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The learning analytics & knowledge (LAK) data challenge 2014

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Davide TaibiAuthors Info & Claims

LAK '14: Proceedings of the Fourth International Conference on Learning Analytics And Knowledge

Pages 289 - 290

https://doi.org/10.1145/2567574.2567630

Published: 24 March 2014 Publication History

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Abstract

The LAK Data Challenge 2014 continues the research efforts of the second edition by stimulating research on the evolving fields Learning Analytics (LA) and Educational Data Mining (EDM). Building on a series of activities of the LinkedUp project, the challenge aims to generate new insights and analysis on the LA & EDM disciplines and is supported through the LAK Dataset - a unique corpus of LA & EDM literature, exposed in structured and machine-readable formats.

References

[1]

Verbert, K., Manouselis, N., Drachsler, H., & Duval, E. (2012). Dataset-Driven Research to Support Learning and Knowledge Analytics. Educational Technology & Society, 15 (3), 133--148.

Google Scholar

[2]

T. Heath and C. Bizer (2011). Linked Data: Evolving the Web into a Global Data Space. Synthesis Lectures on the Semantic Web: Theory and Technology. Morgan & Claypool.

Digital Library

Google Scholar

[3]

Taibi, D. and Dietze, S. (2013). Fostering Analytics on Learning Analytics Research: the LAK Dataset. CEUR WS Proceedings Vol. 974, Proceedings of the LAK Data Challenge.

Google Scholar

[4]

d'Aquin, M., Adamou, A., Dietze, S., Assessing the Educational Linked Data Landscape, ACM Web Science 2013 (WebSci2013), Paris, France, May 2013.

Digital Library

Google Scholar

[5]

d'Aquin, M., Dietze, S., Drachsler, H., Taibi, D. (2014). Using linked data in learning analytics. eLearning Papers, Nr. 36, ISSN: 1887--1542.

Google Scholar

[6]

Nunes, B. P., Fetahu, B., Dietze, S., Casanova, M. A., Cite4Me: A Semantic Search and Retrieval Web Application for Scientific Publications, 12th International Semantic Web Conference (ISWC2013), Sydney, Australia, (2013).

Google Scholar

[7]

Maturana, R. A., Alvarado, M. E. López-Sola, S., Ibáñez, M. J., & Ruiz Elósegui, L., (2013). Linked Data based applications for Learning Analytics Research. CEUR WS Proceedings of the LAK Data Challenge, Vol. 974.

Google Scholar

[8]

Zouaq, Amal, Srećko Joksimović, and Dragan Gašević. (2013). Ontology Learning to Analyze Research Trends in Learning Analytics Publications. CEUR WS Proceedings of the LAK Data Challenge Vol. 974, accessible under http://lak.linkededucation.org.

Google Scholar

Cited By

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Kitto KManly CFerguson RPoquet OHilliger IKhosravi HRienties BDawson S(2023)Towards more replicable content analysis for learning analyticsLAK23: 13th International Learning Analytics and Knowledge Conference10.1145/3576050.3576096(303-314)Online publication date: 13-Mar-2023
https://dl.acm.org/doi/10.1145/3576050.3576096
Corlatescu DRuseti SToma IDascalu MKizilcec RDavis KOchoa X(2022)Where are the Large N Studies in Education?Proceedings of the Ninth ACM Conference on Learning @ Scale10.1145/3491140.3528315(461-465)Online publication date: 1-Jun-2022
https://dl.acm.org/doi/10.1145/3491140.3528315
Sahin MIfenthaler D(2021)Visualization and Dashboards: Challenges and Future DirectionsVisualizations and Dashboards for Learning Analytics10.1007/978-3-030-81222-5_27(585-597)Online publication date: 17-Dec-2021
https://doi.org/10.1007/978-3-030-81222-5_27
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The learning analytics & knowledge (LAK) data challenge 2014

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Information & Contributors

Information

Published In

LAK '14: Proceedings of the Fourth International Conference on Learning Analytics And Knowledge

March 2014

301 pages

ISBN:9781450326643

DOI:10.1145/2567574

Conference Chairs:
Mattew Pistilli
Purdue University, IN
,
James Willis
Purdue University, IN
,
Drew Koch
John N. Gardner Institute for Excellence in Undergraduate Education, NC
,
Kimberly Arnold
University of Wisconsin-Madison, WI
,
Program Chairs:
Stephanie Teasley
University of Michigan, MI
,
Abelardo Pardo
The University of Sydney, Australia

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 March 2014

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Research-article

Conference

LAK '14

Sponsor:

JNGI
University of Wisc-Madison
SoLAR
Purdue University

LAK '14: Learning Analytics and Knowledge Conference 2014

March 24 - 28, 2014

Indiana, Indianapolis, USA

Acceptance Rates

LAK '14 Paper Acceptance Rate 13 of 44 submissions, 30%;

Overall Acceptance Rate 236 of 782 submissions, 30%

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Citations

Cited By

View all

Kitto KManly CFerguson RPoquet OHilliger IKhosravi HRienties BDawson S(2023)Towards more replicable content analysis for learning analyticsLAK23: 13th International Learning Analytics and Knowledge Conference10.1145/3576050.3576096(303-314)Online publication date: 13-Mar-2023
https://dl.acm.org/doi/10.1145/3576050.3576096
Corlatescu DRuseti SToma IDascalu MKizilcec RDavis KOchoa X(2022)Where are the Large N Studies in Education?Proceedings of the Ninth ACM Conference on Learning @ Scale10.1145/3491140.3528315(461-465)Online publication date: 1-Jun-2022
https://dl.acm.org/doi/10.1145/3491140.3528315
Sahin MIfenthaler D(2021)Visualization and Dashboards: Challenges and Future DirectionsVisualizations and Dashboards for Learning Analytics10.1007/978-3-030-81222-5_27(585-597)Online publication date: 17-Dec-2021
https://doi.org/10.1007/978-3-030-81222-5_27
Sahin MIfenthaler D(2021)Visualizations and Dashboards for Learning Analytics: A Systematic Literature ReviewVisualizations and Dashboards for Learning Analytics10.1007/978-3-030-81222-5_1(3-22)Online publication date: 17-Dec-2021
https://doi.org/10.1007/978-3-030-81222-5_1
Feretzakis GKalles DVerykios V(2020)Knowledge Hiding in Decision Trees for Learning Analytics ApplicationsAdvances in Core Computer Science-Based Technologies10.1007/978-3-030-41196-1_3(37-54)Online publication date: 19-Jun-2020
https://doi.org/10.1007/978-3-030-41196-1_3
Syed TPalade VIqbal RNair S(2018)Building a Dataset for Personalized Learning Recommendation System2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI)10.1109/ICACCI.2018.8554438(2080-2086)Online publication date: Sep-2018
https://doi.org/10.1109/ICACCI.2018.8554438
Gursoy MInan ANergiz MSaygin Y(2017)Privacy-Preserving Learning AnalyticsIEEE Transactions on Learning Technologies10.1109/TLT.2016.260774710:1(68-81)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1109/TLT.2016.2607747
Ahmed EImran MGuizani MRayes ALloret JHan GGuibene W(2017)Enabling Mobile and Wireless Technologies for Smart CitiesIEEE Communications Magazine10.1109/MCOM.2017.787685055:3(12-13)Online publication date: 1-Mar-2017
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Duval EVerbert KKlerkx JWolpers MPardo AGovaerts SGillet DOchoa XParra DBaron JLynch GMaziarz NBlikstein PMerceron ASiemens G(2015)VISLAProceedings of the Fifth International Conference on Learning Analytics And Knowledge10.1145/2723576.2723643(394-395)Online publication date: 16-Mar-2015
https://dl.acm.org/doi/10.1145/2723576.2723643
Fernández GMariño O(2015)Visualization Improvement in Learning Analytics Using Semantic EnrichmentState-of-the-Art and Future Directions of Smart Learning10.1007/978-981-287-868-7_58(493-503)Online publication date: 27-Oct-2015
https://doi.org/10.1007/978-981-287-868-7_58

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