LAK

LAK
International Learning Analytics & Knowledge Confrence
Categories: Learning Analytics
https://www.solaresearch.org/events/lak/
Bibliography:	dblp.uni-trier.de/db/conf/lak/
Avg. acceptance rate:	30.4
Table of Contents

International Learning Analytics & Knowledge Confrence (LAK) has an average acceptance rate of 30.4% .

Events

The following events of the series LAK are currently known in this wiki:

	Ordinal	From	To	City	Country	General chair	PC chair	Submitted papers	Acceptance rate	Attendees
LAK 2021	11	Apr 12	Apr 16
LAK 2020		Mar 23	Mar 27	Frankfurt am Main	Germany		Katrien Verbert Maren Scheffel Niels Pinkwart Vitomir Kovanovic
LAK 2019		Mar 4	Mar 8	Tempe	USA	Christopher Brooks Ulrich Hoppe
LAK 2018		Mar 5	Mar 9	Sydney	Australia	Abelardo Pardo Kathryn Bartimote-Aufflick Grace Lynch	Simon Buckingham Shum Rebecca Ferguson Agathe Merceron Xavier Ochoa	115	30.4
LAK 2017		Mar 13	Mar 17	Vancouver	Canada
LAK 2016		Mar 25	Mar 29	Edinburgh	UK
LAK 2015		Mar 16	Mar 20	Poughkeepsie	USA
LAK 2014		Mar 24	Mar 28	Indianapolis	USA
LAK 2013		Apr 8	Apr 12	Leuven	Belgium
LAK 2012		Apr 29	May 2	Vancouver	Canada
LAK 2011		Feb 27	Mar 1	Banff	Canada

Number of Submitted and Accepted Papers (Main Track)

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Acceptance Rate

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Locations

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The International Conference on Learning Analytics & Knowledge is the premier research forum in the field, providing common ground for all stakeholders in the design of analytics systems to debate the state of the art at the intersection of Learning and Analytics — including researchers, educators, instructional designers, data scientists, software developers, institutional leaders and governmental policy makers.

The conference is held in cooperation with ACM in association with ACM SIGCHI and SIGWEB, with the double-blind, peer-reviewed proceedings archived in the ACM Digital Library. The ACM Digital Library (DL) is the world's most comprehensive database of full-text articles and bibliographic literature covering computing and information technology. This renowned repository includes the complete collection of ACM publications plus an extended bibliographic database of core works in computing from scholarly publishers. This guarantees that the proceedings will be available to the widest possible audience of computing professionals. ACM has an enlightened copyright policy with liberal author rights: authors may self-archive their own papers as Open Access Preprints, as long as they carry the specified ACM statement.