Data-driven analyses of electronic text books

Ahcène Boubekki; Ulf Kröhne; Frank Goldhammer; Waltraud Schreiber; Ulf Brefeld

doi:10.1007/978-3-319-41706-6_20

Data-driven analyses of electronic text books

Ahcène Boubekki
, Ulf Kröhne
, Frank Goldhammer
, Waltraud Schreiber
, Ulf Brefeld

Professur für Wirtschaftsinformatik, insbesondere Machine Learning

Publikation: Beiträge in Sammelwerken › Aufsätze in Sammelwerken › Forschung

2 Zitate (Scopus)

Abstract

We present data-driven log file analyses of an electronic text book for history called the mBook to support teachers in preparing lessons for their students. We represent user sessions as contextualised Markov processes of user sessions and propose a probabilistic clustering using expectation maximisation to detect groups of similar (i) sessions and (ii) users. We compare our approach to a standard K-means clustering and report on findings that may have a direct impact on preparing and revising lessons.

Originalsprache	Englisch
Titel	Solving large scale learning tasks : Challenges and algorithms : essays dedicated to Katharina Morik on the occasion of her 60th birthday
Redakteure/-innen	Stefan Michaelis, Nico Piatkowski, Marco Stolpe
Seitenumfang	15
Erscheinungsort	Cham
Herausgeber (Verlag)	Springer International Publishing
Erscheinungsdatum	2016
Seiten	362-376
ISBN (Print)	978-3-319-41705-9
ISBN (elektronisch)	978-3-319-41706-6
DOIs	https://doi.org/10.1007/978-3-319-41706-6_20
Publikationsstatus	Erschienen - 2016

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Wirtschaftsinformatik

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10.1007/978-3-319-41706-6_20

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Boubekki, A., Kröhne, U., Goldhammer, F., Schreiber, W., & Brefeld, U. (2016). Data-driven analyses of electronic text books. in S. Michaelis, N. Piatkowski, & M. Stolpe (Hrsg.), Solving large scale learning tasks: Challenges and algorithms : essays dedicated to Katharina Morik on the occasion of her 60th birthday (S. 362-376). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 9580). Springer International Publishing. https://doi.org/10.1007/978-3-319-41706-6_20

Boubekki, Ahcène ; Kröhne, Ulf ; Goldhammer, Frank et al. / Data-driven analyses of electronic text books. Solving large scale learning tasks: Challenges and algorithms : essays dedicated to Katharina Morik on the occasion of her 60th birthday. Hrsg. / Stefan Michaelis ; Nico Piatkowski ; Marco Stolpe. Cham : Springer International Publishing, 2016. S. 362-376 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "We present data-driven log file analyses of an electronic text book for history called the mBook to support teachers in preparing lessons for their students. We represent user sessions as contextualised Markov processes of user sessions and propose a probabilistic clustering using expectation maximisation to detect groups of similar (i) sessions and (ii) users. We compare our approach to a standard K-means clustering and report on findings that may have a direct impact on preparing and revising lessons.",

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author = "Ahc{\`e}ne Boubekki and Ulf Kr{\"o}hne and Frank Goldhammer and Waltraud Schreiber and Ulf Brefeld",

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Boubekki, A, Kröhne, U, Goldhammer, F, Schreiber, W & Brefeld, U 2016, Data-driven analyses of electronic text books. in S Michaelis, N Piatkowski & M Stolpe (Hrsg.), Solving large scale learning tasks: Challenges and algorithms : essays dedicated to Katharina Morik on the occasion of her 60th birthday. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bd. 9580, Springer International Publishing, Cham, S. 362-376. https://doi.org/10.1007/978-3-319-41706-6_20

Data-driven analyses of electronic text books. / Boubekki, Ahcène; Kröhne, Ulf; Goldhammer, Frank et al.
Solving large scale learning tasks: Challenges and algorithms : essays dedicated to Katharina Morik on the occasion of her 60th birthday. Hrsg. / Stefan Michaelis; Nico Piatkowski; Marco Stolpe. Cham: Springer International Publishing, 2016. S. 362-376 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 9580).

Publikation: Beiträge in Sammelwerken › Aufsätze in Sammelwerken › Forschung

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T1 - Data-driven analyses of electronic text books

AU - Boubekki, Ahcène

AU - Kröhne, Ulf

AU - Goldhammer, Frank

AU - Schreiber, Waltraud

AU - Brefeld, Ulf

PY - 2016

Y1 - 2016

N2 - We present data-driven log file analyses of an electronic text book for history called the mBook to support teachers in preparing lessons for their students. We represent user sessions as contextualised Markov processes of user sessions and propose a probabilistic clustering using expectation maximisation to detect groups of similar (i) sessions and (ii) users. We compare our approach to a standard K-means clustering and report on findings that may have a direct impact on preparing and revising lessons.

AB - We present data-driven log file analyses of an electronic text book for history called the mBook to support teachers in preparing lessons for their students. We represent user sessions as contextualised Markov processes of user sessions and propose a probabilistic clustering using expectation maximisation to detect groups of similar (i) sessions and (ii) users. We compare our approach to a standard K-means clustering and report on findings that may have a direct impact on preparing and revising lessons.

KW - Business informatics

UR - https://www.scopus.com/pages/publications/84978877380

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DO - 10.1007/978-3-319-41706-6_20

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SN - 978-3-319-41705-9

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Solving large scale learning tasks

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Boubekki A, Kröhne U, Goldhammer F, Schreiber W, Brefeld U. Data-driven analyses of electronic text books. in Michaelis S, Piatkowski N, Stolpe M, Hrsg., Solving large scale learning tasks: Challenges and algorithms : essays dedicated to Katharina Morik on the occasion of her 60th birthday. Cham: Springer International Publishing. 2016. S. 362-376. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-41706-6_20

Data-driven analyses of electronic text books

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