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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:0009-5-45384Download
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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" }Download
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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 -Download
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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. ERDownload
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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 |
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DDC | 370 |
Rights | fDPPL |
URN: | urn:nbn:de:0009-5-45384 |