371.33 <br/>
          Radical Solutions and Learning Analytics Personalised Learning and Teaching Through Big Data /  [electronic resource] : 
  edited by Daniel Burgos.
 - 1st ed. 2020. 
.- Singapore :: : , 2020., 
.- XIV, 227 p. 63 illus., 41 illus. in color.,  online resource. 
-ISBN 9789811545269 
 <br/>  - Lecture Notes in Educational Technology,  2196-4963 
  <br/> - SpringerLink (Online service), 
 - Lecture Notes in Educational Technology, .
<br/><br/>1 Learning Analytics as a Breakthrough in Educational Improvement -- 2 LA to Improve the Learner's Performance -- 3 LA to Improve the Teacher's Performance -- 4 Dashboards for a Better Application of LA -- 5 Mobile LA in Digital Devices -- 6 Physical Sensors and LA in the Classroom -- 7 Remote Labs and Big Data -- 8 Understanding Big Data for Educational Management -- 9 Interpretation of Live Data and Decision Making in Streamed Lessons and Real-Time User Tracking -- 10 Prediction of Users' Behaviour -- 11 Prevention of Students and Faculty Attrition -- 12 Personalised Mentoring Through Quantitative & Qualitative Data -- 13 User Vectorisation Through Deep Learning and Neural Networks -- 14 Fighting Student's Drop-Out Through Historical Data -- 15 Visual Analytics for a Better Impact of Deep Data. 
<br/><br/> Learning Analytics become the key for Personalised Learning and Teaching thanks to the storage, categorisation and smart retrieval of Big Data. Thousands of user data can be tracked online via Learning Management Systems, instant messaging channels, social networks and other ways of communication. Always with the explicit authorisation from the end user, being a student, a teacher, a manager or a persona in a different role, an instructional designer can design a way to produce a practical dashboard that helps him improve that very user’s performance, interaction, motivation or just grading. This book provides a thorough approach on how education, as such, from teaching to learning through management, is improved by a smart analysis of available data, making visible and useful behaviours, predictions and patterns that are hinder to the regular eye without the process of massive data. 
<br/><br/><label>Standard No.: </label>10.1007/978-981-15-4526-9  doi 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Educational technology.<br/>Learning.<br/>Instruction.<br/>Higher education.<br/>Educational Technology.<br/>Technology and Digital Education.<br/>Learning & Instruction.<br/>Higher Education.
<br/><br/><label>LC Class. No.: </label>LC8-6691 
<br/><br/><label>Тавиурын заалт: </label>371.33