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Quantitative Analysis of Informational Significance of SWEBOK Knowledge Areas in IEEE/ACM Curriculum Guidelines. / Юрков, Александр Васильевич; Халин, Владимир Георгиевич; Шилова, Ольга Николаевна; Abran, Alain.

System Analysis in Engineering and Control. ред. / Yuriy S. Vasiliev; Nataliya D. Pankratova; Violetta N. Volkova; Olga D. Shipunova; Nikolay N. Lyabakh. Springer Nature, 2022. стр. 561-573 (Lecture Notes in Networks and Systems; Том 442 LNNS).

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование

Harvard

Юрков, АВ, Халин, ВГ, Шилова, ОН & Abran, A 2022, Quantitative Analysis of Informational Significance of SWEBOK Knowledge Areas in IEEE/ACM Curriculum Guidelines. в YS Vasiliev, ND Pankratova, VN Volkova, OD Shipunova & NN Lyabakh (ред.), System Analysis in Engineering and Control. Lecture Notes in Networks and Systems, Том. 442 LNNS, Springer Nature, стр. 561-573, XXV Международная научная и учебно-практическая конференция "СИСТЕМНЫЙ АНАЛИЗ В ПРОЕКТИРОВАНИИ И УПРАВЛЕНИИ" , Санкт-Петербург, Российская Федерация, 13/10/21. https://doi.org/10.1007/978-3-030-98832-6_49

APA

Юрков, А. В., Халин, В. Г., Шилова, О. Н., & Abran, A. (2022). Quantitative Analysis of Informational Significance of SWEBOK Knowledge Areas in IEEE/ACM Curriculum Guidelines. в Y. S. Vasiliev, N. D. Pankratova, V. N. Volkova, O. D. Shipunova, & N. N. Lyabakh (Ред.), System Analysis in Engineering and Control (стр. 561-573). (Lecture Notes in Networks and Systems; Том 442 LNNS). Springer Nature. https://doi.org/10.1007/978-3-030-98832-6_49

Vancouver

Юрков АВ, Халин ВГ, Шилова ОН, Abran A. Quantitative Analysis of Informational Significance of SWEBOK Knowledge Areas in IEEE/ACM Curriculum Guidelines. в Vasiliev YS, Pankratova ND, Volkova VN, Shipunova OD, Lyabakh NN, Редакторы, System Analysis in Engineering and Control. Springer Nature. 2022. стр. 561-573. (Lecture Notes in Networks and Systems). https://doi.org/10.1007/978-3-030-98832-6_49

Author

Юрков, Александр Васильевич ; Халин, Владимир Георгиевич ; Шилова, Ольга Николаевна ; Abran, Alain. / Quantitative Analysis of Informational Significance of SWEBOK Knowledge Areas in IEEE/ACM Curriculum Guidelines. System Analysis in Engineering and Control. Редактор / Yuriy S. Vasiliev ; Nataliya D. Pankratova ; Violetta N. Volkova ; Olga D. Shipunova ; Nikolay N. Lyabakh. Springer Nature, 2022. стр. 561-573 (Lecture Notes in Networks and Systems).

BibTeX

@inproceedings{7a045152b4144b5c93d2a574e06a9694,
title = "Quantitative Analysis of Informational Significance of SWEBOK Knowledge Areas in IEEE/ACM Curriculum Guidelines",
abstract = "This paper reports on a quantitative analysis of the informational significance of SWEBOK knowledgeareas in the curriculum guidelines developed as IEEE/ACM recommendations for educational programs insoftware engineering. The analysis uses a representation of the hierarchical structure of educational contentin the form of an oriented bipartite hypergraph. The out-degrees of the vertices of the graph transitiveclosure are selected as the quantitative characteristics of the studied topics, reflecting their mutualinfluence within educational programs. A feature of the computational algorithm is the representation ofthe transitive closure matrix in the form of a sparse matrix of a block structure, the nonzero blocks ofwhich have a significantly lower dimension. The graph approach to quantitative analysis of SWEBOKknowledge areas, is a novel approach to curricular analytics: it is not limited to the software engineeringexample presented and may be useful for the development of an evidence-based educational policy.",
keywords = "Software engineering, Curriculum, Hypergraphs, Computations on matrices, Numerical algorithms, Computations on matrices, Curriculum, Hypergraphs, Numerical algorithms, Software engineering",
author = "Юрков, {Александр Васильевич} and Халин, {Владимир Георгиевич} and Шилова, {Ольга Николаевна} and Alain Abran",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; null ; Conference date: 13-10-2021 Through 14-10-2021",
year = "2022",
month = jan,
day = "1",
doi = "10.1007/978-3-030-98832-6_49",
language = "English",
isbn = " 978-3-030-98831-9",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer Nature",
pages = "561--573",
editor = "Vasiliev, {Yuriy S.} and Pankratova, {Nataliya D.} and Volkova, {Violetta N.} and Shipunova, {Olga D.} and Lyabakh, {Nikolay N.}",
booktitle = "System Analysis in Engineering and Control",
address = "Germany",

}

RIS

TY - GEN

T1 - Quantitative Analysis of Informational Significance of SWEBOK Knowledge Areas in IEEE/ACM Curriculum Guidelines

AU - Юрков, Александр Васильевич

AU - Халин, Владимир Георгиевич

AU - Шилова, Ольга Николаевна

AU - Abran, Alain

N1 - Conference code: 25

PY - 2022/1/1

Y1 - 2022/1/1

N2 - This paper reports on a quantitative analysis of the informational significance of SWEBOK knowledgeareas in the curriculum guidelines developed as IEEE/ACM recommendations for educational programs insoftware engineering. The analysis uses a representation of the hierarchical structure of educational contentin the form of an oriented bipartite hypergraph. The out-degrees of the vertices of the graph transitiveclosure are selected as the quantitative characteristics of the studied topics, reflecting their mutualinfluence within educational programs. A feature of the computational algorithm is the representation ofthe transitive closure matrix in the form of a sparse matrix of a block structure, the nonzero blocks ofwhich have a significantly lower dimension. The graph approach to quantitative analysis of SWEBOKknowledge areas, is a novel approach to curricular analytics: it is not limited to the software engineeringexample presented and may be useful for the development of an evidence-based educational policy.

AB - This paper reports on a quantitative analysis of the informational significance of SWEBOK knowledgeareas in the curriculum guidelines developed as IEEE/ACM recommendations for educational programs insoftware engineering. The analysis uses a representation of the hierarchical structure of educational contentin the form of an oriented bipartite hypergraph. The out-degrees of the vertices of the graph transitiveclosure are selected as the quantitative characteristics of the studied topics, reflecting their mutualinfluence within educational programs. A feature of the computational algorithm is the representation ofthe transitive closure matrix in the form of a sparse matrix of a block structure, the nonzero blocks ofwhich have a significantly lower dimension. The graph approach to quantitative analysis of SWEBOKknowledge areas, is a novel approach to curricular analytics: it is not limited to the software engineeringexample presented and may be useful for the development of an evidence-based educational policy.

KW - Software engineering

KW - Curriculum

KW - Hypergraphs

KW - Computations on matrices

KW - Numerical algorithms

KW - Computations on matrices

KW - Curriculum

KW - Hypergraphs

KW - Numerical algorithms

KW - Software engineering

UR - https://link.springer.com/book/9783030988333

UR - https://www.beck-shop.de/vasiliev-pankratova-volkova-shipunova-lyabakh-lecture-notes-networks-systems-442-system-analysis-engineering-control/product/33780697

UR - http://www.scopus.com/inward/record.url?scp=85128939187&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/1f85f378-8f65-39c4-be91-715d782a01b9/

U2 - 10.1007/978-3-030-98832-6_49

DO - 10.1007/978-3-030-98832-6_49

M3 - Conference contribution

SN - 978-3-030-98831-9

T3 - Lecture Notes in Networks and Systems

SP - 561

EP - 573

BT - System Analysis in Engineering and Control

A2 - Vasiliev, Yuriy S.

A2 - Pankratova, Nataliya D.

A2 - Volkova, Violetta N.

A2 - Shipunova, Olga D.

A2 - Lyabakh, Nikolay N.

PB - Springer Nature

Y2 - 13 October 2021 through 14 October 2021

ER -

ID: 93322782