Titlebook: Advances in Social Networking-based Learning; Machine Learning-bas Christos Troussas,Maria Virvou Book 2020 Springer Nature Switzerland AG

Suture

书目名称Advances in Social Networking-based Learning影响因子(影响力)




书目名称Advances in Social Networking-based Learning影响因子(影响力)学科排名




书目名称Advances in Social Networking-based Learning网络公开度




书目名称Advances in Social Networking-based Learning网络公开度学科排名




书目名称Advances in Social Networking-based Learning被引频次




书目名称Advances in Social Networking-based Learning被引频次学科排名




书目名称Advances in Social Networking-based Learning年度引用




书目名称Advances in Social Networking-based Learning年度引用学科排名




书目名称Advances in Social Networking-based Learning读者反馈




书目名称Advances in Social Networking-based Learning读者反馈学科排名

neutralize

雪白

Intelligent, Adaptive and Social e-Learning in POLYGLOT,hey involve the development of modeling, diagnostic, feedback and reasoning techniques towards creating a student-centered learning environment. Therefore, there have been systems that combine all of the above technologies for tutoring specific domains. However, there have also been domain independe

motivate

Observe

Affective Computing and Motivation in Educational Contexts: Data Pre-processing and Ensemble Learni and elaborating human affections. It is a field that spans computer science, psychology and cognitive science. Nowadays, affective computing is considered to play a vital role in the field of e-learning since knowledge acquisition can be greatly affected by the changing emotional states of learners

仲裁者

,Blending Machine Learning with Krashen’s Theory and Felder-Silverman Model for Student Modeling,al networking-based learning and e-learning. As a testbed for our research, we have designed and fully implemented POLYGLOT, namely a social networking-based intelligent and adaptive tutoring system for the learning foreign languages. POLYGLOT incorporates the following theories, models and techniqu

泰然自若

共和国

Overview of POLYGLOT Architecture and Implementation,re. POLYGLOT is comprised of the following modules: Social Media User Interface module, Learning content module, Student model, Error diagnosis module, Win-Win Collaboration module, Frustration Recognition and Response module (Affective module), Learning style detection module and Adaptation model.

配偶

ALT

Conclusions,ising from the utilization of social networks in this field. Indeed, the utilization of social networks in the field of e-learning brings considerable changes in the domain of knowledge acquisition since the features and capabilities of social networks create a new era in technology-aided instructio