LEADER 04904nam 22006015 450 001 9910484947303321 005 20200629153555.0 010 $a3-030-39130-2 024 7 $a10.1007/978-3-030-39130-0 035 $a(CKB)4100000010118946 035 $a(MiAaPQ)EBC6027282 035 $a(DE-He213)978-3-030-39130-0 035 $a(iGPub)SPNA0066191 035 $z(PPN)258859318 035 $a(PPN)243770154 035 $a(EXLCZ)994100000010118946 100 $a20200120d2020 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvances in Social Networking-based Learning $eMachine Learning-based User Modelling and Sentiment Analysis /$fby Christos Troussas, Maria Virvou 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (xii, 176 pages) 225 1 $aIntelligent Systems Reference Library,$x1868-4394 ;$v181 311 $a3-030-39129-9 327 $aIntroduction -- Related Work -- Intelligent, Adaptive and social e-learning in POLYGLOT. . 330 $aThis book discusses three important, hot research issues: social networking-based learning, machine learning-based user modeling and sentiment analysis. Although these three technologies have been widely used by researchers around the globe by academic disciplines and by R&D departments in the IT industry, they have not yet been used extensively for the purposes of education. The authors present a novel approach that uses adaptive hypermedia in e-learning models to personalize educational content and learning resources based on the needs and preferences of individual learners. According to reports, in 2018 the vast majority of internet users worldwide are active on social networks, and the global average social network penetration rate as of 2018 is close to half the population. Employing social networking technologies in the field of education allows the latest technological advances to be used to create interactive educational environments where students can learn, collaborate with peers and communicate with tutors while benefiting from a social and pedagogical structure similar to a real class. The book first discusses in detail the current trend of social networking-based learning. It then provides a novel framework that moves further away from digital learning technologies while incorporating a wide range of recent advances to provide solutions to future challenges. This approach incorporates machine learning to the student-modeling component, which also uses conceptual frameworks and pedagogical theories in order to further promote individualization and adaptivity in e-learning environments. Moreover, it examines error diagnosis, misconceptions, tailored testing and collaboration between students are examined and proposes new approaches for these modules. Sentiment analysis is also incorporated into the general framework, supporting personalized learning by considering the user?s emotional state, and creating a user-friendly learning environment tailored to students? needs. Support for students, in the form of motivation, completes the framework. This book helps researchers in the field of knowledge-based software engineering to build more sophisticated personalized educational software, while retaining a high level of adaptivity and user-friendliness within human?computer interactions. Furthermore, it is a valuable resource for educators and software developers designing and implementing intelligent tutoring systems and adaptive educational hypermedia systems. . 410 0$aIntelligent Systems Reference Library,$x1868-4394 ;$v181 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aEducational technology 606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aTechnology and Digital Education$3https://scigraph.springernature.com/ontologies/product-market-codes/O47000 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 0$aEducational technology. 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 615 24$aTechnology and Digital Education. 676 $a371.334 700 $aTroussas$b Christos$4aut$4http://id.loc.gov/vocabulary/relators/aut$0871778 702 $aVirvou$b Maria$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484947303321 996 $aAdvances in Social Networking-based Learning$91984977 997 $aUNINA