Relevant bibliographies by topics / Social learning support networks

Academic literature on the topic 'Social learning support networks'

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Published: 4 June 2021
Last updated: 19 February 2022

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Journal articles on the topic "Social learning support networks"

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Wenz-Gross, Melodie, and Gary N. Siperstein. "Importance of Social Support in the Adjustment of Children with Learning Problems." Exceptional Children 63, no. 2 (January 1997): 183–93. http://dx.doi.org/10.1177/001440299706300203.

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This study examined the social networks, social supports, friendships, and adjustment of 106 4th-, 5th- and 6th-grade children. Forty children were receiving special education services for learning problems, 66 were in general education. Results showed that children with and without learning problems did not differ on the size or composition of their social networks nor on the negative features of their friendships (conflict, competition). However, children with learning problems used their network differently for support. They turned to the family less for problem-solving support and to peers less for all types of support than children without learning problems. Results are discussed in terms of the implications for children with learning problems as they enter adolescence.
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Sloep, Peter, and Adriana Berlanga. "Learning Networks, Networked Learning." Comunicar 19, no. 37 (October 1, 2011): 55–64. http://dx.doi.org/10.3916/c37-2011-02-05.

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Learning Networks are on-line social networks through which users share knowledge with each other and jointly develop new knowledge. This way, Learning Networks may enrich the experience of formal, school-based learning and form a viable setting for professional development. Although networked learning enjoys an increasing interest, many questions remain on how exactly learning in such networked contexts can contribute to successful education and training. Put differently, how should networked learning be designed best to facilitate education and training? Taking this as its point of departure, the chapter addresses such issues as the dynamic evolution of Learning Networks, trust formation and profiling in Learning Networks, and peer-support among Learning Network participants. This discussion will be interspersed with implementation guidelines for Learning Networks and with a discussion of the more extended case of a Learning Network for Higher Education. Taking into consideration research currently carried out at our own centre and elsewhere, the chapter will close off with a look into the future of Learning Networks.Las redes de aprendizaje (Learning Networks) son redes sociales en línea mediante las cuales los participantes comparten información y colaboran para crear conocimiento. De esta manera, estas redes enriquecen la experiencia de aprendizaje en cualquier contexto de aprendizaje, ya sea de educación formal (en escuelas o universidades) o educación no-formal (formación profesional). Aunque el concepto de aprendizaje en red suscita el interés de diferentes actores del ámbito educativo, aún existen muchos interrogantes sobre cómo debe diseñarse el aprendizaje en red para facilitar adecuadamente la educación y la formación. El artículo toma este interrogante como punto de partida, y posteriormente aborda cuestiones como la dinámica de la evolución de las redes de aprendizaje, la importancia de fomentar la confianza entre los participantes y el papel central que desempeña el perfil de usuario en la construcción de la confianza, así como el apoyo entre compañeros. Además, se elabora el proceso de diseño de una red de aprendizaje, y se describe un ejemplo en el contexto universitario. Basándonos en la investigación que actualmente se lleva a cabo en nuestro propio centro y en otros lugares, el capítulo concluye con una visión del futuro de las redes de aprendizaje.
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Yen, Cherng-Jyh, Chih-Hsiung Tu, Laura E. Sujo-Montes, Hoda Harati, and Claudia R. Rodas. "Using Personal Learning Environment (PLE) Management to Support Digital Lifelong Learning." International Journal of Online Pedagogy and Course Design 9, no. 3 (July 2019): 13–31. http://dx.doi.org/10.4018/ijopcd.2019070102.

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Personal Learning Environment is a promising pedagogical approach to integrate formal and informal learning in social media and support student self-regulated learning. The use of PLEs to support lifelong learning can be expanded to the formal, non-formal, or informal learning environments. This study empirically examined how PLE management predicted the use of PLE to support three types of lifelong learning (i.e., formal, non-formal, or informal learning). This study concluded that PLE management was predictive of each type of learning respectively. PLE is not only a technical platform but also a new digital learning literacy, conceptual space, pedagogical process, and social networks that enable and support learners to achieve their lifelong learning goals. While Open Educational Resources (OERs) are perceived as a solution for social justice in digital lifelong learning, PLE and Open Network Learning Environment are identified as the key pedagogy and instructional strategies to empower learners gaining network-learning literacy and becoming competent digital lifelong learners.
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Ko, Pei-Chun. "INVESTIGATING SOCIAL NETWORKS OF OLDER SINGAPOREAN LEARNERS: THE MIXED-METHODS SOCIAL NETWORK APPROACH." Innovation in Aging 3, Supplement_1 (November 2019): S754. http://dx.doi.org/10.1093/geroni/igz038.2768.

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Abstract Lifelong learning has been regarded as an important factor of promoting active engagement in later life for researchers and policy makers. Most of the studies tend to illustrate old learners as a homogeneous and self-resilient group of people to engage in lifelong learning. Few studies address older learners’ social capital in affecting their decision of engagement and in sustaining their motivation. The study documented the existing social networks of older Singaporeans in lifelong learning programs and illustrated how social networks contributed their participation in learning. The mixed methods consist of in-depth interviews and two network instruments (Name Generator and Position Generator) based on 30 older Singaporeans (between 50 and 79 years old) who attended lifelong learning courses between 2016 and 2018. Interviews are transcribed and analyzed. The network instruments of are quantified and visualized. The findings show that older learners’ networks included a mixture of social ties from family and friends. Learners’ closeness with network members and their living arrangement with them influenced learners’ involvement in learning and future planning. Single respondents who had more non-kin members in the networks reported to be more active due to their weak ties. Overlapping networks among couple learners increase the spousal support for learning. Learners who had wider ranges of social resources are associated with their interest in learning activities. The study suggests that advocating lifelong learning needs to take older adults’ networks into considerations as networks represent the social forces that influence their decisions and motivations.
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Haythornthwaite, Caroline. "Learning, connectivity and networks." Information and Learning Sciences 120, no. 1/2 (January 14, 2019): 19–38. http://dx.doi.org/10.1108/ils-06-2018-0052.

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PurposeThis is paper is concerned with the learning outcomes associated with connectivity through online networks, open online exchange and wider changes associated with contemporary information practices. The theme of connectivity is used here to capture both the detailed specificity of relations that define networks of learners and the ambient effect of wide accessibility to resources and people through open, online forums.Design/methodology/approachThe paper follows the idea of a network from the ground up, outlining the social network perspective as a way to consider the foundational bases of learning and networks, as well as the effect of ambient influence. The paper addresses the ways learning may be viewed as a social network relation, an interpersonal relationship and an outcome of interaction and connectivity, and how network connectivity can be used as input for design for learning.FindingsThe paper presents a range of perspectives and studies that view learning from a social network and connectivity perspective, emphasizing both the person-to-person connectivity of a learning tie and the impact of contemporary data and information sharing through the dynamics of open contributory practice.Practical implicationsThe outcome of connectivity in the service of learning is bound up with digital information practices, including individual practices of search, retrieval, participation, knowledge dissemination, knowledge construction and more. This paper provides a network perspective on learning relations that accommodates analysis in online and offline environments, but incorporates attention to the open, online retrieval and contributory practices that now influence learning practices and which may support design of new learning environments.Originality/valueThis paper offers insight into the way social networks and connectivity combine to show network relations, relationships, outcomes and design input at the actor, network and societal levels.
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Cochrane, Thomas, and Vickel Narayan. "Nurturing Collaborative Networks of Mobile Learning Researchers and Practitioners." International Journal of Mobile and Blended Learning 10, no. 4 (October 2018): 73–92. http://dx.doi.org/10.4018/ijmbl.2018100105.

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In this article, we present the development of a framework for supporting and facilitating collaborative networks of reflective practice using mobile social media. Developed throughout a two-year collaborative mobile learning project #NPF14LMD, the framework has subsequently been used to support two wider international networks of mobile learning researchers and practitioners. The #NPF14LMD project was a national project comprised of three universities and three polytechnics across New Zealand. One of the goals of the #NPF14LMD project was to create a collaborative network of practice across the six institutions participating in the project. The network provided a support and communication structure linking the six institutional communities of practice, enabling sharing of their experiences and a sense of belonging to a wider national and international community. This article outlines the use of mobile social media to facilitate the #NPF14LMD network, and the subsequent application of this framework to support two international networks.
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Easterday, Matthew W., Elizabeth M. Gerber, and Daniel G. Rees Lewis. "Social Innovation Networks: A New Approach to Social Design Education and Impact." Design Issues 34, no. 2 (April 2018): 64–76. http://dx.doi.org/10.1162/desi_a_00486.

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We may be able to educate social designers who can design for human needs through social innovation networks (SINs). SINs engage in three interrelated activities of: supporting design teams' project-based learning, supporting the leadership in studio-based learning communities, and continuous network improvement. SINs face challenges in diffusing social design that might be overcome through networked coaching platforms that support teams' socially-regulated learning and leaders' studio orchestration. SINs offer way to spread design education across disciplines in any organization where design teams need to both innovate and learn.
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Kaewsaiha, Pongrapee. "LMS VS SOCIAL NETWORK: CONTENT ANALYSIS WITH THE SOCIAL PRESENCE THEORY APPROACH." EUrASEANs: journal on global socio-economic dynamics, no. 5(24) (September 30, 2020): 28–37. http://dx.doi.org/10.35678/2539-5645.5(24).2020.28-37.

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The purpose of this research is to study how educators and learners use social networks as part of their teaching and learning, instead of Learning Management Systems (LMSs) that are specifically designed for education. The author uses content analysis with multiple studies to find the influence that leads to the acceptance of social networks as a teaching tool, and what is seen as a disadvantage of LMS that reduces potential benefits. With the social presence theory approach, it is possible to visualize the decisions of educators/learners by defining relationships and positioning within social groups. Other studies show that most students use social networks for discussion, collaboration, sharing resources and finding support (including mental support), while LMS is useful for managing communication between teachers and students (including assessments). The emergence of mobile technologies also helps to increase communication efficiency through social networks. On the other hand, studies have shown that social networks sometimes distract students from the learning process.
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Zachos, Georgios, Efrosyni-Alkisti Paraskevopoulou-Kollia, and Ioannis Anagnostopoulos. "Social Media Use in Higher Education: A Review." Education Sciences 8, no. 4 (November 5, 2018): 194. http://dx.doi.org/10.3390/educsci8040194.

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Nowadays, social networks incessantly influence the lives of young people. Apart from entertainment and informational purposes, social networks have penetrated many fields of educational practices and processes. This review tries to highlight the use of social networks in higher education, as well as points out some factors involved. Moreover, through a literature review of related articles, we aim at providing insights into social network influences with regard to (a) the learning processes (support, educational processes, communication and collaboration enhancement, academic performance) from the side of students and educators; (b) the users’ personality profile and learning style; (c) the social networks as online learning platforms (LMS—learning management system); and (d) their use in higher education. The conclusions reveal positive impacts in all of the above dimensions, thus indicating that the wider future use of online social networks (OSNs) in higher education is quite promising. However, teachers and higher education institutions have not yet been highly activated towards faster online social networks’ (OSN) exploitation in their activities.
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Garcia, Elaine, Ibrahim M. Elbeltagi, Kerry Dungay, and Glenn Hardaker. "Student use of Facebook for informal learning and peer support." International Journal of Information and Learning Technology 32, no. 5 (November 2, 2015): 286–99. http://dx.doi.org/10.1108/ijilt-09-2015-0024.

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Purpose – As the use of social networking and social media technologies (SNT) has become pandemic amongst young people (Tess, 2013; Falahah and Rosmala, 2012) there has been an increasing drive amongst educators and researchers to explore the ways in which SNT may be utilised within the classroom (Junco, 2012). Whilst there is therefore an increasing amount of literature available in relation to the use of SNT within the classroom it does not appear that there has been sufficient research considering the manner in which SNT results in the development of a complex, invisible and organic social network amongst students. When these networks exist outside of the classroom they may allow informal learning and peer support to occur. The purpose of this paper is to investigate these issues. Additionally this paper seeks to determine if the use of Facebook by students may provide an indication of the likelihood of student success on their course. Design/methodology/approach – This paper utilises an empirical approach to explore the nature of these invisible networks and the degree to which the use of SNT by students outside of the classroom may provide support for student learning in relation to informal learning and social interaction. This study explores the use of Facebook through the use of a case study of one cohort of 90 creative arts students who undertook a one-year Foundation in Art and Design course within a specialist arts college in the UK. This research utilises the technique of social network analysis (SNA) in order to visualise the type of interactions that occur within the online network and the strength of these interactions (Dawson, 2008). Findings – Results demonstrate that within this case study the creative arts student group created a complex and interrelated network of connections through Facebook with some students clearly placed at the centre of the network and others on the periphery. It is also demonstrated that those students who are more central within the network are more likely to remain on the course and achieve their qualification. Originality/value – This paper demonstrates that SNA provides a useful and insightful way in which to visualise what would otherwise be an invisible network of connections made by students outside of the classroom. Furthermore this paper will provide an insight for teachers and researchers into the benefits of the use of SNT within education, which will have practical implications for the future use of SNT in teaching and learning.
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Dissertations / Theses on the topic "Social learning support networks"

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Lippold, Tessa. "The significance of social support and close relationships for people with learning disabilities." Thesis, n.p, 2000. http://ethos.bl.uk/.

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Harris, Lisa, and Lisa Harris@rmit edu au. "Electronic Classroom, Electronic Community: Virtual Social Networks and Student Learning." RMIT University. Global Studies, Social Science and Planning, 2008. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080717.144715.

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The capacity for online learning environments to provide quality learning experiences for students has been the focus of much speculation and debate in the higher education sector from the late 1990s to the present day. In this area, 'quality' has become synonymous with engaging students in a learning community. This study reports on a qualitative research project designed to explore the significance of community for students when they study in online learning environments. This project used three case studies to explore tertiary students' thoughts and expectations about community in the online environment. The research was constructed iteratively. Data from the initial case suggested the need to explore the relationship between the constructed online learning environment and the development of learning communities or what I have termed Social Learning Support Networks (SLSN). To explore this issue further, the project was expanded and subsequent cases were chosen that included fundamentally different types of online learning environments. The project had two significant results. Firstly, students not only confirmed popular educational theories on the value of learning communities, but also described how this form of social connection might practically benefit their learning. Secondly, the project found that certain forms of synchronous online environments provided enhanced opportunities for students to form social connections that supported their learning. This project provides new evidence of the benefit of community for students studying online and argues that future online learning environments should be shaped by five key principles designed to foster a sense of social connection between students.
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Wilkie, Tara V. "A qualitative investigation into adolescents with learning disabilities : their perceptions and uses of social support." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0021/NQ55392.pdf.

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Khan, Pour Hamed. "Computational Approaches for Analyzing Social Support in Online Health Communities." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1157594/.

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Online health communities (OHCs) have become a medium for patients to share their personal experiences and interact with peers on topics related to a disease, medication, side effects, and therapeutic processes. Many studies show that using OHCs regularly decreases mortality and improves patients mental health. As a result of their benefits, OHCs are a popular place for patients to refer to, especially patients with a severe disease, and to receive emotional and informational support. The main reasons for developing OHCs are to present valid and high-quality information and to understand the mechanism of social support in changing patients' mental health. Given the purpose of OHC moderators for developing OHCs applications and the purpose of patients for using OHCs, there is no facility, feature, or sub-application in OHCs to satisfy patient and moderator goals. OHCs are only equipped with a primary search engine that is a keyword-based search tool. In other words, if a patient wants to obtain information about a side-effect, he/she needs to browse many threads in the hope that he/she can find several related comments. In the same way, OHC moderators cannot browse all information which is exchanged among patients to validate their accuracy. Thus, it is critical for OHCs to be equipped with computational tools which are supported by several sophisticated computational models that provide moderators and patients with the collection of messages that they need for making decisions or predictions. We present multiple computational models to alleviate the problem of OHCs in providing specific types of messages in response to the specific moderator and patient needs. Specifically, we focused on proposing computational models for the following tasks: identifying emotional support, which presents OHCs moderators, psychologists, and sociologists with insightful views on the emotional states of individuals and groups, and identifying informational support, which provides patients with an efficient and effective tool for accessing the best-fit messages from a huge amount of patient posts to satisfy their information needs, as well as provides OHC moderators, health-practitioners, nurses, and doctors with an insightful view about the current discussion under the topics of side-effects and therapeutic processes, giving them an opportunity to monitor and validate the exchange of information in OHCs. We proposed hybrid models that combine high-level, abstract features extracted from convolutional neural networks with lexicon-based features and features extracted from long short-term memory networks to capture the semantics of the data. We show that our models, with and without lexicon-based features, outperform strong baselines.
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Perkins, Marianne. "Refugee Resettlement in Germany: An Analysis of Policy Learning and Support Networks." Digital Commons @ East Tennessee State University, 2021. https://dc.etsu.edu/honors/617.

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The resettlement of refugees and asylum seekers in Germany since reunification in 1990 has been challenged by two peaks in asylum seeker applications in 1992 and again in 2016. From the 1992 peak, which was fueled by asylum seekers fleeing the former Yugoslavia, extensive research has already been conducted over the past thirty years. These studies have demonstrated the actual outcomes of these primarily Yugoslavian asylum seekers and refugees with these findings indicating legal and economic uncertainty having a detrimental effect even years after resettlement. Using Germany as a case study, this analysis aims to survey the available information in the more recent example of asylum seekers arriving in Germany from 2014 onwards primarily from the Syrian Arab Republic, Afghanistan, and Iraq. Ultimately, successful resettlement equates to successful integration measures. The issues of policy legacy and learning as well as elements of the available support network for asylum seekers in housing, Integrationskurse (integration courses), and advice centers are examined to understand how each relates to successful integration and security for asylum seekers. The findings indicate that Germany has achieved successful resettlement and integration of asylum seekers through policy learning from the early 1990s onwards and a strong support network available for those seeking asylum, yet the exclusion of certain groups from integration measures unfairly leaves some behind. A continuous evaluation of these integration measures is necessary to ensure the successful resettlement of refugees and asylum seekers in Germany in anticipated future peaks in asylum seeker applications.
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Moss, Victoria. "Staff as friends? : an exploration of relationships between adults with a learning disability and the staff who support them in the community." Thesis, University of East Anglia, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.300065.

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Bahceci, Oktay, and Oscar Alsing. "Stock Market Prediction using Social Media Analysis." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-166448.

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Stock Forecasting is commonly used in different forms everyday in order to predict stock prices. Sentiment Analysis (SA), Machine Learning (ML) and Data Mining (DM) are techniques that have recently become popular in analyzing public emotion in order to predict future stock prices. The algorithms need data in big sets to detect patterns, and the data has been collected through a live stream for the tweet data, together with web scraping for the stock data. This study examined how three organization's stocks correlate with the public opinion of them on the social networking platform, Twitter. Implementing various machine learning and classification models such as the Artificial Neural Network we successfully implemented a company-specific model capable of predicting stock price movement with 80% accuracy.
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Setari, Ryan R. "SUPPORT NETWORKS OF “EDUCATIONAL PIONEERS”: A METHODOLOGICAL APPROACH FOR EXAMINING THE IMPACT OF A RESIDENTIAL LEARNING COMMUNITY ON FIRST-GENERATION STUDENTS." UKnowledge, 2017. http://uknowledge.uky.edu/epe_etds/49.

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The purpose of this study is to demonstrate the use of social network analysis to examine the peer involvement and supportive relationships of students living within an exclusively first-generation RLC. Using network surveys targeted toward a first-generation population, the networks of first-year residents were visualized and measured. The supportive peer relationships that provided students with encouragement, validation, and academic assistance were identified, as well as the networks for friendship and study partnership. The networks identified for this study were examined to find if change occurred between the start and the end of the semester. Multiple regression QAPs were performed to explore if the RLC’s social programming displayed an association with the network ties students formed at the end of their first semester. The results of these analyses are presented, in addition to recommendations for future research studies and evaluations. This study indicates that first-generation RLCs can gain a great deal of information about their students’ social involvement using social network analysis techniques, as well as investigate if students are acquiring support from peers as intended.
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Bennett, Jeffrey V. "Community-based learning and social support in the Midwestern District high school internship program relative influences on seniors' occupational and citizenship engagement orientations /." Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1164659045.

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Chetty, Preven. "Engaging within zones of proximal development on Facebook : the case of using Facebook to support learning and mentoring on a NQF Level 5 environmental education, training and development practices learnership." Thesis, Rhodes University, 2015. http://hdl.handle.net/10962/d1017335.

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This study focuses on two roll-outs of a, year-long National Qualification Framework (NQF) level 5, environmental education learnership in South Africa and attempts at enhancing collaborative learning at workplaces using a familiar social networking site called Facebook. This study uses the Facebook group sites created for the workplace course component of the course as one of the means of data collection. Additional interviews and focus groups with learners and administrators on both Environmental Education Training and Development Practices (EETDP) courses also informed the study. The study is located within the context of the rise of the information age, its effects on socio-ecological landscape at large and ways of using social networking sites in order to facilitate scaffolding and meaning making within zones of proximal development for environmental education learnerships. It also looks at the model of apprenticeship and workplace based learning as it is broadly located at the nexus of the SAQA-led academic inquiry into workplace based learning and professional development. It was found that the use of Facebook on the EETDP learnership allowed for collaborative learning to take place between peer to peer interactions as well as between tutors and learners. It was also noted that scaffolding processes requires both technical assistance and strong instructional input from course tutors. One of the most important findings in terms of collaborative learning and engaging within the Zone of Proximal Development (ZPD) was that learners were able to communicate more effectively and freely with both fellow learners and tutors on course after participating on the Facebook group sites. The study offers recommendations on how a social networking platform like Facebook can be utilised effectively for environmental education. The study recommends that scaffolding of workplace based tasks and concepts needs to be better integrated with the course and in both online and offline interactions between learners. It also illustrates how social networking sites can become powerful tools for creating meaning making when combined with course work.
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Books on the topic "Social learning support networks"

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The networked teacher: How new teachers build social networks for professional support. New York: Teachers College Press, 2011.

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Aggarwal, Manasvi, and M. N. Murty. Machine Learning in Social Networks. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4022-0.

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Social support: Theory, research, and intervention. New York: Praeger, 1988.

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Harrison, R. F. Auto nomously learning neural networks for clinical decision support. Sheffield: University of Sheffield, Dept. of Automatic Control & Systems Engineering, 1994.

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Building support networks for schools. Santa Barbara, Calif: ABC-CLIO, 1992.

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Chappell, Neena L. Social support and aging. Toronto: Butterworths, 1992.

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Nestmann, Frank, and Klaus Hurrelmann, eds. Social Networks and Social Support in Childhood and Adolescence. Berlin, New York: DE GRUYTER, 1994. http://dx.doi.org/10.1515/9783110866377.

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Rezvanian, Alireza, Behnaz Moradabadi, Mina Ghavipour, Mohammad Mehdi Daliri Khomami, and Mohammad Reza Meybodi. Learning Automata Approach for Social Networks. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-10767-3.

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Counseling and social support: Perspectives and practice. Newbury Park, Calif: Sage Publications, 1990.

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Conway, Lisa. Working with volunteers: Support. London: Volunteer Centre UK, 1994.

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Book chapters on the topic "Social learning support networks"

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Marques, Gonçalo, and Rui Pitarma. "Using IoT and Social Networks for Enhanced Healthy Practices in Buildings." In Information Systems and Technologies to Support Learning, 424–32. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03577-8_47.

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de Jong, Tim, and Marcus Specht. "Mobile Social Software to Support Authenticity." In Learning Network Services for Professional Development, 255–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00978-5_15.

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Kang, Lele, Shaokun Fan, and J. Leon Zhao. "The Design of IdeaWorks: Applying Social Learning Networks to Support Tertiary Education." In Lecture Notes in Computer Science, 118–29. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20895-4_12.

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Klimova, Blanka, Petra Poulova, and Lucie Ptackova. "Social Network Sites as a Good Support for Study Purposes." In Smart Education and e-Learning 2016, 135–43. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39690-3_12.

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Razali, Sharifah Nadiyah, Faaizah Shahbodin, Norasiken Bakar, Hanipah Hussin, Mohd Hafiez Ahmad, and Normala Sulaiman. "Incorporating Learning Management System with Social Network Sites to Support Online Collaborative Learning: Preliminary Analysis." In Advances in Visual Informatics, 549–57. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02958-0_50.

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Albonda, Haider Daami R., and J. Pérez-Romero. "Reinforcement Learning-Based Radio Access Network Slicing for a 5G System with Support for Cellular V2X." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 262–76. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-25748-4_20.

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Chan, Tak-Wai. "Network Supported Active Social Learning Activities." In CISM International Centre for Mechanical Sciences, 379. Vienna: Springer Vienna, 1999. http://dx.doi.org/10.1007/978-3-7091-2490-1_50.

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Bernsteiner, Reinhard. "Facilitating E-Learning with Social Software." In Knowledge Networks, 237–56. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-59904-976-2.ch016.

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This article explores how social software tools can offer support for innovative learning methods and instructional design in general, and those related to self-organized learning in an academic context in particular. In the first section, the theoretical basis for the integration of wikis, discussion forums, and Weblogs in the context of learning are discussed. The second part presents the results of an empirical survey conducted by the authors and explores the usage of typical social software tools that support learning from a student’s perspective. The article concludes that social software tools have the potential to be a fitting technology in a teaching and learning environment.
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"Social Media and Professional Learning Networks." In Practice-Based Professional Development in Education, 182–99. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-4622-2.ch009.

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This chapter examines social media as a form of professional development. It sheds light on social media platforms that support collaboration and reflection among educators. The International Society for Teachers in Education (ISTE) continues to stress the importance of teachers possessing skills and behaviors of digital age professionals. This is necessary as educators become co-learners with their students and colleagues around the world. Social networks, such as Twitter and Google+ communities, provide opportunities to move up the Substitution Augmentation Modification Redefinition Model developed by Dr. Ruben Puentedura, or offer a method of seeing how computer technology might impact teaching and learning, as well as professional learning for teachers.
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Yen, Cherng-Jyh, Chih-Hsiung Tu, Laura E. Sujo-Montes, Hoda Harati, and Claudia R. Rodas. "Using Personal Learning Environment (PLE) Management to Support Digital Lifelong Learning." In Research Anthology on Instilling Social Justice in the Classroom, 761–82. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7706-6.ch045.

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Personal Learning Environment is a promising pedagogical approach to integrate formal and informal learning in social media and support student self-regulated learning. The use of PLEs to support lifelong learning can be expanded to the formal, non-formal, or informal learning environments. This study empirically examined how PLE management predicted the use of PLE to support three types of lifelong learning (i.e., formal, non-formal, or informal learning). This study concluded that PLE management was predictive of each type of learning respectively. PLE is not only a technical platform but also a new digital learning literacy, conceptual space, pedagogical process, and social networks that enable and support learners to achieve their lifelong learning goals. While Open Educational Resources (OERs) are perceived as a solution for social justice in digital lifelong learning, PLE and Open Network Learning Environment are identified as the key pedagogy and instructional strategies to empower learners gaining network-learning literacy and becoming competent digital lifelong learners.
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Conference papers on the topic "Social learning support networks"

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Arieli, Itai, Fedor Sandomirskiy, and Rann Smorodinsky. "On Social Networks that Support Learning." In EC '21: The 22nd ACM Conference on Economics and Computation. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3465456.3467536.

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Filvà, Daniel Amo, Francisco J. García-Peñalvo, and Marc Alier Forment. "Social network analysis approaches for social learning support." In the Second International Conference. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2669711.2669910.

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Makrehchi, Masoud, and Mohamed Kamel. "Learning Social Networks from Web Documents Using Support Vector Classifiers." In 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings)(WI'06). IEEE, 2006. http://dx.doi.org/10.1109/wi.2006.109.

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Oliveira, Luciana, and Álvaro Figueira. "EduBridge Social - Bridging Social Networks and Learning Management Systems." In 8th International Conference on Computer Supported Education. SCITEPRESS - Science and and Technology Publications, 2016. http://dx.doi.org/10.5220/0005811101620171.

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Rafiq, Yasmin, Luke Dickens, Alessandra Russo, Arosha K. Bandara, Mu Yang, Avelie Stuart, Mark Levine, Gul Calikli, Blaine A. Price, and Bashar Nuseibeh. "Learning to share: Engineering adaptive decision-support for online social networks." In 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE). IEEE, 2017. http://dx.doi.org/10.1109/ase.2017.8115641.

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Sharma, Richa, Hema Banati, and Punam Bedi. "Social support based multi-agent framework for designing an e-learning course." In 2011 IEEE 3rd International Conference on Communication Software and Networks (ICCSN). IEEE, 2011. http://dx.doi.org/10.1109/iccsn.2011.6013800.

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Xu, Rongbin, Menglong Wang, Ying Xie, and Yun Yang. "Distinct Collective Inference Learning in Social Networks." In 2018 IEEE 22nd International Conference on Computer Supported Cooperative Work in Design (CSCWD). IEEE, 2018. http://dx.doi.org/10.1109/cscwd.2018.8465300.

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Nisiotis, Louis, and Lyuba Alboul. "Work-in-Progress—Converging Virtual Reality, Robots, and Social Networks to Support Immersive Learning." In 2020 6th International Conference of the Immersive Learning Research Network (iLRN). IEEE, 2020. http://dx.doi.org/10.23919/ilrn47897.2020.9155125.

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Silva, Soraia P. A., Claudia L. R. Motta, and Carlo E. T. Oliveira. "Promoting learning through social networks supported by a social matching system model." In 2010 14th International Conference on Computer Supported Cooperative Work in Design (CSCWD). IEEE, 2010. http://dx.doi.org/10.1109/cscwd.2010.5471885.

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Cristiani, André, Douglas Lieira, and Heloisa Camargo. "A Sentiment Analysis of Brazilian Elections Tweets." In Symposium on Knowledge Discovery, Mining and Learning. Sociedade Brasileira de Computação, 2020. http://dx.doi.org/10.5753/kdmile.2020.11971.

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The internet connection is present in people’s lives all the time, through smartphones, tablets, computers, among others. The use of social networks is increasingly common around the world. Many companies and people use them to spread products and services and publish opinions, facts that have turned the social networks into powerful sources of information on various topics. Identifying these feelings is a great strategy for many types of decision making. Thus, the purpose of this paper is to collect messages from a specific social network, in this case Twitter, referring to the 2018 Brazilian presidential elections and classify them as: positive, negative and neutral, in order to discover a possible relationship between opinions of social network users and the final outcome of the elections. For this, a corpus was built, preprocessed and evaluated by two different machine learning approaches: Naive Bayes and SVM (Support Vector Machine). The results showed that this social network is a good source of information to perform sentiment analysis and that the number of tweets classified as positive have a strong relationship with the researchers and the final result of the 2018 elections.
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Reports on the topic "Social learning support networks"

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Acemoglu, Daron, Munther Dahleh, Ilan Lobel, and Asuman Ozdaglar. Bayesian Learning in Social Networks. Cambridge, MA: National Bureau of Economic Research, May 2008. http://dx.doi.org/10.3386/w14040.

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Tian, Yuan, Maria Esther Caballero, and Brian Kovak. Social Learning along International Migrant Networks. Cambridge, MA: National Bureau of Economic Research, August 2020. http://dx.doi.org/10.3386/w27679.

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Pal, Chris, Xuerui Wang, and Andrew McCallum. Transfer Learning for Enhancing Information Flow in Organizations and Social Networks. Fort Belvoir, VA: Defense Technical Information Center, September 2007. http://dx.doi.org/10.21236/ada534353.

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Liebeskind, Julia Porter, Amalya Lumerman Oliver, Lynne Zucker, and Marilynn Brewer. Social Networks, Learning, and Flexibility: Sourcing Scientific Knowledge in New Biotechnology Firms. Cambridge, MA: National Bureau of Economic Research, October 1995. http://dx.doi.org/10.3386/w5320.

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Oppel, Annalena. Beyond Informal Social Protection – Personal Networks of Economic Support in Namibia. Institute of Development Studies (IDS), November 2020. http://dx.doi.org/10.19088/ids.2020.002.

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This paper poses a different lens on informal social protection (ISP). ISP is generally understood as practices of livelihood support among individuals. While studies have explored the social dynamics of such, they rarely do so beyond the conceptual space of informalities and poverty. For instance, they discuss aspects of inclusion, incentives and disincentives, efficiency and adequacy. This provides important insights on whether and to what extent these practices provide livelihood support and for whom. However, doing so in part disregards the socio-political context within which support practices take place. This paper therefore introduces the lens of between-group inequality through the Black Tax narrative. It draws on unique mixed method data of 205 personal support networks of Namibian adults. The results show how understanding these practices beyond the lens of informal social protection can provide important insights on how economic inequality resonates in support relationships, which in turn can play a part in reproducing the inequalities to which they respond.
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Chandrasekhar, Arun, Horacio Larreguy, and Juan Pablo Xandri. Testing Models of Social Learning on Networks: Evidence from a Lab Experiment in the Field. Cambridge, MA: National Bureau of Economic Research, August 2015. http://dx.doi.org/10.3386/w21468.

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Bühler, Christoph, and Ewa Fratczak. Learning from others and receiving support: the impact of personal networks on fertility intentions in Poland. Rostock: Max Planck Institute for Demographic Research, July 2005. http://dx.doi.org/10.4054/mpidr-wp-2005-017.

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Allier-Gagneur, Zoé, and Caitlin Moss Coflan. Your Questions Answered: Using Technology to Support Gender Equity, Social Inclusion and Out-Of-School Learning. EdTech Hub, June 2020. http://dx.doi.org/10.53832/edtechhub.0025.

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Yorke, Louise, Darge Wole, and Pauline Rose. An Emerging Strategy for the Development of Culturally Relevant Scales to Capture Aspects of Students’ Socio-Emotional Learning and Social Support for Learning. Research on Improving Systems of Education (RISE), September 2021. http://dx.doi.org/10.35489/bsg-rise-ri_2021/031.

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Existing research on students’ socio-emotional learning and social support for learning in the Global South is limited and most scales that have been developed to measure these aspects of students’ learning and development originate in the Global North. We outline our emerging strategy for capturing student socio-emotional learning and social support for learning in the context of Ethiopia, which may have relevance for other researchers seeking to explore this area of study in Ethiopia or in other related contexts. We propose that considering aspects of students’ socio-emotional learning and social support for learning—in addition to foundational skills of numeracy and literacy—can help to move towards a more expansive and holistic understanding of learning.
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Green, Carla. Social Support in an Urban Moroccan Neighborhood: the Effects of Social Networks, Mediation and Patronage on the Physical Health and Psychological Adjustment of Women. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.1334.

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