeling technique to detect coherent topics from students’ posts in online discussion forums. We construct topic chains by connecting semantically similar topics across months using Word Mover’s Distance. Consistent academic discourse and contemporary events such as the COVID-19 outbreak and the Black Lives Matter movement were found among prominent topics. In later months, new themes around students’ lived experiences emerged and evolved into discussions reflecting the shift in educational experiences. Results revealed a significant increase in more general topics after the onset of pandemic. Our proposed framework can also be applied to other contexts investigating temporal topic trends in large-scale text data. © 2022, Springer Nature Switzerland AG.
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BACKGROUND: Compared to other types of dementia, family caregivers of people with Lewy body dementia (LBD) report higher stress levels and more severe depressive symptoms. Although several digital support interventions for caregivers of persons with dementia exist, few target LBD specifically or leverage a fully remote and asynchronous approach suitable for pandemic circumstances. OBJECTIVE: We performed a pilot evaluation of a digital intervention designed to help caregivers of people with LBD address challenges they have experienced, with the end goal of reducing psychological distress in this population. METHODS: We recruited 15 family caregivers of people with LBD to participate in the quasi-experimental, single-arm, mixed methods study titled Virtual Online Communities for Aging Life Experience-Lewy Body Dementia (VOCALE-LBD). The study offers an 8-week web-based intervention that uses a digital discussion platform and involves moderation, peer-to-peer support, didactic training, and problem-solving skill enactment. RESULTS: Participants' baseline characteristics were the following: mean age 66 (SD 8) years; 14 of 15 (93%) of them were female; all (15/15, 100%) were White; and 8 (53%) of them had at least a postgraduate degree. Throughout the intervention, participants engaged in weekly web-based discussions, generating a total of 434 posts (average 4 posts per week). Attrition was 20% (3/15). Upon study exit, participants showed the following average improvements: 3.0 (SD 6.0) in depression, 8.3 (SD 16.7) in burden, 2.9 (SD 6.8) in stress, and 0.3 (SD 0.8) in loneliness. When looking at the proportion of participants with clinically signiï¬cant improvement versus those with a worsening of ≥0.5 SD for each outcome, we observed net improvements of 50% (6/12), 33% (4/12), 25% (3/12), and 25% (3/12) in depression, loneliness, burden, and stress, respectively. In terms of the benefits of participation, participants reported that participation helped them "a great deal" to (1) improve their understanding of LBD (9/12, 75%), (2) gain confidence in dealing with difficult behaviors of the care recipient (6/12, 50%), and (3) improve in one's abilities to provide care to the care recipient (4/12, 33%). CONCLUSIONS: The study generated promising feasibility and preliminary efficacy data for a low-cost, web-based intervention designed for caregivers of persons with LBD. Though the study was not powered for significance, we observed nominal average and net improvements in important psychological outcomes. Moreover, many caregivers reported that study participation helped them better understand the disease, feel more conï¬dent in dealing with difficult behaviors of the care recipient, and improve their ability to care for the care recipient. If validated in future studies, the intervention could be an accessible, on-demand resource for caregivers, enabling them to engage in moderated remote discussions with peers at their own convenience in terms of location, time of the day, and frequency.
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BACKGROUND: A growing body of evidence indicates that the COVID-19 pandemic has had detrimental mental health effects for pregnant women. However, little is known about the specific stressors that increased anxiety for pregnant women at the start of the pandemic. The present study aimed to better understand the concerns of pregnant women during the beginning COVID-19 pandemic by analyzing content posted during the month of March 2020 on online pregnancy message boards hosted on WhatToExpect.com. METHODS: All posts published between March 1-31, 2020 on nine different due-date specific WhatToExpect.com message boards were reviewed for COVID-19 relevance. Posts mentioning COVID-19 or its direct effects (e.g., "quarantine" or "stay-at-home order") were included in our final sample. Data were coded by three authors according to a codebook developed inductively by all four authors. Posts were analyzed by overall frequency of appearance, by trimester, and temporally across the month of March 2020. RESULTS: Across the 5,541 posts included in our final sample, the most common topics were fear of COVID-19 exposure, concerns with labor and delivery, navigating social interactions, and disruptions to prenatal care. The most dominant topics by trimester were disruptions to prenatal care (first trimester), fear of COVID-19 exposure (second trimester), and concerns about labor and delivery (third trimester). CONCLUSION: Our findings add to prior literature by demonstrating the salience of social concerns, which was the third largest COVID-19 topic in our sample. Emotional distress was most salient with regard to restrictions on birthing partners, but was apparent in everything from disruptions to pregnancy announcements, to cancelled baby showers, and limitations on newborn visitors. Given that anxiety during pregnancy is associated with worse maternal-fetal health outcomes, in the early stages of future pandemics healthcare providers should focus not only on strictly health-related concerns expressed by pregnant women, but also more broadly on other sources of anxiety that may be impacting the well-being and mental health of their patients.
Subject(s)
COVID-19 , Pandemics , Anxiety/epidemiology , Anxiety/etiology , Anxiety/psychology , COVID-19/epidemiology , Female , Humans , Infant, Newborn , Pregnancy , Pregnant Women/psychology , SARS-CoV-2ABSTRACT
As the COVID-19 pandemic continues, university education and feedback guidance have inevitably moved to online platforms, becoming a global trend. This study focuses on a case of Sookmyung Women's University in South Korea, which has operated an online discussion clinic for university general education for more than a year as a case study. There are two main research methods. A frequency analysis was conducted to confirm what kind of counseling the students preferred at the discussion clinic based on the answers written in the students' applications. The students whose applications were used for the analysis were divided into 57 teams, and there were two to six members per team. The results were as follows: In the survey results, students wanted help with the preparation process necessary for the discussion and the practical strategies for facilitating discussions. They wanted personalized counseling, demonstrating that discussion education provided in the foundational curriculum is insufficient. Second, the educational model of the discussion clinic and educational examples were examined. The findings confirmed that online discussion education is effective if the system is technically supplemented. Instructors and researchers are prepared to meet students' demands for feedback and individual counseling, even if these are not provided through face-to-face discussions. Additionally, face-to-face guidance can be operated more effectively by taking advantage of online systems. The findings also demonstrate that further research on designing and operating online discussion centers is required. This study is a preceding study on developing online systems and educational guidelines for higher educational institutions to present new insights into smart learning. This paper also includes suggestions for educational and scientific discussions. The online discussion instructional model shown in this paper explores methods of scientific communication through a debate on scientific issues.
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Given the lockdown situation due to the global pandemic in place, teaching and learning hardware-oriented hand-son skills became a major challenge for engineering education. The present study investigates some of the approaches and demonstrates an effective method of teaching modern engineering skills in a simulated environment, such as investigating the Industry 4.0 concept of 'Warehouse Automation.' As part of Project-Based Learning, we are using open source software and free services in a six-month online robotics competition with several stages and tasks. This learning activity was implemented among 1880 participants (470 teams) to teach complex engineering concepts from multidisciplinary domains such as - (1) Robot Operating System (ROS) to control two Robotic Arms in a dynamic simulator, (2) Internet of Things protocols such as MQTT and HTTP, and (3) free cloud services to log data in a database and developing an email notifications system. All the necessary resources were provided to the participants along with the troubleshooting guide that was provided via an online discussion forum. After each task performance of teams was recorded and feedback was collected from the participants. All the recorded data was passed through various statistical analyses as a part of the study to assess the effectiveness of this teaching and learning activity. The study further inspects- whether there is a correlation between participants' performance in the academic-curricular and the competition, and whether more interaction through online-discussion-forum leads to better performance. Finally, the study will help us understand the perception of participants about COVID-19 impact on their performance. © 2022 IEEE.
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Sentiment Analysis (SA) has become an extremely sought after area of research especially post COVID-19 when people used to spent a lot of time on the social media to interact with each other. This interaction was done through posts having both textual and visual cues and also by participating in online discussions forums. Some of the inherent challenges encountered in the process of SA include discernment of sarcasm, irony, humor, negation, multi-polarity or Aspect-Level Sentiment Analysis (ASA) etc. Researchers are now gradually shifting their focus to the identification and detection of sarcasm and how it can empower SA. Sarcasm expresses a person's downside feelings by using positive words in an implicit way. It also has an overall impact on increasing the efficiency of the SA models. Eliciting sarcastic statements is tough for humans as well as for machines without the knowledge of the context or background in which it is expressed, body language and/or facial expression of the speaker and his voice modulation. This review paper studies some of the approaches used for sarcasm detection and also guides researchers in exploring the different modalities of data for developing applications like a virtual chat-bot or assistant, depression analysis, stress management system at workplace etc. © 2022 IEEE.
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Studying incivility in online discussions is a crucial research endeavor, especially in light of a pandemic, as user comments have been shown to be an important source of information and basis for opinion formation. Scholars are increasingly interested in studying incivility from a comparative perspective. This study contributes to this strand of literature by investigating incivility in user comments on the news website and Facebook site of the Austrian newspaper Der Standard. A content analysis (N = 240) was employed to identify forms and levels of incivility in user comments on topics related to COVID-19. Results show Facebook comments to be significantly less uncivil than user comments on the newspaper's website. Moreover, differences regarding the prevalence of the dimensions of incivility on the two platforms were identified. Finally, results suggest that incivility does not necessarily go hand in hand with lower levels of deliberative quality. Implications for news organizations and democracy are discussed. Copyright © 2022 Schroll and Huber.
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In literature review it is found that the research shows that online discussion can promote the development of students' higher-order thinking, but the current online discussion effect is not ideal mainly because teachers lack careful design of online discussion. Through the design and implementation of online discussion organization, the results show that the discussion topics put forward by students according to the given scope of teachers can stimulate the enthusiasm of discussion participation;Compared with class group discussion, students in panel discussion show higher enthusiasm and deeper interaction;Without a host in the discussion, students have higher enthusiasm for discussion and are easier to achieve higher-level goals. It can be seen from the research that when teachers design online discussions, it is more conducive to achieving the goal of online discussions by letting students put forward discussion topics for spontaneous panel discussions. © 2021 ACM.
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While a variety of learning technologies are presently available to facilitate student-to-student peer interactions and collaborative learning online, recent research suggests that students' opportunities to interact with their peers were significantly reduced following the abrupt transition to remote instruction due to coronavirus disease. This raises concerns because peer interaction is known to be a key ingredient in effective online learning environments, and during remote instruction, the primary connection between a student and their identity as a member of a college community would have been online courses. In this study, we investigate whether and how collaborative technologies supported peer interaction, and students' learning, during remote instruction. Specifically, we used results from a multicampus survey of students and instructors, as well as data from our online learning management system, to explore the use of collaborative tools at a large scale and their associations with student outcomes. Findings indicate that instructors, as was typical before the pandemic, generally favored individual learning activities over collaborative activities during campus closure. But in those situations where collaborative activities were present during remote instruction, triangulation analyses indicate that their use was related to improved performance as measured by instructors' survey responses, by students' performance in their courses, and by an increased sense of belonging among students. (PsycInfo Database Record (c) 2022 APA, all rights reserved)