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001 978-981-15-4526-9
003 DE-He213
005 20210226030739.0
007 cr nn 008mamaa
008 200508s2020 si | s |||| 0|eng d
020 _a9789811545269
_9978-981-15-4526-9
024 7 _a10.1007/978-981-15-4526-9
_2doi
050 4 _aLC8-6691
072 7 _aJNV
_2bicssc
072 7 _aEDU039000
_2bisacsh
072 7 _aJNV
_2thema
082 0 4 _a371.33
_223
245 1 0 _aRadical Solutions and Learning Analytics
_h[electronic resource] :
_bPersonalised Learning and Teaching Through Big Data /
_cedited by Daniel Burgos.
250 _a1st ed. 2020.
264 1 _aSingapore :
_bSpringer Singapore :
_bImprint: Springer,
_c2020.
300 _aXIV, 227 p. 63 illus., 41 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Educational Technology,
_x2196-4963
505 0 _a1 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.
520 _aLearning 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.
650 0 _aEducational technology.
650 0 _aLearning.
650 0 _aInstruction.
650 0 _aHigher education.
650 1 4 _aEducational Technology.
_0https://scigraph.springernature.com/ontologies/product-market-codes/O21000
650 2 4 _aTechnology and Digital Education.
_0https://scigraph.springernature.com/ontologies/product-market-codes/O47000
650 2 4 _aLearning & Instruction.
_0https://scigraph.springernature.com/ontologies/product-market-codes/O22000
650 2 4 _aHigher Education.
_0https://scigraph.springernature.com/ontologies/product-market-codes/O36000
700 1 _aBurgos, Daniel.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789811545252
776 0 8 _iPrinted edition:
_z9789811545276
776 0 8 _iPrinted edition:
_z9789811545283
830 0 _aLecture Notes in Educational Technology,
_x2196-4963
856 4 0 _uhttps://doi.org/10.1007/978-981-15-4526-9
912 _aZDB-2-EDA
912 _aZDB-2-SXED
999 _c102385
_d102385