Research with simulated data

Arnon Hershkovitz; Simon Knight; Jelena Jovanovic; Shane Dawson; Dragan Gašević

doi:10.18608/jla.2017.41.1

Research with simulated data

Arnon Hershkovitz, Simon Knight, Jelena Jovanovic, Shane Dawson, Dragan Gašević

Research output: Contribution to journal › Editorial › Other › peer-review

Abstract

This first issue of the Journal of Learning Analytics in 2017 features a special section of invited papers from the recent Learning Analytics and Knowledge conference (LAK'16). The theme of the conference, and this special section, relates to the need for Learning Analytics research to challenge our methodological and theoretical assumptions and build new interdisciplinary connections to further our thinking.

Original language	English
Pages (from-to)	1-2
Number of pages	2
Journal	Journal of Learning Analytics
Volume	4
Issue number	1
DOIs	https://doi.org/10.18608/jla.2017.41.1
Publication status	Published - 2017
Externally published	Yes

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10.18608/jla.2017.41.1

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Cite this

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title = "Research with simulated data",

abstract = "This first issue of the Journal of Learning Analytics in 2017 features a special section of invited papers from the recent Learning Analytics and Knowledge conference (LAK'16). The theme of the conference, and this special section, relates to the need for Learning Analytics research to challenge our methodological and theoretical assumptions and build new interdisciplinary connections to further our thinking.",

author = "Arnon Hershkovitz and Simon Knight and Jelena Jovanovic and Shane Dawson and Dragan Ga{\v s}evi{\'c}",

year = "2017",

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language = "English",

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AU - Knight, Simon

AU - Jovanovic, Jelena

AU - Dawson, Shane

AU - Gašević, Dragan

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AB - This first issue of the Journal of Learning Analytics in 2017 features a special section of invited papers from the recent Learning Analytics and Knowledge conference (LAK'16). The theme of the conference, and this special section, relates to the need for Learning Analytics research to challenge our methodological and theoretical assumptions and build new interdisciplinary connections to further our thinking.

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DO - 10.18608/jla.2017.41.1

M3 - Editorial

VL - 4

SP - 1

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JO - Journal of Learning Analytics

JF - Journal of Learning Analytics

SN - 1929-7750

IS - 1

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