Search results for: online social learning

Authors: Mary H Moen, Lauren H. Mandel

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Creating a sense of community in online learning is important for student engagement and success. The integration of discussion forums within online learning environments presents an opportunity to explore how this computer mediated communications format can cultivate a sense of community among students in accelerated master’s degree programs. This research has two aims, to delve into the ways instructors utilize this communications technology to create community and to understand the feelings and experiences of graduate students participating in these forums in regard to its effectiveness in community building. This study is a two-phase approach encompassing qualitative and quantitative methodologies. The data will be collected at an online accelerated Master of Library and Information Studies program at a public university in the northeast of the United States. Phase 1 is a content analysis of the syllabi from all courses taught in the 2023 calendar year, which explores the format and rules governing discussion forum assignments. Four to six individual interviews of department faculty and part time faculty will also be conducted to illuminate their perceptions of the successes and challenges of their discussion forum activities. Phase 2 will be an online survey administered to students in the program during the 2023 calendar year. Quantitative data will be collected for statistical analysis, and short answer responses will be analyzed for themes. The survey is adapted from the Classroom Community Scale Short-Form (CSS-SF), which measures students' self-reported responses on their feelings of connectedness and learning. The prompts will contextualize the items from their experience in discussion forums during the program. Short answer responses on the challenges and successes of using discussion forums will be analyzed to gauge student perceptions and experiences using this type of communication technology in education. This research study is in progress. The authors anticipate that the findings will provide a comprehensive understanding of the varied approaches instructors use in discussion forums for community-building purposes in an accelerated MLIS program. They predict that the more varied, flexible, and consistent student uses of discussion forums are, the greater the sense of community students will report. Additionally, students’ and instructors’ perceptions and experiences within these forums will shed light on the successes and challenges faced, thereby offering valuable recommendations for enhancing online learning environments. The findings are significant because they can contribute actionable insights for instructors, educational institutions, and curriculum designers aiming to optimize the use of discussion forums in online accelerated graduate programs, ultimately fostering a richer and more engaging learning experience for students.

Keywords: accelerated online learning, discussion forums, LIS programs, sense of community, g

Procedia PDF Downloads 84

Authors: Shawndra Bowers, Allie Brandriet, Betsy Gilbertson

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This paper will highlight how Auburn Online’s instructional designers leveraged student and faculty data to update and improve online course design and instructional materials. When designing and revising online courses, it can be difficult for faculty to know what strategies are most likely to engage learners and improve educational outcomes in a specific discipline. It can also be difficult to identify which metrics are most useful for understanding and improving teaching, learning, and course design. At Auburn Online, the instructional designers use a suite of data based student’s performance, participation, satisfaction, and engagement, as well as faculty perceptions, to inform sound learning and design principles that guide growth-mindset consultations with faculty. The consultations allow the instructional designer, along with the faculty member, to co-create an actionable course improvement plan. Auburn Online gathers learning analytics from a variety of sources that any instructor or instructional design team may have access to at their own institutions. Participation and performance data, such as page: views, assignment submissions, and aggregate grade distributions, are collected from the learning management system. Engagement data is pulled from the video hosting platform, which includes unique viewers, views and downloads, the minutes delivered, and the average duration each video is viewed. Student satisfaction is also obtained through a short survey that is embedded at the end of each instructional module. This survey is included in each course every time it is taught. The survey data is then analyzed by an instructional designer for trends and pain points in order to identify areas that can be modified, such as course content and instructional strategies, to better support student learning. This analysis, along with the instructional designer’s recommendations, is presented in a comprehensive report to instructors in an hour-long consultation where instructional designers collaborate with the faculty member on how and when to implement improvements. Auburn Online has developed a triage strategy of priority 1 or 2 level changes that will be implemented in future course iterations. This data-informed decision-making process helps instructors focus on what will best work in their teaching environment while addressing which areas need additional attention. As a student-centered process, it has created improved learning environments for students and has been well received by faculty. It has also shown to be effective in addressing the need for improvement while removing the feeling the faculty’s teaching is being personally attacked. The process that Auburn Online uses is laid out, along with the three-tier maintenance and revision guide that will be used over a three-year implementation plan. This information can help others determine what components of the maintenance and revision plan they want to utilize, as well as guide them on how to create a similar approach. The data will be used to analyze, revise, and improve courses by providing recommendations and models of good practices through determining and disseminating best practices that demonstrate an impact on student success.

Keywords: data-driven, improvement, online courses, faculty development, analytics, course design

Procedia PDF Downloads 61

Authors: Pinar Ozdemir Ayber, Zeina Hojeij

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Blended Learning (BL) is a rapidly growing teaching and learning approach, which brings together the best of both face-to-face and online learning to expand learning opportunities for students. However, there is limited research on the practices, opportunities and quality of instruction in Blended Classrooms, and on the role of the teaching faculty as well as the learners in these types of classes. This paper will highlight the researchers’ experiences and reflections on blending their classes. It will focus on the importance of designing effective lesson plans that emphasize learner engagement and motivation in alignment with course learning outcomes. In addition, it will identify the changing roles of the teacher and the learners and suggest appropriate variations to the traditional classroom setting taking into consideration the benefits and the challenges of the Blended Classroom. It is hoped that this paper would provide sufficient input for participants to reflect on ways they can blend their own lessons to promote ubiquitous learning and student autonomy. Practical tips and ideas will be shared with the participants on various strategies and technologies that were used in the researchers’ classes.

Keywords: blended learning, learner autonomy, learner engagement, learner motivation, mobile learning tools

Procedia PDF Downloads 303

Authors: Ashwaq Alsulami, Jianhua Shao

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Various organisations often need to understand discussions on social media, such as what trending topics are and characteristics of the people engaged in the discussion. A number of approaches have been proposed to extract attributes that would characterise a discussion group. However, these approaches are largely based on supervised learning, and as such they require a large amount of labelled data. We propose an approach in this paper that does not require labelled data, but rely on lexical sources to detect meaningful attributes for online discussion groups. Our findings show an acceptable level of accuracy in detecting attributes for Twitter discussion groups.

Keywords: attributed community, attribute detection, community, social network

Procedia PDF Downloads 162

Authors: Iván García-Magariño, Javier Bravo-Agapito, Marta López-Fernández

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Online judges have proven their utility in partial auto-evaluation of programming short exercises in the last decades. UnitJudge online judge has the advantage of facilitating the evaluation of separate units to provide more segregate and meaningful feedback to students in complex exercises and practices. This paper discusses the use of UnitUdge in advanced Java object-oriented programming exercises and web development practices. This later usage has been proposed by means of the Selenium Java library and classes to provide the web address. Consequently, UnitJudge is an online judge system that can be applied in several subjects, and therefore, many other students would take advantage of self-testing their exercises. This paper presents the experiments with a Java programming exercise for learning Java object-oriented classes with a generic type. Considering 10 students who voluntarily used UnitJudge, 80% successfully learned this concept, passing the judge exercise with correct results.

Keywords: online judges, programming skills, computer science education, auto-evaluation

Procedia PDF Downloads 101

Authors: Filomena Lopes, Sandra Fernandes

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Active learning strategies are at the center of any change process aimed to improve the development of student skills. This paper aims to analyse the impact of teaching strategies, including problem-based learning (PBL), in the curricular unit of information system for management, based on students’ perceptions of how they contribute to develop the desired learning outcomes of the curricular unit. This course is part of the 1st semester and 3rd year of the graduate degree program in management at a private higher education institution in Portugal. The methodology included an online questionnaire to students (n=40). Findings from students reveal a positive impact of the teaching strategies used. In general, 35% considered that the strategies implemented in the course contributed to the development of courses’ learning objectives. Students considered PBL as the learning strategy that better contributed to enhance the courses’ learning outcomes. This conclusion brings forward the need for further reflection and discussion on the impact of student feedback on teaching and learning processes.

Keywords: higher education, active learning strategies, skills development, student assessment

Procedia PDF Downloads 61

Authors: Emily Jin, Harry Sharples, Anne Weist

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Introduction: NICE Evidence Search Student Champion Scheme is a peer-assisted learning scheme that aims to improve the routine use of evidence-based information by future health and social care staff. The focus is on the NICE evidence search portal that provides selected information from more than 800 reliable health, social care, and medicines sources, including up-to-date guidelines and information for the public. This paper aims to evaluate the effectiveness of the scheme when implemented in Liverpool School of Medicine and to understand the experiences of those attending. Methods: Twelve student champions were recruited and trained in February 2020 as peer tutors during a workshop facilitated by NICE. Cascade sessions were then organised and delivered on an optional basis for students, in small groups of < 10 to approximately 70 attendees. Surveys were acquired immediately before and 8-12 weeks after cascade sessions (n=47 and 45 respectively). Data from these surveys facilitated the analysis of the scheme. Results: Surveys demonstrated 74% of all attendees frequently searched for health and social care information online as a part of their studies. However, only 15% of attendees reported having prior formal training on searching for health information, despite receiving such training earlier on in the curriculum. After attending cascade sessions, students reported a 58% increase in confidence when searching for information using evidence search, from a pre-session a baseline of 36%. Conclusion: NICE Evidence Search Student Champion Scheme provided clear benefits for attending students, increasing confidence in searching for peer-reviewed, mainly secondary sources of health information. The lack of reported training represents the unmet need that the champion scheme satisfies, and this likely benefits student champions as well as attendees. Increasing confidence in searching for healthcare information online may support future evidence-based decision-making.

Keywords: evidence-based medicine, NICE, medical education, medical school, peer-assisted learning

Procedia PDF Downloads 130

Authors: Aisha Iddrisu

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The proliferation of cyberviolence in the wave of increased social media consumption calls for immediate attention both at the local and global levels. With over 4.70 billion social media users worldwide and 8.8 social media users in Ghana, various forms of violence have become the order of the day in most countries and communities. Cyber violence is defined as producing, retrieving, and sharing of hurtful or dangerous online content to cause emotional, psychological, or physical harm. The urgency and severity of cyber violence have led to the enactment of laws in various countries though lots still need to be done, especially in Ghana. In Ghana, studies on cyber violence have not been extensively dealt with. Existing studies concentrate only on one form or the other form of cyber violence, thus cybercrime and cyber bullying. Also, most studies in Africa have not explored cyber violence forms using empirical theories and the few that existed were qualitatively researched, whereas others examine the effect of cyber violence rather than examining why those who involve in it behave the way they behave. It is against this backdrop that this study aims to examine various cyber violence behaviour among social media users in Ghana by applying the theory of Self-control and Social control theory. This study is important for the following reasons. The outcome of this research will help at both national and international level of policymaking by adding to the knowledge of understanding cyberviolence and why people engage in various forms of cyberviolence. It will also help expose other ways by which such behaviours are enforced thereby serving as a guide in the enactment of the rightful rules and laws to curb such behaviours. It will add to literature on consequences of new media. This study seeks to confirm or reject to the following research hypotheses. H1 Social media usage has direct significant effect of cyberviolence behaviours. H2 Ineffective parental management has direct significant positive relation to Low self-control. H3 Low self-control has direct significant positive effect on cyber violence behaviours among social, H4 Differential association has significant positive effect on cyberviolence behaviour among social media users in Ghana. H5 Definitions have a significant positive effect on cyberviolence behaviour among social media users in Ghana. H6 Imitation has a significant positive effect on cyberviolence behaviour among social media users in Ghana. H7 Differential reinforcement has a significant positive effect on cyberviolence behaviour among social media users in Ghana. H8 Differential association has a significant positive effect on definitions. H9 Differential association has a significant positive effect on imitation. H10 Differential association has a significant positive effect on differential reinforcement. H11 Differential association has significant indirect positive effects on cyberviolence through the learning process.

Keywords: cyberviolence, social media users, self-control theory, social learning theory

Procedia PDF Downloads 86

Authors: Maria Antonietta Marongiu

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Propositional information in discourse is made coherent, intelligible, and persuasive through metadiscourse. The linguistic and rhetorical choices that writers/speakers make to organize and negotiate content matter are intended to help relate a text to its context. Besides, they help the audience to connect to and interpret a text according to the values of a specific discourse community. Based on these assumptions, this work aims to analyse the use of metadiscourse in the spoken performance of teachers in online EFL, ESP, and subject-teacher courses taught in English to non-native learners in higher education. In point of fact, the global spread of Covid 19 has forced universities to transition their in-class courses to online delivery. This has inevitably placed on the instructor a heavier interactional responsibility compared to in-class courses. Accordingly, online delivery needs greater structuring as regards establishing the reader/listener’s resources for text understanding and negotiating. Indeed, in online as well as in in-class courses, lessons are social acts which take place in contexts where interlocutors, as members of a community, affect the ways ideas are presented and understood. Following Hyland’s Interactional Model of Metadiscourse (2005), this study intends to investigate Teacher Talk in online academic courses during the Covid 19 lock-down in Italy. The selected corpus includes the transcripts of online EFL and ESP courses and subject-teachers online courses taught in English. The objective of the investigation is, firstly, to ascertain the presence of metadiscourse in the form of interactive devices (to guide the listener through the text) and interactional features (to involve the listener in the subject). Previous research on metadiscourse in academic discourse, in college students' presentations in EAP (English for Academic Purposes) lessons, as well as in online teaching methodology courses and MOOC (Massive Open Online Courses) has shown that instructors use a vast array of metadiscoursal features intended to express the speakers’ intentions and standing with respect to discourse. Besides, they tend to use directions to orient their listeners and logical connectors referring to the structure of the text. Accordingly, the purpose of the investigation is also to find out whether metadiscourse is used as a rhetorical strategy by instructors to control, evaluate and negotiate the impact of the ongoing talk, and eventually to signal their attitudes towards the content and the audience. Thus, the use of metadiscourse can contribute to the informative and persuasive impact of discourse, and to the effectiveness of online communication, especially in learning contexts.

Keywords: discourse analysis, metadiscourse, online EFL and ESP teaching, rhetoric

Procedia PDF Downloads 129

Authors: Sameil Hanna Samweil Botros

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The variation of social networking websites inside higher training has garnered enormous hobby in recent years, with numerous researchers thinking about it as a possible shift from the conventional lecture room-based learning paradigm. However, this boom in research and carried out research, but the adaption of SNS-based modules has not proliferated inside universities. This paper commences its contribution with the aid of studying the numerous fashions and theories proposed in the literature and amalgamates together various effective aspects for the inclusion of social technology within e-gaining knowledge. A three-phased framework is similarly proposed, which informs the important concerns for the hit edition of SNS in improving the student's mastering experience. This suggestion outlines the theoretical foundations as a way to be analyzed in sensible implementation across worldwide university campuses.

Keywords: eLearning, institutionalization, teaching and learning, transformation vtuber, ray tracing, avatar agriculture, adaptive, e-learning, technology eLearning, higher education, social network sites, student learning

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Authors: Aya M. Aboudesouky

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Covid-19 has changed and affected the whole world dramatically in a new way that the entire world, even scientists, have not imagined before. The educational institutions around the world have been fighting since Covid-19 hit the world last December to keep the educational process unchanged for all students. E-learning was a must for almost all US universities during the pandemic. It was specifically more challenging to use online case-based learning instead of regular classes among nursing students who take practical education. This study aims to examine the difference in performance and satisfaction between nursing students taking traditional education and those who take virtual case-based education during their practical study. This study enrolls 40 last-year nursing undergraduates from a mid-sized university in Western Pennsylvania. The study uses a convenient sample. Students will be divided into two groups; a control group that is exposed to traditional teaching strategy and a treatment group that is exposed to a case-based teaching strategy. The module designed for this study is a total parenteral nutrition (TPN) module that will be taught for one month. The treatment group (n=20) utilizes the virtual simulation of the CBL method, while the control group (n=20) uses the traditional lecture-based teaching method. Student evaluations are collected after a month by using the survey to attain the students’ learning satisfaction and self-evaluation of the course. The post-test is used to assess the end of the course performance.

Keywords: virtual case-based learning, traditional education, nursing education, Covid-19 crisis, online practical education

Procedia PDF Downloads 128

Authors: Beatriz Delgado

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Although social anxiety is one of the most prevalent disorders in adolescents and causes considerable difficulties and social distress in those with the disorder, to date very few studies have explored the impact of social anxiety on academic adjustment in student populations. The aim of this study was analyze the effect of social anxiety on school functioning in Secondary Education. Specifically, we examined the relationship between social anxiety and self-concept, academic goals, causal attributions, intellectual aptitudes, and learning strategies, personality traits, and academic performance, with the purpose of creating a causal-explanatory model of academic performance. The sample consisted of 2,022 students in the seven to ten grades of Compulsory Secondary Education in Spain (M = 13.18; SD = 1.35; 51.1% boys). We found that: (a) social anxiety has a direct positive effect on internal attributional style, and a direct negative effect on self-concept. Social anxiety also has an indirect negative effect on internal causal attributions; (b) prior performance (first academic trimester) exerts a direct positive effect on intelligence, achievement goals, academic self-concept, and final academic performance (third academic trimester), and a direct negative effect on internal causal attributions. It also has an indirect positive effect on causal attributions (internal and external), learning goals, achievement goals, and study strategies; (c) intelligence has a direct positive effect on learning goals and academic performance (third academic trimester); (d) academic self-concept has a direct positive effect on internal and external attributional style. Also, has an indirect effect on learning goals, achievement goals, and learning strategies; (e) internal attributional style has a direct positive effect on learning strategies and learning goals. Has a positive but indirect effect on achievement goals and learning strategies; (f) external attributional style has a direct negative effect on learning strategies and learning goals and a direct positive effect on internal causal attributions; (g) learning goals have direct positive effect on learning strategies and achievement goals. The structural equation model fit the data well (CFI = .91; RMSEA = .04), explaining 93.8% of the variance in academic performance. Finally, we emphasize that the new causal-explanatory model proposed in the present study represents a significant contribution in that it includes social anxiety as an explanatory variable of cognitive-motivational constructs.

Keywords: academic performance, adolescence, cognitive-motivational variables, social anxiety

Procedia PDF Downloads 332

Authors: Mehran Asadi, Afrand Agah

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In data mining, partitioning is used as a fundamental tool for classification. With the help of partitioning, we study the structure of data, which allows us to envision decision rules, which can be applied to classification trees. In this research, we used online social network dataset and all of its attributes (e.g., Node features, labels, etc.) to determine what constitutes an above average chance of being a divergent node. We used the R statistical computing language to conduct the analyses in this report. The data were found on the UC Irvine Machine Learning Repository. This research introduces the basic concepts of classification in online social networks. In this work, we utilize overfitting and describe different approaches for evaluation and performance comparison of different classification methods. In classification, the main objective is to categorize different items and assign them into different groups based on their properties and similarities. In data mining, recursive partitioning is being utilized to probe the structure of a data set, which allow us to envision decision rules and apply them to classify data into several groups. Estimating densities is hard, especially in high dimensions, with limited data. Of course, we do not know the densities, but we could estimate them using classical techniques. First, we calculated the correlation matrix of the dataset to see if any predictors are highly correlated with one another. By calculating the correlation coefficients for the predictor variables, we see that density is strongly correlated with transitivity. We initialized a data frame to easily compare the quality of the result classification methods and utilized decision trees (with k-fold cross validation to prune the tree). The method performed on this dataset is decision trees. Decision tree is a non-parametric classification method, which uses a set of rules to predict that each observation belongs to the most commonly occurring class label of the training data. Our method aggregates many decision trees to create an optimized model that is not susceptible to overfitting. When using a decision tree, however, it is important to use cross-validation to prune the tree in order to narrow it down to the most important variables.

Keywords: online social networks, data mining, social cloud computing, interaction and collaboration

Procedia PDF Downloads 158

Authors: Ahmed Elzainy, Abir El Sadik, Waleed Al Abdulmonem, Ahmad Alamro, Homaidan Al-Homaidan

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Problem-based learning (PBL) is an educational modality which stimulates critical and creative thinking. PBL has been practiced in the college of medicine, Qassim University, Saudi Arabia, since the 2002s with offline face to face activities. Therefore, crucial technological changes in paperless work were needed. The aim of the present study was to design and implement the digitalization of the PBL activities and to evaluate its impact on students' and tutors’ performance. This approach promoted the involvement of all stakeholders after their awareness of the techniques of using online tools. IT support, learning resources facilities, and required multimedia were prepared. Students’ and staff perception surveys reflected their satisfaction with these remarkable changes. The students were interested in the new digitalized materials and educational design, which facilitated the conduction of PBL sessions and provided sufficient time for discussion and peer sharing of knowledge. It enhanced the tutors for supervision and tracking students’ activities on the Learning Management System. It could be concluded that introducing of digitalization of the PBL activities promoted the students’ performance, engagement and enabled a better evaluation of PBL materials and getting prompt students as well as staff feedback. These positive findings encouraged the college to implement the digitalization approach in other educational activities, such as Team-Based Learning, as an additional opportunity for further development.

Keywords: multimedia in PBL, online PBL, problem-based learning, PBL digitalization

Procedia PDF Downloads 120

Authors: Devatha Kalyan Kumar, Aravindraj D., Sadathulla A.

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Big data are now rapidly expanding in all engineering and science and many other domains. The potential of large or massive data is undoubtedly significant, make sense to require new ways of thinking and learning techniques to address the various big data challenges. Machine learning is continuously unleashing its power in a wide range of applications. In this paper, the latest advances and advancements in the researches on machine learning for big data processing. First, the machine learning techniques methods in recent studies, such as deep learning, representation learning, transfer learning, active learning and distributed and parallel learning. Then focus on the challenges and possible solutions of machine learning for big data.

Keywords: active learning, big data, deep learning, machine learning

Procedia PDF Downloads 446

Authors: Jolanta Jonak

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Traditional classrooms are challenging for many students, but especially for students that learn differently due to cognitive makeup, learning preferences, or disability. These students often require different teaching approaches and learning opportunities to benefit from learning. Teachers frequently divert to using one teaching approach, the one that matches their own learning style. For instance, teachers that are auditory learners, likely default to providing auditory learning opportunities. However, if a student is a visual learner, he/she may not fully benefit from that teaching style. Based on research, students and their parents’ feedback, large numbers of students are not provided the type of education and types of supports they need in order to be successful in an academic environment. This eventually leads to not learning at an appropriate rate and ultimately leading to skill deficiencies and deficits. Providing varied learning approaches promote high academic and social-emotional growth of all students and it will prevent inaccurate Special Education referrals. Varied learning opportunities can be delivered for all students by providing Differentiated Instruction (DI). This type of instruction allows each student to learn in the most optimal way regardless of learning preferences and cognitive learning profiles. Using Differentiated Instruction will lead to a high level of student engagement and learning. In addition, experiencing success in the classroom, will contribute to increased social emotional wellbeing. Being cognizant of how teaching approaches impact student's learning, school staff can avoid inaccurate perceptions about the students’ learning abilities, unnecessary referrals for special education evaluations, and inaccurate decisions about the presence of a disability. This presentation will illustrate learning differences due to various factors, how to recognize them, and how to address them through Differentiated Instruction.

Keywords: special education, disability, differences, differentiated instruction, social emotional wellbeing

Procedia PDF Downloads 49

Authors: Mohammad Abu-Shaira, Weishi Shi

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Adaptive learning, a commonly employed solution to drift, involves updating predictive models online during their operation to react to concept drifts, thereby serving as a critical component and natural extension for online learning systems that learn incrementally from each example. This paper introduces LSTM-SCCM “Long Short-Term Memory Stream Cruise Control Method”, a drift adaptation-as-a-service framework for online learning. LSTM-SCCM automates drift adaptation through prompt detection, drift magnitude quantification, dynamic hyperparameter tuning, performing shortterm optimization and model recalibration for immediate adjustments, and, when necessary, conducting long-term model recalibration to ensure deeper enhancements in model performance. LSTM-SCCM is incorporated into a suite of cutting-edge online regression models, assessing their performance across various types of concept drift using diverse datasets with varying characteristics. The findings demonstrate that LSTM-SCCM represents a notable advancement in both model performance and efficacy in handling concept drift occurrences. LSTM-SCCM stands out as the sole framework adept at effectively tackling concept drifts within regression scenarios. Its proactive approach to drift adaptation distinguishes it from conventional reactive methods, which typically rely on retraining after significant degradation to model performance caused by drifts. Additionally, LSTM-SCCM employs an in-memory approach combined with the Self-Adjusting Memory (SAM) architecture to enhance real-time processing and adaptability. The framework incorporates variable thresholding techniques and does not assume any particular data distribution, making it an ideal choice for managing high-dimensional datasets and efficiently handling large-scale data. Our experiments, which include abrupt, incremental, and gradual drifts across both low- and high-dimensional datasets with varying noise levels, and applied to four state-of-the-art online regression models, demonstrate that LSTM-SCCM is versatile and effective, rendering it a valuable solution for online regression models to address concept drift.

Keywords: automated drift detection and adaptation, concept drift, hyperparameters optimization, online and adaptive learning, regression

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Authors: Saroj Pandey

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COVID-19, declared by the World Health Organization a pandemic (WHO,2020), has created an unprecedented crisis world over endangering the human survival itself. Corona induced lockdowns forced approximately 140 million students of 190 countries at various levels of education from preprimary to higher education to remain confined to their homes. In India, approximately 360 million students were affected by the forced shut down of schools due to the countrywide lockdown in March 2020 and resultant disruption of education. After the initial shock and anxiety the Indian polity and education system bounced back with a number of initiatives, and online education came as a major rescuer for the education system of the country. The distance and online mode of learning that was treated as the poor cousin of conventional mode and often criticized for its quality became the major crusader overnight changing the entire ecosystem of traditional teaching -leaning towards the virtual mode. Teachers who were averse to technology were forced to remodel their educational pedagogies and reorient themselves overnight to use various online platforms such as Zoom, Google meet, and other such platforms to reach the learners. This metamorphosis through ensured students was meaningfully engaged in their studies during the lockdown period but it has its own set of challenges. This paper deals with the government initiatives, and teachers' self-efforts to keep the channel of teaching learning on providing academic and socio emotional support to students during the most difficult period of their life as well as the digital divide between the rich and poor, rural and urban, and boys and girls in India and resultant challenges. It also provides an overview of few significant self-initiatives of teachers to reach their students during the crisis period, who did not have internet and smartphone facilities as well as the initiatives being taken at the government level to address the learning needs and mitigate the learning gaps of learners, bridge the digital divide, strategic planning and upskilling of teachers to overcome the effect of COVID-19 crisis.

Keywords: COVID-19, online education, initiatives, challenges

Procedia PDF Downloads 114

Authors: Prachi Desai, Ankita Gandhi, Mitali Acharya

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Rainfall forecast is mainly used for predictions of rainfall in a specified area and determining their future rainfall conditions. Rainfall is always a global issue as it affects all major aspects of one's life. Agricultural, fisheries, forestry, tourism industry and other industries are widely affected by these conditions. The studies have resulted in insufficient availability of water resources and an increase in water demand in the near future. We already have a new forecast system that uses the deep Convolutional Neural Network (CNN) to forecast monthly rainfall and climate changes. We have also compared CNN against Artificial Neural Networks (ANN). Machine Learning techniques that are used in rainfall predictions include ARIMA Model, ANN, LR, SVM etc. The dataset on which we are experimenting is gathered online over the year 1901 to 20118. Test results have suggested more realistic improvements than conventional rainfall forecasts.

Keywords: ANN, CNN, supervised learning, machine learning, deep learning

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Authors: Elisabeth Desiana Mayasari, Laurensia Aptik Evanjeli, Brigitta Erlita Tri Anggadewi

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The condition of the COVID-19 pandemic demands adaptation in various aspects of human life, including in the field of education. Teachers are expected to do distance learning or Learning From Home (LFH). The teacher said that he experienced stress, anxiety, feeling depressed, and afraid based on the interview. Learning adaptations and pandemic situations can impact the mental health of teachers, so the purpose of this study is to determine the mental health of teachers while teaching online. This research was conducted with a quantitative approach using a survey method. The subjects in this study were 330 elementary school teachers under the auspices of a foundation in Yogyakarta. Teachers' mental health was measured using the Indonesian version of The Mental Health Inventory (MHI-38), which has a reliability of 0.888. The results showed that the teachers generally had a good mental health condition marked by a lower negative aspect score than the positive aspect. In addition, the overall mental health aspect shows that some teachers have better mental health when compared to the average score, as well as higher positive aspect scores in all sub-aspects.

Keywords: mental health, teacher, COVID-19 pandemic, MHI-38

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Authors: Cristina Galván-Fernández, Elena Barberà, Jingjing Zhang

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In recent years, MOOCs have been in the spotlight for its high drop-out rates, which potentially impact on the quality of the learning experience. This study attempts to explore how learning support can be used to keep student retention, and in turn to improve the quality of learning in MOOCs. In this study, the patterns of learning support were identified from a total of 4202592 units of video sessions, clickstream data of 25600 students, and 382 threads generated in 10 forums (optional and mandatory) in five different types of MOOCs (e.g. conventional MOOCs, professional MOOCs, and informal MOOCs). The results of this study have shown a clear correlation between the types of MOOCs, the design framework of the MOOCs, and the learning support. The patterns of tutor-peer interaction are identified, and are found to be highly correlated with student retention in all five types of MOOCs. In addition, different patterns of ‘good’ students were identified, which could potentially inform the instruction design of MOOCs.

Keywords: higher education, learning support, MOOC, retention

Procedia PDF Downloads 335

Authors: Hasna Mekkaoui Alaoui, Mariem Mekkaoui Alaoui

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In a context marked by a growing and pressing demand for online training within Moroccan universities, massive open online courses (Moocs) are undergoing constant evolution, amplified by the widespread use of digital technology and accentuated by the Coronavirus pandemic. However, despite their growing popularity and expansion, these courses are still lacking in terms of tools, enabling teachers and researchers to carry out a fine-grained analysis of the learning processes taking place within them. What's more, the circulation and sharing of knowledge within these environments is becoming increasingly important. The crucial aspect of traceability emerges here, as MOOCs record and generate traces from the most minute to the most visible. This leads us to consider traceability as a valuable approach in the field of educational research, where the trace is envisaged as a research tool in its own right. In this exploratory research project, we are looking at aspects of community knowledge sharing based on traces observed in the "Communication des organisations" Mooc. Focusing in particular on the mediating trace and its impact in identifying knowledge circulation processes in this learning space, we have mobilized the traces of video capsules as an index of knowledge circulation in the Mooc device. Our study uses a methodological approach based on thematic analysis, and although the results show that learners reproduce knowledge from different video vignettes in almost identical ways, they do not limit themselves to the knowledge provided to them. This research offers concrete perspectives for improving the dynamics of online devices, with a potentially positive impact on the quality of online university teaching.

Keywords: circulation, index, digital environments, mediation., trace

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Authors: Michael Subbey, Kwame Takyi Danquah

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Finding a child's exceptional skills and abilities at a young age and nurturing them is a challenging process. The Social Learning Theory (SLT) of Albert Bandura is used to analyze the effects of early talent identification on children's growth and development. The study examines both the advantages and disadvantages of early talent identification and stresses the significance of a moral strategy that puts the welfare of the child first. The paper emphasizes the value of a balanced approach to early talent identification that takes into account individual differences, cultural considerations, and the child's social environment.

Keywords: early talent development, social learning theory, child development, child welfare

Procedia PDF Downloads 108

Authors: Wiem Ben Khalifa, Dalila Souilem, Mahmoud Neji

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The evolutions of Social Web and Semantic Web lead us to ask ourselves about the way of supporting the personalization of learning by means of intelligent filtering of educational resources published in the digital networks. We recommend personalized courses of learning articulated around a first educational course defined upstream. Resuming the context and the stakes in the personalization, we also suggest anchoring the personalization of learning in a community of interest within a group of learners enrolled in the same training. This reflection is supported by the display of an active and semantic system of learning dedicated to the constitution of personalized to measure courses and in the due time.

Keywords: Semantic Web, semantic system, ontology, evaluation, e-learning

Procedia PDF Downloads 335

Authors: David Ofosu-Hamilton, John K. E. Edumadze

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Universities have come to recognize the role Information and Communication Technology (ICT) skills plays in the daily activities of tertiary students. The ability to use ICT – essentially, computers and their diverse applications – are important resources that influence an individual’s economic and social participation and human capital development. Our society now increasingly relies on the Internet, and the Cloud as a means to communicate and disseminate information. The educated individual should, therefore, be able to use ICT to create and share knowledge that will improve society. It is, therefore, important that universities require incoming students to demonstrate a level of computer proficiency or trained to do so at a minimal cost by deploying advanced educational technologies. The training and standardized assessment of all in-coming first-year students of the University of Cape Coast in Information Technology Skills (ITS) have become a necessity as students’ most often than not highly overestimate their digital skill and digital ignorance is costly to any economy. The one-semester course is targeted at fresh students and aimed at enhancing the productivity and software skills of students. In this respect, emphasis is placed on skills that will enable students to be proficient in using Microsoft Office and Google Apps for Education for their academic work and future professional work whiles using emerging digital multimedia technologies in a safe, ethical, responsible, and legal manner. The course is delivered in blended mode - online and self-paced (student centered) using Alison’s free cloud-based tutorial (Moodle) of Microsoft Office videos. Online support is provided via discussion forums on the University’s Moodle platform and tutor-directed and assisted at the ICT Centre and Google E-learning laboratory. All students are required to register for the ITS course during either the first or second semester of the first year and must participate and complete it within a semester. Assessment focuses on Alison online assessment on Microsoft Office, Alison online assessment on ALISON ABC IT, Peer assessment on e-portfolio created using Google Apps/Office 365 and an End of Semester’s online assessment at the ICT Centre whenever the student was ready in the cause of the semester. This paper, therefore, focuses on the digital culture approach of hybrid teaching, learning and paperless examinations and the possible adoption by other courses or programs at the University of Cape Coast.

Keywords: assessment, blended, cloud, paperless

Procedia PDF Downloads 248

Authors: Zhi Liu, Xian Peng, Monika Domanska, Lingyun Kang, Sannyuya Liu

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Massive Open education has become increasingly popular among worldwide learners. An increasing number of course reviews are being generated in Massive Open Online Course (MOOC) platform, which offers an interactive feedback channel for learners to express opinions and feelings in learning. These reviews typically contain subjective emotion and topic information towards the courses. However, it is time-consuming to artificially detect these opinions. In this paper, we propose an emotion-oriented topic detection model to automatically detect the students’ opinioned aspects in course reviews. The known overall emotion orientation and emotional words in each review are used to guide the joint probabilistic modeling of emotion and aspects in reviews. Through the experiment on real-life review data, it is verified that the distribution of course-emotion-aspect can be calculated to capture the most significant opinioned topics in each course unit. This proposed technique helps in conducting intelligent learning analytics for teachers to improve pedagogies and for developers to promote user experiences.

Keywords: Massive Open Online Course (MOOC), course reviews, topic model, emotion recognition, topical aspects

Procedia PDF Downloads 262

Authors: Shirin Alabdulqader

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This research aims to investigate the concept of code-switching (CS) between English, Arabic, and the CS practices of Saudi online users via a Translanguaging (TL) lens for more inclusive view towards the nature of the data from the study. It employs Digitally Mediated Communication (DMC), specifically the WhatsApp and Twitter platforms, in order to understand how the users employ online resources to communicate with others on a daily basis. This project looks beyond language and considers the multimodal affordances (visual and audio means) that interlocutors utilise in their online communicative practices to shape their online social existence. This exploratory study is based on a data-driven interpretivist epistemology as it aims to understand how meaning (reality) is created by individuals within different contexts. This project used a mixed-method approach, combining a qualitative and a quantitative approach. In the former, data were collected from online chats and interview responses, while in the latter a questionnaire was employed to understand the frequency and relations between the participants’ linguistic and non-linguistic practices and their social behaviours. The participants were eight bilingual Saudi nationals (both men and women, aged between 20 and 50 years old) who interacted with others online. These participants provided their online interactions, participated in an interview and responded to a questionnaire. The study data were gathered from 194 WhatsApp chats and 122 Tweets. These data were analysed and interpreted according to three levels: conversational turn taking and CS; the linguistic description of the data; and CS and persona. This project contributes to the emerging field of analysing online Arabic data systematically, and the field of multimodality and bilingual sociolinguistics. The findings are reported for each of the three levels. For conversational turn taking, the CS analysis revealed that it was used to accomplish negotiation and develop meaning in the conversation. With regard to the linguistic practices of the CS data, the majority of the code-switched words were content morphemes. The third level of data interpretation is CS and its relationship with identity; two types of identity were indexed; absolute identity and contextual identity. This study contributes to the DMC literature and bridges some of the existing gaps. The findings of this study are that CS by its nature, and most of the findings, if not all, support the notion of TL that multiliteracy is one’s ability to decode multimodal communication, and that this multimodality contributes to the meaning. Either this is applicable to the online affordances used by monolinguals or multilinguals and perceived not only by specific generations but also by any online multiliterates, the study provides the linguistic features of CS utilised by Saudi bilinguals and it determines the relationship between these features and the contexts in which they appear.

Keywords: social media, code-switching, translanguaging, online interaction, saudi bilinguals

Procedia PDF Downloads 131

Authors: Pailin Klinkesorn

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The research aimed to study the use of learning strategies for Japanese language among college students with different learning achievements who study Japanese as a foreign language in the Higher Education’s level. The survey was conducted by using a questionnaire adapted from Strategy Inventory for language Learning or SILL (Oxford, 1990), consisting of two parts: questions about personal data and questions about the use of learning strategies for Japanese language. The samples of college students in the Japanese language program were purposively selected from Suansunandha Rajabhat University. The data from the questionnaire was statistically analyzed by using mean scores and one-way ANOVA. The results showed that Social Strategies was used by the greatest number of college students, whereas Memory Strategies was used by the least number of students. The students in different levels used various strategies, including Memory Strategies, Cognitive Strategies, Metacognitive Strategies and Social Strategies, at the significance level of 0.05. In addition, the students with different learning achievements also used different strategies at the significance level of 0.05. Further studies can explore learning strategies of other groups of Japanese learners, such as university students or company employees. Moreover, learning strategies for language skills, including listening, speaking, reading and writing, can be analyzed for better understanding of learners’ characteristics and for teaching applications.

Keywords: language learning strategies, achievement, Japanese, college students

Procedia PDF Downloads 392

Authors: Naser Zourikalatehsamad, Seyed Abdorreza Payambarpour, Ibrahim Alwashali, Zahra Abdolkarimi

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The paper aims to evaluate the effect of online advertising on consumer purchase behavior in Malaysian organizations. The paper has potential to extend and refine theory. A survey was distributed among Students of UTM university during the winter 2014 and 160 responses were collected. Regression analysis was used to test the hypothesized relationships of the model. Result shows that the predictors (cost saving factor, convenience factor and customized product or services) have positive impact on intention to continue seeking online advertising.

Keywords: consumer purchase, convenience, customized product, cost saving, customization, flow theory, mass communication, online advertising ads, online advertising measurement, online advertising mechanism, online intelligence system, self-confidence, willingness to purchase

Procedia PDF Downloads 481

Authors: H. S. Saini, K. Vijayalakshmi, Rishi Sayal

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Network-based education has been growing rapidly in size and quality. Knowledge clustering becomes more important in personalized information retrieval for web-learning. A personalized-Learning service after the learners’ knowledge has been classified with clustering. Through automatic analysis of learners’ behaviors, their partition with similar data level and interests may be discovered so as to produce learners with contents that best match educational needs for collaborative learning. We present a specific mining tool and a recommender engine that we have integrated in the online learning in order to help the teacher to carry out the whole e-learning process. We propose to use sequential pattern mining algorithms to discover the most used path by the students and from this information can recommend links to the new students automatically meanwhile they browse in the course. We have Developed a specific author tool in order to help the teacher to apply all the data mining process. We tend to report on many experiments with real knowledge so as to indicate the quality of using both clustering and sequential pattern mining algorithms together for discovering personalized e-learning systems.

Keywords: e-learning, cluster, personalization, sequence, pattern

Procedia PDF Downloads 429