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Kortemeyer, G. (2017). The Spectrum of Learning Analytics. eleed, Iss. 12. (urn:nbn:de:0009-5-45384)

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%0 Journal Article
%T The Spectrum of Learning Analytics
%A Kortemeyer, Gerd
%J eleed
%D 2017
%V 12
%N 1
%@ 1860-7470
%F kortemeyer2017
%X "Learning Analytics" became a buzzword during the hype surrounding the advent of "big data" MOOCs, however, the concept has been around for over two decades. When the first online courses became available it was used as a tool to increase student success in particular courses, frequently combined with the hope of conducting educational research. In recent years, the same term started to be used on the institutional level to increase retention and decrease time-to-degree. These two applications, within particular courses on the one hand and at the institutional level on the other, are at the two extremes of the spectrum of Learning Analytics – and they frequently appear to be worlds apart. The survey describes affordances, theories and approaches in these two categories.
%L 370
%K assessment
%K data mining
%K e-learning
%K educational data mining
%K learning analytics
%K personalization
%U http://nbn-resolving.de/urn:nbn:de:0009-5-45384

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@Article{kortemeyer2017,
  author = 	"Kortemeyer, Gerd",
  title = 	"The Spectrum of Learning Analytics",
  journal = 	"eleed",
  year = 	"2017",
  volume = 	"12",
  number = 	"1",
  keywords = 	"assessment; data mining; e-learning; educational data mining; learning analytics; personalization",
  abstract = 	"``Learning Analytics'' became a buzzword during the hype surrounding the advent of ``big data'' MOOCs, however, the concept has been around for over two decades. When the first online courses became available it was used as a tool to increase student success in particular courses, frequently combined with the hope of conducting educational research. In recent years, the same term started to be used on the institutional level to increase retention and decrease time-to-degree. These two applications, within particular courses on the one hand and at the institutional level on the other, are at the two extremes of the spectrum of Learning Analytics -- and they frequently appear to be worlds apart. The survey describes affordances, theories and approaches in these two categories.",
  issn = 	"1860-7470",
  url = 	"http://nbn-resolving.de/urn:nbn:de:0009-5-45384"
}

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TY  - JOUR
AU  - Kortemeyer, Gerd
PY  - 2017
DA  - 2017//
TI  - The Spectrum of Learning Analytics
JO  - eleed
VL  - 12
IS  - 1
KW  - assessment
KW  - data mining
KW  - e-learning
KW  - educational data mining
KW  - learning analytics
KW  - personalization
AB  - "Learning Analytics" became a buzzword during the hype surrounding the advent of "big data" MOOCs, however, the concept has been around for over two decades. When the first online courses became available it was used as a tool to increase student success in particular courses, frequently combined with the hope of conducting educational research. In recent years, the same term started to be used on the institutional level to increase retention and decrease time-to-degree. These two applications, within particular courses on the one hand and at the institutional level on the other, are at the two extremes of the spectrum of Learning Analytics – and they frequently appear to be worlds apart. The survey describes affordances, theories and approaches in these two categories.
SN  - 1860-7470
UR  - http://nbn-resolving.de/urn:nbn:de:0009-5-45384
ID  - kortemeyer2017
ER  -

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Wordbib

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ISI

PT Journal
AU Kortemeyer, G
TI The Spectrum of Learning Analytics
SO eleed
PY 2017
VL 12
IS 1
DE assessment; data mining; e-learning; educational data mining; learning analytics; personalization
AB "Learning Analytics" became a buzzword during the hype surrounding the advent of "big data" MOOCs, however, the concept has been around for over two decades. When the first online courses became available it was used as a tool to increase student success in particular courses, frequently combined with the hope of conducting educational research. In recent years, the same term started to be used on the institutional level to increase retention and decrease time-to-degree. These two applications, within particular courses on the one hand and at the institutional level on the other, are at the two extremes of the spectrum of Learning Analytics – and they frequently appear to be worlds apart. The survey describes affordances, theories and approaches in these two categories.
ER

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Full Metadata

Bibliographic Citation	e-learning and education, Iss. 12
Title	The Spectrum of Learning Analytics (eng)
Author	Gerd Kortemeyer
Language	eng
Abstract	"Learning Analytics" became a buzzword during the hype surrounding the advent of "big data" MOOCs, however, the concept has been around for over two decades. When the first online courses became available it was used as a tool to increase student success in particular courses, frequently combined with the hope of conducting educational research. In recent years, the same term started to be used on the institutional level to increase retention and decrease time-to-degree. These two applications, within particular courses on the one hand and at the institutional level on the other, are at the two extremes of the spectrum of Learning Analytics – and they frequently appear to be worlds apart. The survey describes affordances, theories and approaches in these two categories.
Subject	assessment, data mining, e-learning, educational data mining, learning analytics, personalization
Classified Subjects	ddc 005.7, data in computer systems 005.74, data files and databases 153.15, learning 371.26, examination and tests; academicx prognosis and placement 371.358, electronic distance education 378.3, student aid and related topics pacs C6130M, multimedia D2030, education and training IT applications D2080, information services and database systems in it
DDC	370
Rights	fDPPL
URN:	urn:nbn:de:0009-5-45384