Journal articles on the topic 'Social learning support networks'
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1
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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Dziura, Sarah L., and James C. Thompson. "The Neural Representational Space of Social Memory." Open Mind 3 (October 2019): 1–12. http://dx.doi.org/10.1162/opmi_a_00021.
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Social functioning involves learning about the social networks in which we live and interact; knowing not just our friends, but also who is friends with our friends. This study utilized an incidental learning paradigm and representational similarity analysis (RSA), a functional MRI multivariate pattern analysis technique, to examine the relationship between learning social networks and the brain’s response to the faces within the networks. We found that accuracy of learning face pair relationships through observation is correlated with neural similarity patterns to those pairs in the left temporoparietal junction (TPJ), the left fusiform gyrus, and the subcallosal ventromedial prefrontal cortex (vmPFC), all areas previously implicated in social cognition. This model was also significant in portions of the cerebellum and thalamus. These results show that the similarity of neural patterns represent how accurately we understand the closeness of any two faces within a network. Our findings indicate that these areas of the brain not only process knowledge and understanding of others, but also support learning relations between individuals in groups.
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Dafoulas, Georgios, and Azam Shokri. "Investigating the educational value of social learning networks: a quantitative analysis." Interactive Technology and Smart Education 13, no. 4 (November 21, 2016): 305–22. http://dx.doi.org/10.1108/itse-09-2016-0034.
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Purpose The emergence of Education 2.0 enabled technology-enhanced learning, necessitating new pedagogical approaches, while e-learning has evolved into an instrumental pedagogy of collaboration through affordances of social media. Social learning networks and ubiquitous learning enabled individual and group learning through social engagement and social distribution of knowledge. Nevertheless, these developments have not been supported with extensive studies focusing on quantifying the impact of technology-enhanced learning on students’ progress and achievement. The purpose of this paper is to investigate how a quantitative overview of Facebook’s influence on students’ progress can be incorporated in a proposed e-moderation model of teaching and learning. Design/methodology/approach The approach is based on extending Salmon’s (2003) e-moderation model, which provides an emphasis on the theoretical perspectives that support socially situated learning environments of social networks such as Facebook. The findings revealed that students’ grades were positively influenced by the complementary use of Facebook on their courses of study. Findings The use of a social learning network also triggered a significant increase in student participation in learning activities delivered over Facebook. Research limitations/implications The main research limitations were due to the fact that a single social network was chosen for conducting the experiments. Furthermore, the investigation was narrowed down to a selected range of sessions offered to college and university students as part of their course. Originality/value The paper’s contribution is twofold, as it offers an original set of guidelines for conducting social learning network experiments and provides valuable quantifiable findings on the educational value of such networks.
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Tosun, Nilgün. "Social Networks as a Learning and Teaching Environment and Security in Social Networks." Journal of Education and Training Studies 6, no. 11a (November 29, 2018): 194. http://dx.doi.org/10.11114/jets.v6i11a.3817.
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Technology is in a constantly evolving and changing structure since the existence of mankind. Because of this dynamic structure, technology fulfills a number of functions such as facilitating people's lives, time, profit from work, profit from cost, making life more enjoyable. At the same time, technology is used in all areas of life, and it also causes changes and transformations in these areas. Education is one of these areas, perhaps the most important, that technology affects. The hunter society, written with nails, made an important step with the paper's invention, and the written documents were moved from the stones to the books. The invention of computers and the internet has also opened an important milestone in human history and education. In the beginning, the course contents loaded on storage units such as floppy disks, CDs, DVDs were used by the students and teachers, computers were included in the education systems. During periods when we have not yet met with the internet, computer-assisted education has found a large place in many educational institutions and in the curriculum of education level. The development of information Technologies led to widespread use of the internet over time, and shortly thereafter examples of use in education began to increase. Computer-assisted education has also led to the rapid transition of education through internet-supported education, along with the different demands of the network society's individuals. Users are not satisfied with the internet environments where only reading authority is available, and more and more active and interacting requests have come to the agenda. Beyond reading, social networks that make it possible to comment, create content, upload/share/view images, upload video/audio files, and make video, text and voice calls have become popular for users. Social networking platforms where users interact with the environment or with other users in the environment have been attracted by the diversity of user profiles, the usage rates and durations, and the easy and versatility of accessibility. Because of these features, studies on the use of social networks in the field of education to support learning and teaching have also been accelerated and diversified. Social networks can also contain some security issues because they are huge platforms where billions of users are together. Having information about security issues as little as possible, what to do when they are encountered is important for the continuity of learning and teaching. The aim of this study is to demonstrate the importance of social networks, education, learning and teaching influences, possible security threats to be encountered in social networks, and measures to be taken. It is hoped that working in this context will shed light on the work of learners, teachers and decision makers on the subject.
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Pataraia, Nino, Anoush Margaryan, Isobel Falconer, Allison Littlejohn, and Jennifer Falconer. "Discovering academics' key learning connections." Journal of Workplace Learning 26, no. 1 (February 4, 2014): 56–72. http://dx.doi.org/10.1108/jwl-03-2013-0012.
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Purpose – The aim of this exploratory study is to investigate the role of personal networks in supporting academics' professional learning. In particular, the paper examines the composition of academics' networks and the implications of network tendencies for academics' learning about teaching. Design/methodology/approach – The study adopts a mixed-methods approach. Firstly, the composition of academics' networks is examined using social network analysis. Secondly, the role of these networks in academics' learning about teaching is analysed through semi-structured interviews. Findings – Findings reveal the prevalence of localised and strong-tie connections, which could inhibit opportunities for effective learning and spread of innovations in teaching. The study highlights the need to promote connectivity within and across institutions, creating favourable conditions for effective professional learning. Research limitations/implications – While the study makes a valuable contribution to the literature, the generalisability of these findings is limited, because the sample is restricted to 37 academics. Participants' characteristics and networking behaviours may not be fully representative of academics in a wider range of contexts and settings. Another limitation is that the evaluation of people's learning was limited to self-reported measures. Future research should measure a broader range of evidence related to academics' professional networks. Practical implications – This study extends the discussion of professional learning in academia in a novel way, by taking a social network perspective. The approach employed attempts to enrich the limited understanding of academics' networks, by unpacking the ways in which academics' personal networks support their learning. Originality/value – The originality of this work lies in its intent to uncover relationships that condition professional learning and enhancement of teaching practice. Reflection on personal networks can potentially enable individuals to determine the effectiveness of their networks and the significance of their network connections.
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Aljably, Randa, Yuan Tian, and Mznah Al-Rodhaan. "Preserving Privacy in Multimedia Social Networks Using Machine Learning Anomaly Detection." Security and Communication Networks 2020 (July 20, 2020): 1–14. http://dx.doi.org/10.1155/2020/5874935.
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Nowadays, user’s privacy is a critical matter in multimedia social networks. However, traditional machine learning anomaly detection techniques that rely on user’s log files and behavioral patterns are not sufficient to preserve it. Hence, the social network security should have multiple security measures to take into account additional information to protect user’s data. More precisely, access control models could complement machine learning algorithms in the process of privacy preservation. The models could use further information derived from the user’s profiles to detect anomalous users. In this paper, we implement a privacy preservation algorithm that incorporates supervised and unsupervised machine learning anomaly detection techniques with access control models. Due to the rich and fine-grained policies, our control model continuously updates the list of attributes used to classify users. It has been successfully tested on real datasets, with over 95% accuracy using Bayesian classifier, and 95.53% on receiver operating characteristic curve using deep neural networks and long short-term memory recurrent neural network classifiers. Experimental results show that this approach outperforms other detection techniques such as support vector machine, isolation forest, principal component analysis, and Kolmogorov–Smirnov test.
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Kato, Mitsue, and Toru Yamamoto. "Development of Neural-Net-Based Decision Support System for Mattress Patterns Using Particle Swarm Optimization." International Journal of Automation Technology 4, no. 2 (March 5, 2010): 178–83. http://dx.doi.org/10.20965/ijat.2010.p0178.
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The particle swarm optimization (PSO) concept simulating a simplified social milieu, is optimization useful for solving nonconvex continuous optimization problems. We discuss a new learning algorithm for simultaneously adjusting connection weights in neural networks and user-specified parameters included in units. Based on our algorithm, neural network learning, e.g., learning cost or adaptability, can be improved, as demonstrated in mattress decision support system.
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Deed, Craig, and Anthony Edwards. "Using Social Networks in Learning and Teaching in Higher Education." International Journal of Knowledge Society Research 1, no. 2 (April 2010): 1–12. http://dx.doi.org/10.4018/jksr.2010040101.
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Realising the potential for web-based communication in learning and teaching is challenging for educators. In this paper, the authors examine students’ attitudes toward active learning when using an unrestricted blog in an academic context and whether this can be used to support reflective and critical discussion, leading to knowledge construction. The authors collected data using an online survey with questions on student perceptions of the type, frequency and effectiveness of their strategy. Analysis of the data was conducted using Bloom’s revised taxonomy. The research indicates that students must have prior familiarity with this form of communication technology to construct knowledge in an academic context. The authors conclude that effective learning will only emerge if informed by the student experience and perspective.
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Ortega, Lorena, Ian Thompson, and Harry Daniels. "School staff advice-seeking patterns regarding support for vulnerable students." Journal of Educational Administration 58, no. 2 (November 19, 2019): 151–70. http://dx.doi.org/10.1108/jea-12-2018-0236.
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Purpose Supporting the learning and wellbeing of vulnerable students is an important yet challenging part of school educators’ work. The purpose of this paper is to investigate advice-seeking patterns around the issue of supporting the learning and wellbeing of vulnerable students, among professional staff in six English secondary schools. The paper focuses on investigating variation in advice-seeking patterns among schools, exploring the association between these patterns and staff perceptions of the school climate for collaboration, and examining how these informal advice-seeking patterns relate to formal support arrangements in the schools. Design/methodology/approach A mixed-methods approach that combined findings from social network analysis with in-depth interviews was used. Findings It was found that advice-seeking patterns among staff vary substantively, even among similar schools. Furthermore, schools with more cohesive and reciprocal advice networks also showed a stronger climate for collaboration (i.e. mutual respect and distributed leadership). Also, formal organizational structures and informal advice-seeking structures showed coherence in the sample, as formally designated leaders, such as the Headteacher and the Special Educational Needs Coordinators, were generally highly central to their schools’ advice network. Originality/value This study advances the field as there is little research that examines the social networks of educators in England, and no previous studies that explore teacher advice-seeking networks in relation to supporting vulnerable students, internationally.
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Skahill, Michael P. "The Role of Social Support Network in College Persistence among Freshman Students." Journal of College Student Retention: Research, Theory & Practice 4, no. 1 (May 2002): 39–52. http://dx.doi.org/10.2190/lb7c-9ayv-9r84-q2q5.
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This study examined the role of social support networks in student persistence among residential and commuter students at an urban technical arts college for a 12-week duration. Fifteen commuter students and 25 residential students completed the study. The research methodology was social network analysis. Findings indicate that commuter students are less likely to persist in their college studies, students residing in student housing facilities experience significant and abrupt changes in social network density. However, residential students who reported making greater numbers of new friends with connections to the school also reported attaining personal and academic goals at a rate significantly greater than other subjects. The article concludes with a discussion about the role and importance of a socially connected academic community to learning and persistence.
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Berry, Sharla. "Student Support Networks in Online Doctoral Programs: Exploring Nested Communities." International Journal of Doctoral Studies 12 (2017): 033–48. http://dx.doi.org/10.28945/3676.
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Aim/Purpose: Enrollment in online doctoral programs has grown over the past decade. A sense of community, defined as feelings of closeness within a social group, is vital to retention, but few studies have explored how online doctoral students create community. Background: In this qualitative case study, I explore how students in one online doctoral program created a learning community. Methodology: Data for the study was drawn from 60 hours of video footage from six online courses, the message boards from the six courses, and twenty interviews with first and second-year students. Contribution: Findings from this study indicate that the structure of the social network in an online doctoral program is significantly different from the structure of learning communities in face-to-face programs. In the online program, the doctoral community was more insular, more peer-centered, and less reliant on faculty support than in in-person programs. Findings: Utilizing a nested communities theoretical framework, I identified four subgroups that informed online doctoral students’ sense of community: cohort, class groups, small peer groups, and study groups. Students interacted frequently with members of each of the aforementioned social groups and drew academic, social, and emotional support from their interactions. Recommendations for Practitioners: Data from this study suggests that online doctoral students are interested in making social and academic connections. Practitioners should leverage technology and on-campus supports to promote extracurricular interactions for online students. Recommendation for Researchers: Rather than focus on professional socialization, students in the online doctoral community were interested in providing social and academic support to peers. Researchers should consider how socialization in online doctoral programs differs from traditional, face-to-face programs. Impact on Society: As universities increase online offerings, it is important to consider the issues that impact retention in online programs. By identifying the social structures that support online community, this study helps build knowledge around retention and engagement of online students. Future Research: Future research should continue to explore the unique social networks that support online students.
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Pérez-Hernando, Sara, and Nuria Fuentes-Peláez. "The Potential of Networks for Families in the Child Protection System: A Systematic Review." Social Sciences 9, no. 5 (May 6, 2020): 70. http://dx.doi.org/10.3390/socsci9050070.
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There has recently been increased interest in the potential for formal and informal networks to aid interventions with biologic families in helping them achieve reunification in the context of the child protection system. When group support is provided to families, the creation of a network of social support seems to be a consequence. The article analyzes the conceptualization of social support in order to create social support networks and the benefits on the intervention with families in the framework of the child protection system through a systematic review. From a wide search 4348 documents, finally 14 articles were included in the reviews. Results show that social support is considered a process by which social resources are provided from formal (professional services and programs associated with those services in any off the protection, health of educational systems) and informal (extended family, friends, neighbors and acquaintances) networks, allowing the families to confront daily moments as well as in crisis situations. This social support is related to emotional, psychological, physical, instrumental, material and information support that allow families to face their difficulties. Formal and informal networks of child protection systems contribute to social support, resilience, consolidation of learning and the assistance of families to social intervention programs.
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Jafarkhani, Fatemeh, Zahra Jamebozorg, and Maryam Brahman. "Application of Social Networks to Support Students' Language Learning Skills in a Blended Approach." World Family Medicine Journal/Middle East Journal of Family Medicine 15, no. 8 (October 2017): 89–95. http://dx.doi.org/10.5742/mewfm.2017.93061.
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Kumar Atmakur, Vijay, and Dr P.Siva Kumar. "A prototype analysis of machine learning methodologies for sentiment analysis of social networks." International Journal of Engineering & Technology 7, no. 2.7 (March 18, 2018): 963. http://dx.doi.org/10.14419/ijet.v7i2.7.11436.
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In present day’s social networking technologies are increased because of different user’s communication with each others. There are different types of networks are available in present situations like face book, twitter and LinkedIn. These are the valuable resources for data mining applications because of prevalence presents of different user’s information present in outside environment. Sentiment analysis is the process that defines attitudes, views, emotions and opinions from text, database sources and tweets. Sentiment analysis involves to categorize data based on different opinions like positive and negative or neutral reference classes. In this paper, we analyze different machine learning approaches to define sentiment analysis on social networks. This paper describes comparative analysis of existing machine learning approaches to classify text and other reference classes to evaluate different metric representations. And also this paper describes different machine learning methodologies like Naïve Bayesian, Entropy max and support vector machine (SVM) research on social network data streams. And also discuss major innovations to evaluate different procedures and challenges of analysis of sentiment or opinion mining aspects in present social networks.
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Shadiev, Rustam, and Yueh-Min Huang. "Exploring the influence of technological support, cultural constructs, and social networks on online cross-cultural learning." Australasian Journal of Educational Technology 36, no. 3 (June 26, 2020): 104–18. http://dx.doi.org/10.14742/ajet.6038.
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In this study, we carried out an online cross-cultural learning activity supported by speech-enabled language translation technology on a social network service with representatives from 13 nationalities. The participants were assigned into two groups: Group I discussed the traditions and related culture of interest whereas Group II discussed traditions, culture, and any other topics of interest. We tested the effectiveness of the learning activity supported by speech-enabled language translation technology on cross-cultural learning; analysed the social network; measured the cultural constructs, and investigated the relationship between the cultural constructs and cross-cultural learning. The results revealed that Group I outperformed Group II in terms of both procedural and declarative knowledge. The results showed that Group II had better social network characteristics; for example, Group I had fewer edges and a lower average network degree than Group II. In terms of cultural constructs, the results related to power distance, individualism, and uncertainty avoidance were contradictory to those of earlier research. Finally, we found no relationship between the cultural constructs and cross-cultural learning. In this paper, we discuss implications for and suggestions to the field of technology-supported cross-cultural learning based on the results.
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Weibler, Jürgen, and Sigrid Rohn-Endres. "Learning Conversation and Shared Network Leadership." Journal of Personnel Psychology 9, no. 4 (January 2010): 181–94. http://dx.doi.org/10.1027/1866-5888/a000015.
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This paper develops an understanding of how shared leadership emerges in social network interactions. On the basis of a qualitative research design (grounded theory methodology – GTM) our study in two interorganizational networks offers insights into the interplay between structures, individuals, and the collective for the emergence of shared network leadership (SNL). The network-specific Gestalt of SNL appears as a pattern of collective and individual leadership activities unified under the roof of a highly developed learning conversation. More importantly, our findings support the idea that individual network leadership would not emerge without embeddedness in certain high-quality collective processes of relating and dialogue. Both theoretical and practical implications of this original network leadership perspective are discussed.
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García-Peñalvo, F. J., J. C. González-González, and M. Murray. "MyElvin." International Journal of Knowledge Society Research 3, no. 1 (January 2012): 26–39. http://dx.doi.org/10.4018/jksr.2012010103.
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ELIN (European Languages Virtual Network) is a European Union Lifelong Learning Programme Project aimed at creating an informal social network to support and facilitate languages learning, this social environment is so called MyElvin. This social platform allows a very interesting combination of formal and informal learning activities. The research work behind this project aims to research and develop the connection between social networks, professional profiles and language learning in an informal educational context. At the core of the ELVIN project, there will be a web 2.0 social networking platform, MyElvin that connects employees/students for language practice based on their own professional/academic needs and abilities, using all relevant technologies. This paper presents the first system prototype that integrates social media and content repository.
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Liu, Ming, Abelardo Pardo, and Li Liu. "Using Learning Analytics to Support Engagement in Collaborative Writing." International Journal of Distance Education Technologies 15, no. 4 (October 2017): 79–98. http://dx.doi.org/10.4018/ijdet.2017100105.
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Online collaborative writing tools provide an efficient way to complete a writing task. However, existing tools only focus on technological affordances and ignore the importance of social affordances in a collaborative learning environment. This article describes a learning analytic system that analyzes writing behaviors, and creates visualizations incorporating individual engagement awareness and group ranking awareness (social affordance), and review writing behaviour history (technological affordance), to support student engagement. Studies examined the performance of the system used by university students in two collaborative writing activities: collaboratively writing a project proposal (N = 41) and writing tutorial discussion answers (N = 25). Results show that students agreed with what the visualization conveys and visualizations enhance their engagement in a collaborative writing activity. In addition, students stated that the visualizations were useful to help them reflect on the writing process and support the assessment of individual contributions.
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Weber, Hannes, Marc Schwenzer, and Steffen Hillmert. "Homophily in the formation and development of learning networks among university students." Network Science 8, no. 4 (April 14, 2020): 469–91. http://dx.doi.org/10.1017/nws.2020.10.
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AbstractStudents’ personal learning networks can be a valuable resource of success in higher education: they offer opportunities for academic and personal support and provide sources of information related to exams or homework. We study the determinants of learning networks using a panel study among university students in their first and second year of study. A long-standing question in social network analysis has been whether the tendency of individuals with similar characteristics to form ties is a result of preferences “choice homophily” or rather selective opportunities “induced homophily”. We expect a latent preference for homophilic learning partnerships with regard to attributes, such as gender, ability, and social origin. We estimate recently developed temporal exponential random graph models to control for previous network structure and study changes in learning ties among students. The results show that especially for males, same-gender partnerships are preferred over heterogeneous ties, while chances for tie formation decrease with the difference in academic ability among students. Social origin is a significant factor in the crosssectional exploration but does appear to be less important in the formation of new (strong) partnerships during the course of studies.
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Veletsianos, George, and Cesar Navarrete. "Online social networks as formal learning environments: Learner experiences and activities." International Review of Research in Open and Distributed Learning 13, no. 1 (January 31, 2012): 144. http://dx.doi.org/10.19173/irrodl.v13i1.1078.
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<p>While the potential of social networking sites to contribute to educational endeavors is highlighted by researchers and practitioners alike, empirical evidence on the use of such sites for formal online learning is scant. To fill this gap in the literature, we present a case study of learners’ perspectives and experiences in an online course taught using the Elgg online social network. Findings from this study indicate that learners enjoyed and appreciated both the social learning experience afforded by the online social network and supported one another in their learning, enhancing their own and other students’ experiences. Conversely, results also indicate that students limited their participation to course-related and graded activities, exhibiting little use of social networking and sharing. Additionally, learners needed support in managing the expanded amount of information available to them and devised strategies and “workarounds” to manage their time and participation.<br /><strong></strong></p>
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Feng, Yinan, Pan Zhou, Dapeng Wu, and Yuchong Hu. "Accurate Content Push for Content-Centric Social Networks: A Big Data Support Online Learning Approach." IEEE Transactions on Emerging Topics in Computational Intelligence 2, no. 6 (December 2018): 426–38. http://dx.doi.org/10.1109/tetci.2018.2804335.
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Anshari, Muhammad, Yabit Alas, and Lim Sei Guan. "Developing online learning resources: Big data, social networks, and cloud computing to support pervasive knowledge." Education and Information Technologies 21, no. 6 (May 21, 2015): 1663–77. http://dx.doi.org/10.1007/s10639-015-9407-3.
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LeBlanc, Raeann G., and Cynthia Jacelon. "SOCIAL NETWORK INFLUENCES ON SENSE OF CONTROL AND ATTRIBUTED DIGNITY IN OLDER AGE: RESEARCH RESULTS." Innovation in Aging 3, Supplement_1 (November 2019): S887. http://dx.doi.org/10.1093/geroni/igz038.3247.
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Abstract The purpose of this study was to explore the relationship between the functions of individual social networks, defined here as social support, and the outcomes of sense of control and attributed dignity among a sample of older people living with multiple chronic conditions. This study integrated an explanatory sequential (Quan/Qual) mixed methods design. Descriptive statistics were used to describe social networks. Bivariate correlations and regression statistics were used to examine the relationships of social network support (MOS-Social Support Scale) with the dependent variables of sense of control (Wallhagen Revised PCQ Questionnaire) and attributed dignity (Jacelon Attributed Dignity Scale). Open-ended interviews and thematic analysis were used to expand understanding of the quantitative findings. A cross-sectional sample of eighty-nine community dwelling older people living with multiple chronic health conditions participated. Social support, as a function of one’s social network, predicted the outcome of sense of control (β = .33, p ≤ .01) and attributed dignity (β = .44, p ≤ .001). Correlation statistics and regression models substantiated positive relationships of social supports’ influence on perceived sense of control and attributed dignity. Thematic analysis, based on open-ended interviews (n=12), expanded on the nuances of social influences on sense of control and attributed dignity in managing chronic health conditions through the themes “learning to ask for help”, “only a phone call away” and “smaller circles”. This research proposes new ways of understanding the relationships between perceptions of social support, sense of control and attributed dignity in later life in managing health.
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Azorín, Cecilia. "The emergence of professional learning networks in Spain." Journal of Professional Capital and Community 4, no. 1 (January 21, 2019): 36–51. http://dx.doi.org/10.1108/jpcc-03-2018-0012.
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Purpose The purpose of this paper is to construct a policy map of professional learning networks (PLNs) in Spain. It includes initiatives prompted in Spanish schools in which social, political, cultural and educational elements are integrated. At the same time, it analyses which organization promotes each of the networks, the objectives pursued and the scope of the network in the territory in which it is created. Design/methodology/approach The methodology followed is essentially descriptive and incorporates the first experiences with school networks which have been disseminated in the Spanish literature. It stimulates reflection on the role networks are expected to play in relation to local developments in this specific school system. Findings The cases described (Castellon, Catalonia, Malaga and Seville) suggest a way forward for practitioners to advance toward an educational paradigm based on greater collaboration. This includes a partnership approach among professionals within and across classrooms, schools, communities, districts and education systems. In particular, the results place the focus of the network on the prevalence of the following school classification, included schools (community networks linking to the territory), extended schools (socio-educational networks), equity schools (equity fostering networks) and partnership schools (school-to-school support networks), whose objectives and scopes are reviewed. Research limitations/implications With the Spanish context in mind, it is essential to recognize that more empirical evidence is still needed to make a significant contribution toward building knowledge in this research line. Indeed, sustainability seems to be an important point to consider in a short-term world where quick-fix solutions are required. However, PLNs need time to know how beneficial they really are, for example, in terms of student outcomes and school improvement. Practical implications The argument developed assumes networks as a mirror wherein the present and future of education takes place. In this sense, the scientific and educational communities have both a challenge and an opportunity to rethink the potential of networking and collaboration in education. The article tries to be attractive to a specialized reader or one simply interested in the problem of networks in education and the reality of PLNs in Spain. Social implications The network society demands a network school environment where communities are part of a local character strategy. Originality/value This document offers an interesting view on networks that not only focus on education but on social and welfare issues and it aims to target education from a broader perspective; so resulting in opening schools to the community, which is not a widely covered topic in education research. In summary, the paper can be considered as a pioneer study in the Spanish context, which contains valuable information about PLNs, their origin and current status in this part of the world.
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Gillard, Steve, Rhiannon Foster, and Kati Turner. "Evaluating the Prosper peer-led peer support network: a participatory, coproduced evaluation." Mental Health and Social Inclusion 20, no. 2 (May 9, 2016): 80–91. http://dx.doi.org/10.1108/mhsi-12-2015-0045.
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Purpose – A range of one-to-one, group and online approaches to peer support are increasingly complementing formal mental health service delivery. Evidence is emerging of the potential benefits and challenges of peer support for individuals, communities and organisations. There is more limited evidence describing peer-led peer support networks. The paper aims to discuss these issues. Design/methodology/approach – In an evaluation of Prosper, a peer-led, peer support network and social movement, members of the network played a participatory role in the design, conduct and interpretative work of the evaluation. An online survey, one-to-one interviews and group discussions were used. Findings – The evaluation describes an evolving network with planning and development meetings constituting core activity for many members alongside a monthly training programme supporting people to set up their own activities. There were strong shared values, and consensus that Prosper could strengthen social networks, improve individual well-being and impact on the way people used mental health services. Challenges were identified around feelings of uncertainty and vulnerability in relation to involvement in the network. Research limitations/implications – The participatory nature of the evaluation adds value to the learning offered. This was a descriptive evaluation; potential is indicated for the more formal modelling and testing of peer-led network and social movement initiatives. Practical implications – Clarity is needed on the relationship of the network to statutory mental health services – specifically around taking on a “service provider” role – and on the advantages and challenges of a “hybrid” organisational model that combines traditional, hierarchical and new distributed forms of leadership and structure. Social implications – Prosper demonstrated potential to create a sense of common culture based on sharing lived experience and mutual peer support, providing an alternative to the traditional culture of mental health services. Originality/value – This paper offers wider learning derived from evaluation of a highly original initiative in peer leadership, network structure and interface with statutory mental health services.
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Tu, Chih-Hsiung, Cherng-Jyh Yen, J. Michael Blocher, and Junn-Yih Chan. "A Study of the Predictive Relationship Between Online Social Presence and ONLE Interaction." International Journal of Distance Education Technologies 10, no. 3 (July 2012): 53–66. http://dx.doi.org/10.4018/jdet.2012070104.
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Open Network Learning Environments (ONLE) are online networks that afford learners the opportunity to participate in creative content endeavors, personalized identity projections, networked mechanism management, and effective collaborative community integration by applying Web 2.0 tools in open environments. It supports social interaction by integrating User-Generated Content, Participatory Web, digital identities, social and networking linkages, and collaborative learning community to allow learners manage and tailor their social presence. The purposes of this study were to assess the predictive relationship between online social presence and overall ONLE’s social interaction and examine the predictive relationships between online social presence and four dimensions of ONLE’s interaction (i.e., cognitive, social, networking, and integration). The results of this study did not support the role of online social presence as a predictor for overall ONLE’s social interaction. Although social presence can serve as a predictor for networking and integration dimensions, social presence cannot serve as a predictor for cognitive and social dimensions. This study suggests CMC and ONLE have different dynamics in social interaction. ONLE focuses on “social and “networking” linkages to transform online learners into “network learners” to project their ideal and preferred “network social presence” rather than online social presence.
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Garbach, Kelly, and Geoffrey P. Morgan. "Grower networks support adoption of innovations in pollination management: The roles of social learning, technical learning, and personal experience." Journal of Environmental Management 204 (December 2017): 39–49. http://dx.doi.org/10.1016/j.jenvman.2017.07.077.
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De Juan-Jordán, Hugo, María Guijarro-García, and Javier Guardiola-Contreras. "Corporate Social Networks Applied in the Classroom." Multidisciplinary Journal for Education, Social and Technological Sciences 3, no. 2 (October 3, 2016): 156. http://dx.doi.org/10.4995/muse.2016.6342.
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<p class="Textoindependiente21"><span lang="EN-US">The impact of online social networks has been extensive because of the new way they enable not only in terms of the relation, communication and collaboration among people, but also between people and businesses. So much so, their use is already habitual within organizations, known as Corporate Social Networks, in order to achieve the same benefits.</span></p><p class="Textoindependiente21">The present study aims to analyze the advantages these corporate social networks have in the classroom seen as a micro-organization where a group of students interact, work and collaborate during a master´s or postgraduate course. To support this research, during 2015 a corporate social network (Yammer) has been introduced to 5 groups of students of various master´s in the prestigious business school ESIC. The feedback obtained from those students and some examples of classroom dynamics prove the usefulness and great value of a corporate social network in postgraduate classes, although some common difficulties and considerations raised by the students themselves have to be taken into account in order to manage its optimal adoption in class.</p><p class="Textoindependiente21">This study also tries to propose some guidelines and best practices obtained as a result of the experience of use and the adoption of social networks in class in order to improve the learning process and innovate in the methodology applied to education.</p>
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Tauginienė, Loreta, and Rima Kalinauskaitė. "Participation of doctoral students in online social networks." Studies in Graduate and Postdoctoral Education 9, no. 2 (November 16, 2018): 144–64. http://dx.doi.org/10.1108/sgpe-d-18-00002.
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Purpose This paper aims to examine the use of online social networks by doctoral students. Design/methodology/approach A quantitative online survey was conducted – 448 doctoral students from 15 universities and 11 research institutes in Lithuania were asked about their participation in both academic and non-academic online social networks. Findings The results show that despite efforts to link academics to society, doctoral students are not supported by universities/research institutes nor are doctoral students trained for this purpose, including regarding such threats as offensive posts. Additionally, more comprehensive information is disclosed in academic social networks, but these networks are less common and less frequently used. Research limitations/implications International doctoral students in Lithuania cover about 4.4 per cent of the total population of doctoral students. They were not invited to participate in the survey. Furthermore, doctoral students consider any online social network as their professional (academic) network, as was found from our results. This resulted in the confusion of our definition of academic online social networks. Practical implications Learning about the diverse online roles doctoral students may take could be facilitated were doctoral students to receive clear and consistent awareness-raising and develop self-awareness in the importance of the roles, the most central online social networks and potential threats, and related institutional support to address them. Originality/value This study provides results on how engagement of doctoral students in online social networks might affect their links with society and what academic institutions should promote in doctoral education.
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Ardito, Gerald, and Betül Czerkawski. "The Development of Autonomous Student Learning Networks: Patterns of Interactions in an Open World Learning Environment for Teachers Exploring Teaching with and through Computer Science." Sustainability 13, no. 16 (August 4, 2021): 8696. http://dx.doi.org/10.3390/su13168696.
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This pilot case study sought to investigate patterns of interactions between learners and their instructor in a teacher education course called “Computer Science for Teachers”. This course was constructed to leverage aspects of open world game design elements in order to investigate the effects of degrees of autonomy in gameplay/learning. This course was conducted in a specially built social learning platform based on Elgg software. Student interactions with the instructor and other students in this course were analyzed to determine the learning networks students constructed during each key learning activity as well as the epistemic spaces defined by these interactions. Descriptive statistics along with social network analysis (SNA) and epistemic network analysis (ENA) were used to investigate these data. The findings indicate that more traditional/less open world gaming type learning activities were associated with learning networks and epistemic spaces that were teacher-centered and narrower, while more open world gaming/high levels of autonomy (student-centric) learning activities were associated with learning networks that were highly decentralized and epistemic spaces that featured students asking and answering questions of/for one another. These findings were consistent with existing research into player behavior in open world type games and learner behavior in settings with high levels of autonomy support. Implications for further research are discussed.
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Pang, Bo, Erik Nijkamp, and Ying Nian Wu. "Deep Learning With TensorFlow: A Review." Journal of Educational and Behavioral Statistics 45, no. 2 (September 10, 2019): 227–48. http://dx.doi.org/10.3102/1076998619872761.
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This review covers the core concepts and design decisions of TensorFlow. TensorFlow, originally created by researchers at Google, is the most popular one among the plethora of deep learning libraries. In the field of deep learning, neural networks have achieved tremendous success and gained wide popularity in various areas. This family of models also has tremendous potential to promote data analysis and modeling for various problems in educational and behavioral sciences given its flexibility and scalability. We give the reader an overview of the basics of neural network models such as the multilayer perceptron, the convolutional neural network, and stochastic gradient descent, the most commonly used optimization method for neural network models. However, the implementation of these models and optimization algorithms is time-consuming and error-prone. Fortunately, TensorFlow greatly eases and accelerates the research and application of neural network models. We review several core concepts of TensorFlow such as graph construction functions, graph execution tools, and TensorFlow’s visualization tool, TensorBoard. Then, we apply these concepts to build and train a convolutional neural network model to classify handwritten digits. This review is concluded by a comparison of low- and high-level application programming interfaces and a discussion of graphical processing unit support, distributed training, and probabilistic modeling with TensorFlow Probability library.
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Cannavacciuolo, Lorella, Luca Iandoli, Cristina Ponsiglione, and Giuseppe Zollo. "Learning by failure vs learning by habits." International Journal of Entrepreneurial Behavior & Research 23, no. 3 (May 2, 2017): 524–46. http://dx.doi.org/10.1108/ijebr-11-2015-0238.
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Purpose The purpose of this paper is to explain the emergence of collaboration networks in entrepreneurial clusters as determined by the way entrepreneurs exchange knowledge and learn through business transactions needed to implement temporary supply chains in networks of co-located firms. Design/methodology/approach A socio-computational approach is adopted to model business transactions and supply chain formation in Marshallian industrial districts (IDs). An agent-based model is presented and used as a virtual lab to test the hypotheses between the firms’ behaviour and the emergence of structural properties at the system level. Findings The simulation findings and their validation based on the comparison with a real world cluster show that the topological properties of the emerging network are influenced by the learning strategies and decision-making criteria firms use when choosing partners. With reference to the specific case of Marshallian IDs it is shown that inertial learning based on history and past collaboration represents in the long term a major impediment for the emergence of hubs and of a network topology that is more conducive to innovation and growth. Research limitations/implications The paper offers an alternative view of entrepreneurial learning (EL) as opposed to the dominant view in which learning occurs as a result of exceptional circumstances (e.g. failure). The results presented in this work show that adaptive, situated, and day-by-day learning has a profound impact on the performance of entrepreneurial clusters. These results are encouraging to motivate additional research in areas such as in modelling learning or in the application of the proposed approach to the analysis of other types of entrepreneurial ecosystems, such as start-up networks and makers’ communities. Practical implications Agent-based model can support policymakers in identifying situated factors that can be leveraged to produce changes at the macro-level through the identification of suitable incentives and social networks re-engineering. Originality/value The paper presents a novel perspective on EL and offers evidence that micro-learning strategies adopted and developed in routine business transactions do have an impact on firms’ performances (survival and growth) as well as on systemic performances related to the creation and diffusion of innovation in firms networks.
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Soumplis, Alexandros, Eleni Koulocheri, Nektarios Kostaras, Nikos Karousos, and Michalis Xenos. "Learning Management Systems and Learning 2.0." International Journal of Web-Based Learning and Teaching Technologies 6, no. 4 (October 2011): 1–18. http://dx.doi.org/10.4018/jwltt.2011100101.
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The unprecedented growth of Web 2.0 has affected learning and has made the growth of learning networks possible. Learning networks are shaped by communities to help their members acquire knowledge in specific areas and are the most notable feature of Learning 2.0, the new learning era that focuses on individual learning needs. The evolution of learning forces traditional Learning Management Systems (LMS) to incorporate more Web 2.0 features and slowly transform to Personal Learning Environments (PLEs). A Personal Learning Environment is a loosely structured collection of tools with strong social networking characteristics, which gives users the ability to create, maintain, and redistribute their own learning content. This paper is a field study of the most well-known and established LMSs and their support for specific features within several categories of tools of Web 2.0. The incorporation of Web 2.0 features within those LMSs differentiates them regarding their ability and potential to be used as PLEs.
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Brandl, Hanja B., Damien R. Farine, Caterina Funghi, Wiebke Schuett, and Simon C. Griffith. "Early-life social environment predicts social network position in wild zebra finches." Proceedings of the Royal Society B: Biological Sciences 286, no. 1897 (February 27, 2019): 20182579. http://dx.doi.org/10.1098/rspb.2018.2579.
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Early-life experience can fundamentally shape individual life-history trajectories. Previous research has suggested that exposure to stress during development causes differences in social behaviour later in life. In captivity, juvenile zebra finches exposed to elevated corticosterone levels were less socially choosy and more central in their social networks when compared to untreated siblings. These differences extended to other aspects of social life, with ‘stress-exposed’ juveniles switching social learning strategies and juvenile males less faithfully learning their father's song. However, while this body of research suggests that the impacts of early-life stress could be profound, it remains unknown whether such effects are strong enough to be expressed under natural conditions. Here, we collected data on social associations of zebra finches in the Australian desert after experimentally manipulating brood sizes. Juveniles from enlarged broods experienced heightened sibling competition, and we predicted that they would express similar patterns of social associations to stress-treated birds in the captive study by having more, but less differentiated, relationships. We show striking support for the suggested consequences of developmental stress on social network positions, with our data from the wild replicating the same results in 9 out of 10 predictions previously tested in captivity. Chicks raised in enlarged broods foraged with greater numbers of conspecifics but were less ‘choosy’ and more central in the social network. Our results confirm that the natural range of variation in early-life experience can be sufficient to predict individuals' social trajectories and support theory highlighting the potential importance of developmental conditions on behaviour.
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Vanichvatana, Sonthya. "How social network applications enhancing team project collaborations at home." Cypriot Journal of Educational Sciences 15, no. 2 (April 30, 2020): 386–98. http://dx.doi.org/10.18844/cjes.v15i2.4812.
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Team project collaboration is an important teaching and learning activity. Informal learning spaces are required to support such outside classrooms learning activity. There are increasing numbers of students who use virtual space platforms and social network applications (SNA) to support team project works at home. The objectives of this study were to understand how students used SNA to support team project works at home, how they learn about SNA, students’ views of pro and con of SNA, and how much students need any supports from higher education institutions on this matter. This research used business students of a Bangkok private university as a case study. The results showed that though numerous advantages of SNA, students still valued face-to-face meetings in many phases of a team project. Students with higher cumulative grade point averages reflected higher proportions of needs for universities to teach them how to use SNA for team project collaboration at home than the lower cumulative grade point average students.
Keywords: Higher education institutions; Home; Informal learning spaces; Social network applications; Virtual spaces
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Aleksic-Miric, Ana. "Inter-organizational design fit in inter-organizational knowledge management." Sociologija 56, no. 3 (2014): 343–63. http://dx.doi.org/10.2298/soc1403343a.
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The purpose of this paper is to analyze existing knowledge on how organizations learn using multilevel comparison perspective of intra- and inter-organizational learning and to offer deeper understanding of the role that organizational design properties have in inter-organizational learning. Using Argote and Ophir (2005) findings on similarity vs complementarity fit developed for intra-organizational learning as an anchor, we analyze the role similarity vs complementarity fit of organizational configuration and coordination properties in inter-organizational settings. Our intention is to explicitly express the role of interorganizational design fit in inter-organizational knowledge management. Framework developed here systematizes and explains how strategic objectives of network creation (exploration or exploitation) should be aligned with learning mechanisms (learning by doing or learning by listening/observing) and organizational design properties. From the point of organization theory, this paper advances knowledge about the influence organizational design as intra-organizational property has on knowledge transfer between organizations and inter-organizational learning. Our framework helps managers understand how inter-organizational design fit can influence inter-organizational learning within the network. With regard to policy making, knowledge networks are becoming increasingly important as a mechanism of industrial development support, economic growth, increase of employment and poverty reduction and this paper points to mechanisms of inter-organizational design that can be used in managing these networks.
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Bates, Claire. "Supported Loving – developing a national network to support positive intimate relationships for people with learning disabilities." Tizard Learning Disability Review 24, no. 1 (March 8, 2019): 13–19. http://dx.doi.org/10.1108/tldr-06-2018-0017.
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Purpose The purpose of this paper is to outline the work of the Supported Loving Network from its origin in academic research to the practical development of a national Network supporting relationships for people with learning disabilities. Design/methodology/approach First, the need for the Network is established through a review of the research literature. The paper goes on to critically discuss the Network’s progress to date including its limitations and difficulties encountered, concluding by considering plans for future growth and development. Findings There is evidence that having a national Network is helpful in supporting intimate relationships for people with learning disabilities. The Network is having a positive impact on professionals who support people with learning disabilities by providing a space for discussion, inspiration and to share positive practice. However, an increase in resources would enable Supported Loving to have a wider reach and possibly a greater influence on organisations that provide social care to adults with learning disabilities. Originality/value The research indicates that people with learning disabilities are still less likely to have a loving relationship. The level of interest and engagement with Supported Loving implies that the Network is of value to people with learning disabilities and the professionals who work with them.
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Murphy, Dom, Abbie Deeming, Helen Millward, and Julie Jones. "Social Media Networks and Community Development in Work-based Undergraduate Students." Polish Journal of Educational Studies 72, no. 1 (December 1, 2019): 5–23. http://dx.doi.org/10.2478/poljes-2019-0002.
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AbstractThe purpose of the study was to explore how students on two related work-based degree courses with limited opportunities for face to face interaction used social media platforms to support their experiences and learning. The students involved work as teaching assistants in a range of mainstream and special schools in the East Midlands and attend classes one day a week. It was noted by tutors that students made frequent references to using various social media platforms for sharing student-to-student information relating to the taught sessions or assignments in preference to the university’s virtual learning environment. To investigate this phenomenon, a case study approach, using focus groups and a paired interview, was adopted. The entire student population on the courses was invited to participate, so the sample was self-selecting and a total of 11% of the students volunteered, participating in either a focus group discussion or paired interview. The study found that students made extensive use of social media platforms, mainly Facebook and Whatsapp, for academic and affective support. Students found this to be an effective way to keep in touch with one another away from university, to share resources and experiences and felt that it helped with their identity as a higher education student.
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JangMook Kang, and SookYoung Choi. "An E-learning Support System based on Location-based Social Network." International Journal of Advancements in Computing Technology 3, no. 7 (August 31, 2011): 55–63. http://dx.doi.org/10.4156/ijact.vol3.issue7.8.
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Heiman, Tali. "Social support networks, stress, sense of coherence and academic success of university students with learning disabilities." Social Psychology of Education 9, no. 4 (December 12, 2006): 461–78. http://dx.doi.org/10.1007/s11218-006-9007-6.
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Punia, Sanjeev Kumar, Manoj Kumar, Thompson Stephan, Ganesh Gopal Deverajan, and Rizwan Patan. "Performance Analysis of Machine Learning Algorithms for Big Data Classification." International Journal of E-Health and Medical Communications 12, no. 4 (July 2021): 60–75. http://dx.doi.org/10.4018/ijehmc.20210701.oa4.
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In broad, three machine learning classification algorithms are used to discover correlations, hidden patterns, and other useful information from different data sets known as big data. Today, Twitter, Facebook, Instagram, and many other social media networks are used to collect the unstructured data. The conversion of unstructured data into structured data or meaningful information is a very tedious task. The different machine learning classification algorithms are used to convert unstructured data into structured data. In this paper, the authors first collect the unstructured research data from a frequently used social media network (i.e., Twitter) by using a Twitter application program interface (API) stream. Secondly, they implement different machine classification algorithms (supervised, unsupervised, and reinforcement) like decision trees (DT), neural networks (NN), support vector machines (SVM), naive Bayes (NB), linear regression (LR), and k-nearest neighbor (K-NN) from the collected research data set. The comparison of different machine learning classification algorithms is concluded.