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

Professorship of Information Systems, in particular Machine Learning

Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research

2 Citations (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.

Original language	English
Title of host publication	Solving large scale learning tasks : Challenges and algorithms : essays dedicated to Katharina Morik on the occasion of her 60th birthday
Editors	Stefan Michaelis, Nico Piatkowski, Marco Stolpe
Number of pages	15
Place of Publication	Cham
Publisher	Springer International Publishing
Publication date	2016
Pages	362-376
ISBN (Print)	978-3-319-41705-9
ISBN (Electronic)	978-3-319-41706-6
DOIs	https://doi.org/10.1007/978-3-319-41706-6_20
Publication status	Published - 2016

Research areas and keywords

Business informatics

Access to Document

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

Cite this

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 (Eds.), Solving large scale learning tasks: Challenges and algorithms : essays dedicated to Katharina Morik on the occasion of her 60th birthday (pp. 362-376). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 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. editor / Stefan Michaelis ; Nico Piatkowski ; Marco Stolpe. Cham : Springer International Publishing, 2016. pp. 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 (eds), 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), vol. 9580, Springer International Publishing, Cham, pp. 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. ed. / Stefan Michaelis; Nico Piatkowski; Marco Stolpe. Cham: Springer International Publishing, 2016. p. 362-376 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9580).

Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research

TY - CHAP

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

U2 - 10.1007/978-3-319-41706-6_20

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

M3 - Contributions to collected editions/anthologies

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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EP - 376

BT - Solving large scale learning tasks

A2 - Michaelis, Stefan

A2 - Piatkowski, Nico

A2 - Stolpe, Marco

PB - Springer International Publishing

CY - Cham

ER -

Boubekki A, Kröhne U, Goldhammer F, Schreiber W, Brefeld U. Data-driven analyses of electronic text books. In Michaelis S, Piatkowski N, Stolpe M, editors, 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. p. 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

Abstract

Research areas and keywords

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