Impact of Time Granularity on Histories Binary Correlation Analysis

Paolo Mengoni; Alfredo Milani; Yuanxi Li

doi:10.1007/978-3-030-24296-1_27

Impact of Time Granularity on Histories Binary Correlation Analysis

Paolo Mengoni^*
, Alfredo Milani
, Yuanxi Li

^*Corresponding author for this work

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

1 Citation (Scopus)

Abstract

Activities taken by students within a Virtual Learning Environment (VLE) can be represented by using binary student histories. Virtual Learning Environments allow educators to track most of the students’ individual activities that can be used to elicit the students social communities. In this work, we analyse the impact of granularity in the social community elicitation. Granularity can be seen as the resolution of the student history vectors where each time slot is directly dependent from this value. Indeed, the higher is the resolution of the students histories the more precise is the representation of their actions within the VLE. When comparing the histories using various similarity measures to elicit the students’ groups, we find the optimal granularity and demonstrate that there is a resolution limit where the similarity measures will not help to distinguish the social communities.

Original language	English
Title of host publication	Computational Science and Its Applications – ICCSA 2019
Subtitle of host publication	19th International Conference, Saint Petersburg, Russia, July 1–4, 2019, Proceedings, Part II
Editors	Sanjay Misra, Osvaldo Gervasi, Beniamino Murgante, Elena Stankova, Vladimir Korkhov, Carmelo Torre, Ana Maria A.C. Rocha, David Taniar, Bernady O. Apduhan, Eufemia Tarantino
Publisher	Springer Cham
Pages	323-335
Number of pages	13
ISBN (Electronic)	9783030242961
ISBN (Print)	9783030242954
DOIs	https://doi.org/10.1007/978-3-030-24296-1_27
Publication status	Published - 29 Jun 2019
Event	19th International Conference on Computational Science and Its Applications, ICCSA 2019 - Saint Petersburg, Russian Federation Duration: 1 Jul 2019 → 4 Jul 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11620 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	19th International Conference on Computational Science and Its Applications, ICCSA 2019
Country/Territory	Russian Federation
City	Saint Petersburg
Period	1/07/19 → 4/07/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 4 Quality Education

User-Defined Keywords

Cluster analysis
Community elicitation
Data analysis
Learning analytics

Access to Document

10.1007/978-3-030-24296-1_27

Cite this

Mengoni, P., Milani, A., & Li, Y. (2019). Impact of Time Granularity on Histories Binary Correlation Analysis. In S. Misra, O. Gervasi, B. Murgante, E. Stankova, V. Korkhov, C. Torre, A. M. A. C. Rocha, D. Taniar, B. O. Apduhan, & E. Tarantino (Eds.), Computational Science and Its Applications – ICCSA 2019: 19th International Conference, Saint Petersburg, Russia, July 1–4, 2019, Proceedings, Part II (pp. 323-335). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11620 LNCS). Springer Cham. https://doi.org/10.1007/978-3-030-24296-1_27

Mengoni, Paolo ; Milani, Alfredo ; Li, Yuanxi. / Impact of Time Granularity on Histories Binary Correlation Analysis. Computational Science and Its Applications – ICCSA 2019: 19th International Conference, Saint Petersburg, Russia, July 1–4, 2019, Proceedings, Part II. editor / Sanjay Misra ; Osvaldo Gervasi ; Beniamino Murgante ; Elena Stankova ; Vladimir Korkhov ; Carmelo Torre ; Ana Maria A.C. Rocha ; David Taniar ; Bernady O. Apduhan ; Eufemia Tarantino. Springer Cham, 2019. pp. 323-335 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{33bb62c6e4fc4ab18c296d1fc0143a2a,

title = "Impact of Time Granularity on Histories Binary Correlation Analysis",

abstract = "Activities taken by students within a Virtual Learning Environment (VLE) can be represented by using binary student histories. Virtual Learning Environments allow educators to track most of the students{\textquoteright} individual activities that can be used to elicit the students social communities. In this work, we analyse the impact of granularity in the social community elicitation. Granularity can be seen as the resolution of the student history vectors where each time slot is directly dependent from this value. Indeed, the higher is the resolution of the students histories the more precise is the representation of their actions within the VLE. When comparing the histories using various similarity measures to elicit the students{\textquoteright} groups, we find the optimal granularity and demonstrate that there is a resolution limit where the similarity measures will not help to distinguish the social communities.",

keywords = "Cluster analysis, Community elicitation, Data analysis, Learning analytics",

author = "Paolo Mengoni and Alfredo Milani and Yuanxi Li",

note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 19th International Conference on Computational Science and Its Applications, ICCSA 2019 ; Conference date: 01-07-2019 Through 04-07-2019",

year = "2019",

month = jun,

day = "29",

doi = "10.1007/978-3-030-24296-1\_27",

language = "English",

isbn = "9783030242954",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Cham",

pages = "323--335",

editor = "Sanjay Misra and Osvaldo Gervasi and Beniamino Murgante and Elena Stankova and Vladimir Korkhov and Carmelo Torre and Rocha, \{Ana Maria A.C.\} and David Taniar and Apduhan, \{Bernady O.\} and Eufemia Tarantino",

booktitle = "Computational Science and Its Applications – ICCSA 2019",

}

Mengoni, P, Milani, A & Li, Y 2019, Impact of Time Granularity on Histories Binary Correlation Analysis. in S Misra, O Gervasi, B Murgante, E Stankova, V Korkhov, C Torre, AMAC Rocha, D Taniar, BO Apduhan & E Tarantino (eds), Computational Science and Its Applications – ICCSA 2019: 19th International Conference, Saint Petersburg, Russia, July 1–4, 2019, Proceedings, Part II. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11620 LNCS, Springer Cham, pp. 323-335, 19th International Conference on Computational Science and Its Applications, ICCSA 2019, Saint Petersburg, Russian Federation, 1/07/19. https://doi.org/10.1007/978-3-030-24296-1_27

Impact of Time Granularity on Histories Binary Correlation Analysis. / Mengoni, Paolo; Milani, Alfredo; Li, Yuanxi.
Computational Science and Its Applications – ICCSA 2019: 19th International Conference, Saint Petersburg, Russia, July 1–4, 2019, Proceedings, Part II. ed. / Sanjay Misra; Osvaldo Gervasi; Beniamino Murgante; Elena Stankova; Vladimir Korkhov; Carmelo Torre; Ana Maria A.C. Rocha; David Taniar; Bernady O. Apduhan; Eufemia Tarantino. Springer Cham, 2019. p. 323-335 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11620 LNCS).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - Impact of Time Granularity on Histories Binary Correlation Analysis

AU - Mengoni, Paolo

AU - Milani, Alfredo

AU - Li, Yuanxi

PY - 2019/6/29

Y1 - 2019/6/29

N2 - Activities taken by students within a Virtual Learning Environment (VLE) can be represented by using binary student histories. Virtual Learning Environments allow educators to track most of the students’ individual activities that can be used to elicit the students social communities. In this work, we analyse the impact of granularity in the social community elicitation. Granularity can be seen as the resolution of the student history vectors where each time slot is directly dependent from this value. Indeed, the higher is the resolution of the students histories the more precise is the representation of their actions within the VLE. When comparing the histories using various similarity measures to elicit the students’ groups, we find the optimal granularity and demonstrate that there is a resolution limit where the similarity measures will not help to distinguish the social communities.

AB - Activities taken by students within a Virtual Learning Environment (VLE) can be represented by using binary student histories. Virtual Learning Environments allow educators to track most of the students’ individual activities that can be used to elicit the students social communities. In this work, we analyse the impact of granularity in the social community elicitation. Granularity can be seen as the resolution of the student history vectors where each time slot is directly dependent from this value. Indeed, the higher is the resolution of the students histories the more precise is the representation of their actions within the VLE. When comparing the histories using various similarity measures to elicit the students’ groups, we find the optimal granularity and demonstrate that there is a resolution limit where the similarity measures will not help to distinguish the social communities.

KW - Cluster analysis

KW - Community elicitation

KW - Data analysis

KW - Learning analytics

UR - https://www.scopus.com/pages/publications/85069211286

U2 - 10.1007/978-3-030-24296-1_27

DO - 10.1007/978-3-030-24296-1_27

M3 - Conference proceeding

AN - SCOPUS:85069211286

SN - 9783030242954

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

SP - 323

EP - 335

BT - Computational Science and Its Applications – ICCSA 2019

A2 - Misra, Sanjay

A2 - Gervasi, Osvaldo

A2 - Murgante, Beniamino

A2 - Stankova, Elena

A2 - Korkhov, Vladimir

A2 - Torre, Carmelo

A2 - Rocha, Ana Maria A.C.

A2 - Taniar, David

A2 - Apduhan, Bernady O.

A2 - Tarantino, Eufemia

PB - Springer Cham

T2 - 19th International Conference on Computational Science and Its Applications, ICCSA 2019

Y2 - 1 July 2019 through 4 July 2019

ER -

Mengoni P, Milani A, Li Y. Impact of Time Granularity on Histories Binary Correlation Analysis. In Misra S, Gervasi O, Murgante B, Stankova E, Korkhov V, Torre C, Rocha AMAC, Taniar D, Apduhan BO, Tarantino E, editors, Computational Science and Its Applications – ICCSA 2019: 19th International Conference, Saint Petersburg, Russia, July 1–4, 2019, Proceedings, Part II. Springer Cham. 2019. p. 323-335. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-24296-1_27

Impact of Time Granularity on Histories Binary Correlation Analysis

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