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short-paper

DOP8: merging both data and analysis operators life cycles for technology enhanced learning

Authors:

Nadine Mandran,

Michael Ortega,

Denis BouhineauAuthors Info & Claims

LAK '15: Proceedings of the Fifth International Conference on Learning Analytics And Knowledge

Pages 213 - 217

https://doi.org/10.1145/2723576.2723580

Published: 16 March 2015 Publication History

Abstract

This paper presents DOP8: a Data Mining Iterative Cycle that improves the classical data life cycle. While the latter only combines the data production and data analysis phases, DOP8 also integrates the analysis operators life cycle. In this cycle, data life cycle and operators life cycle processing meet in the data analysis step. This paper also presents a reification of DOP8 in a new computing platform: UnderTracks. The latter provides a flexibility on storing and sharing data, operators and analysis processes. Undertracks is compared with three types of platform 'Storage platform', 'Analysis platform' and 'Storage and Analysis platform'. Several real TEL analysis scenarios are present into the platform, (1) to test Undertracks flexibility on storing data and operators and (2) to test Undertracks flexibility on designing analysis processes.

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Cited By

Su HZhang JTang S(2024)Artificial Intelligence Innovations in Visual Arts and Design EducationIntegrating Technology in Problem-Solving Educational Practices10.4018/979-8-3693-6745-2.ch010(219-240)Online publication date: 25-Oct-2024
https://doi.org/10.4018/979-8-3693-6745-2.ch010
Lebis ALefevre MLuengo VGuin NPardo ABartimote-Aufflick KLynch GShum SFerguson RMerceron AOchoa X(2018)Capitalisation of analysis processesProceedings of the 8th International Conference on Learning Analytics and Knowledge10.1145/3170358.3170408(245-254)Online publication date: 7-Mar-2018
https://dl.acm.org/doi/10.1145/3170358.3170408
Bey ABouhineau DChampagnat R(2018)Human Scoring Versus Automatic Scoring of Computer Programs: Does Algo+ Score as well as Instructors? An Experimental Study2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT)10.1109/ICALT.2018.00089(355-357)Online publication date: Jul-2018
https://doi.org/10.1109/ICALT.2018.00089
Show More Cited By

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DOP8: merging both data and analysis operators life cycles for technology enhanced learning

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Published In

cover image ACM Other conferences

LAK '15: Proceedings of the Fifth International Conference on Learning Analytics And Knowledge

March 2015

448 pages

ISBN:9781450334174

DOI:10.1145/2723576

Conference Chairs:
Josh Baron
Marist College
,
Grace Lynch
SoLAR
,
Nicole Maziarz
Marist College
,
Program Chairs:
Paulo Blikstein
Stanford University
,
Agathe Merceron
Beuth University of Applied Sciences Berlin
,
George Siemens
University of Texas at Arlington

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 March 2015

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HUBBLE ANR
MOCA ANR

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LAK '15

LAK '15: the 5th International Learning Analytics and Knowledge Conference

March 16 - 20, 2015

New York, Poughkeepsie

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LAK '15 Paper Acceptance Rate 20 of 74 submissions, 27%;

Overall Acceptance Rate 236 of 782 submissions, 30%

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Cited By

Su HZhang JTang S(2024)Artificial Intelligence Innovations in Visual Arts and Design EducationIntegrating Technology in Problem-Solving Educational Practices10.4018/979-8-3693-6745-2.ch010(219-240)Online publication date: 25-Oct-2024
https://doi.org/10.4018/979-8-3693-6745-2.ch010
Lebis ALefevre MLuengo VGuin NPardo ABartimote-Aufflick KLynch GShum SFerguson RMerceron AOchoa X(2018)Capitalisation of analysis processesProceedings of the 8th International Conference on Learning Analytics and Knowledge10.1145/3170358.3170408(245-254)Online publication date: 7-Mar-2018
https://dl.acm.org/doi/10.1145/3170358.3170408
Bey ABouhineau DChampagnat R(2018)Human Scoring Versus Automatic Scoring of Computer Programs: Does Algo+ Score as well as Instructors? An Experimental Study2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT)10.1109/ICALT.2018.00089(355-357)Online publication date: Jul-2018
https://doi.org/10.1109/ICALT.2018.00089
Mandran N(2018)BibliographyTraceable Human Experiment Design Research10.1002/9781119453635.biblio(235-246)Online publication date: 16-Feb-2018
https://doi.org/10.1002/9781119453635.biblio
Vermeulen MGuigon GMandran NLabat J(2017)Teachers at the Heart of the Learning Games Design: The DISC Model2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT)10.1109/ICALT.2017.41(145-149)Online publication date: Jul-2017
https://doi.org/10.1109/ICALT.2017.41
Lebis ALefevre MLuengo VGuin N(2016)Towards a Capitalization of Processes Analyzing Learning Interaction TracesAdaptive and Adaptable Learning10.1007/978-3-319-45153-4_33(397-403)Online publication date: 7-Sep-2016
https://doi.org/10.1007/978-3-319-45153-4_33
Vermeulen MMandran NLabat J(2016)Chronicle of a Scenario Graph: From Expected to Observed Learning PathAdaptive and Adaptable Learning10.1007/978-3-319-45153-4_24(321-330)Online publication date: 7-Sep-2016
https://doi.org/10.1007/978-3-319-45153-4_24

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