Agile and cyclic learning in teaching parallel and distributed computing

published in EASEAI 2020: Proceedings of the 2^nd ACM SIGSOFT International Workshop on Education through Advanced Software Engineering and Artificial Intelligence, November 2020, pp. 27-33, DOI: 10.1145/3412453.3423198.

Cite as

Virginia Niculescu, Adrian Sterca, and Darius Bufnea. 2020. Agile and cyclic learning in teaching parallel and distributed computing. In Proceedings of the 2nd ACM SIGSOFT International Workshop on Education through Advanced Software Engineering and Artificial Intelligence (EASEAI 2020). Association for Computing Machinery, New York, NY, USA, 27–33. DOI:https://doi.org/10.1145/3412453.3423198

Virginia Niculescu, Adrian Sterca, and Darius Bufnea. 2020. Agile and cyclic learning in teaching parallel and distributed computing. In Proceedings of the 2nd ACM SIGSOFT International Workshop on Education through Advanced Software Engineering and Artificial Intelligence (EASEAI 2020). Association for Computing Machinery, New York, NY, USA, 27–33. DOI:https://doi.org/10.1145/3412453.3423198

Full paper (preprint version)

Agile and cyclic learning in teaching parallel and distributed computing

Authors

Virginia Niculescu, Adrian Sterca, Darius Bufnea
Department of Computer Science, Faculty of Mathematics and Computer Science, Babeș-Bolyai University of Cluj-Napoca, Romania

Abstract

Agile and cyclic learning are methodologies that have been recently proposed to be used in teaching Computer Science. This paper investigates their usage for the undergraduate studies on parallel and distributed computing (PDC). The aim of this analysis is to evaluate their effectiveness, and also to evaluate to which extent we have to go with the knowledge related to PDC at the undergraduate level. Also, we intended to find out the pace in which agile and cyclic learning enforces the best knowledge transfer of PDC concepts. The analysis takes into consideration several courses spread on the entire curricula, students auto-evaluation based on questionnaires, and grade results. The analysis emphasizes the fact that the tendency is to introduce more and more information and this is facilitated by an agile approach, but in the same time this should be moderated if the final goal is to assure also a good and deep understanding of associated knowledge.

Key words

agile methodologies, cyclic learning, knowledge levels, undergraduate studies, parallel and distributed computing

BibTeX bib file

agile-2020.bib

@inproceedings{agile2020,
author = {Niculescu, Virginia and Sterca, Adrian and Bufnea, Darius},
title = {Agile and Cyclic Learning in Teaching Parallel and Distributed Computing},
year = {2020},
isbn = {9781450381024},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3412453.3423198},
doi = {10.1145/3412453.3423198},
abstract = {Agile and cyclic learning are methodologies that have been recently proposed to be used in teaching Computer Science. This paper investigates their usage for the undergraduate studies on parallel and distributed computing (PDC). The aim of this analysis is to evaluate their effectiveness, and also to evaluate to which extent we have to go with the knowledge related to PDC at the undergraduate level. Also, we intended to find out the pace in which agile and cyclic learning enforces the best knowledge transfer of PDC concepts. The analysis takes into consideration several courses spread on the entire curricula, students auto-evaluation based on questionnaires, and grade results. The analysis emphasizes the fact that the tendency is to introduce more and more information and this is facilitated by an agile approach, but in the same time this should be moderated if the final goal is to assure also a good and deep understanding of associated knowledge.},
booktitle = {Proceedings of the 2nd ACM SIGSOFT International Workshop on Education through Advanced Software Engineering and Artificial Intelligence},
pages = {27–33},
numpages = {7},
keywords = {agile methodologies, parallel and distributed computing, cyclic learning, knowledge levels, undergraduate studies},
location = {Virtual, USA},
series = {EASEAI 2020}
}

@inproceedings{agile2020,

author = {Niculescu, Virginia and Sterca, Adrian and Bufnea, Darius},

title = {Agile and Cyclic Learning in Teaching Parallel and Distributed Computing},

year = {2020},

isbn = {9781450381024},

publisher = {Association for Computing Machinery},

address = {New York, NY, USA},

url = {https://doi.org/10.1145/3412453.3423198},

doi = {10.1145/3412453.3423198},

abstract = {Agile and cyclic learning are methodologies that have been recently proposed to be used in teaching Computer Science. This paper investigates their usage for the undergraduate studies on parallel and distributed computing (PDC). The aim of this analysis is to evaluate their effectiveness, and also to evaluate to which extent we have to go with the knowledge related to PDC at the undergraduate level. Also, we intended to find out the pace in which agile and cyclic learning enforces the best knowledge transfer of PDC concepts. The analysis takes into consideration several courses spread on the entire curricula, students auto-evaluation based on questionnaires, and grade results. The analysis emphasizes the fact that the tendency is to introduce more and more information and this is facilitated by an agile approach, but in the same time this should be moderated if the final goal is to assure also a good and deep understanding of associated knowledge.},

booktitle = {Proceedings of the 2nd ACM SIGSOFT International Workshop on Education through Advanced Software Engineering and Artificial Intelligence},

pages = {27–33},

numpages = {7},

keywords = {agile methodologies, parallel and distributed computing, cyclic learning, knowledge levels, undergraduate studies},

location = {Virtual, USA},

series = {EASEAI 2020}

}

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