Designing Personalized Learning Environments throughMonitoring and Guiding User Interactions with Code andNatural Language

Mircea Lungu

doi:10.1145/3340435.3342724

Designing Personalized Learning Environments throughMonitoring and Guiding User Interactions with Code andNatural Language

Software Engineering

Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

Abstract

Learning the vocabulary of a new language and a new programming API are similar in multiple ways. In this paper we evaluate several of the similarities and show that based on them we can design systems that can guide the learner towards improving their knowledge without an external tutor or preset curriculum. Instead, the class of systems we propose here are based on automated approaches of building maps of knowledge of the domain by mining repositories. By intersecting this knowledge with models of learner knowledge built by observing past learner interactions with artifacts of the domain we can generate highly personalized learning guidance.

Original language	English
Title of host publication	Proceedings of the 1st ACM SIGSOFT International Workshop on Education through Advanced Software Engineering and Artificial Intelligence
Publisher	Association for Computing Machinery
Publication date	2019
Pages	5-8
ISBN (Print)	978-1-4503-6852-0
DOIs	https://doi.org/10.1145/3340435.3342724
Publication status	Published - 2019
Event	International Workshop on Education through Advanced Software Engineering and Artificial Intelligence - Duration: 26 Aug 2019 → 26 Aug 2019 https://easeai.github.io/

Workshop

Workshop	International Workshop on Education through Advanced Software Engineering and Artificial Intelligence
Period	26/08/2019 → 26/08/2019
Internet address	https://easeai.github.io/

Keywords

software engineering
education
Software Architecture
ecosystems
artificial intelligence

Access to Document

10.1145/3340435.3342724

EASEAI___Designing_Personalized_Learning_Environments (6)Submitted manuscript, 534 KB

Cite this

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title = "Designing Personalized Learning Environments throughMonitoring and Guiding User Interactions with Code andNatural Language",

abstract = "Learning the vocabulary of a new language and a new programming API are similar in multiple ways. In this paper we evaluate several of the similarities and show that based on them we can design systems that can guide the learner towards improving their knowledge without an external tutor or preset curriculum. Instead, the class of systems we propose here are based on automated approaches of building maps of knowledge of the domain by mining repositories. By intersecting this knowledge with models of learner knowledge built by observing past learner interactions with artifacts of the domain we can generate highly personalized learning guidance.",

keywords = "software engineering, education, Software Architecture, ecosystems, artificial intelligence, software engineering, education, Software Architecture, ecosystems, artificial intelligence",

author = "Mircea Lungu",

year = "2019",

doi = "10.1145/3340435.3342724",

language = "English",

isbn = "978-1-4503-6852-0",

pages = "5--8",

booktitle = "Proceedings of the 1st ACM SIGSOFT International Workshop on Education through Advanced Software Engineering and Artificial Intelligence",

publisher = "Association for Computing Machinery",

address = "United States",

note = "International Workshop on Education through Advanced Software Engineering and Artificial Intelligence, EASEAI ; Conference date: 26-08-2019 Through 26-08-2019",

url = "https://easeai.github.io/",

}

Lungu, M 2019, Designing Personalized Learning Environments throughMonitoring and Guiding User Interactions with Code andNatural Language. in Proceedings of the 1st ACM SIGSOFT International Workshop on Education through Advanced Software Engineering and Artificial Intelligence. Association for Computing Machinery, pp. 5-8, International Workshop on Education through Advanced Software Engineering and Artificial Intelligence, 26/08/2019. https://doi.org/10.1145/3340435.3342724

Designing Personalized Learning Environments throughMonitoring and Guiding User Interactions with Code andNatural Language. / Lungu, Mircea.
Proceedings of the 1st ACM SIGSOFT International Workshop on Education through Advanced Software Engineering and Artificial Intelligence. Association for Computing Machinery, 2019. p. 5-8.

Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

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AB - Learning the vocabulary of a new language and a new programming API are similar in multiple ways. In this paper we evaluate several of the similarities and show that based on them we can design systems that can guide the learner towards improving their knowledge without an external tutor or preset curriculum. Instead, the class of systems we propose here are based on automated approaches of building maps of knowledge of the domain by mining repositories. By intersecting this knowledge with models of learner knowledge built by observing past learner interactions with artifacts of the domain we can generate highly personalized learning guidance.

KW - software engineering

KW - education

KW - Software Architecture

KW - ecosystems

KW - artificial intelligence

KW - software engineering

KW - education

KW - Software Architecture

KW - ecosystems

KW - artificial intelligence

U2 - 10.1145/3340435.3342724

DO - 10.1145/3340435.3342724

M3 - Article in proceedings

SN - 978-1-4503-6852-0

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BT - Proceedings of the 1st ACM SIGSOFT International Workshop on Education through Advanced Software Engineering and Artificial Intelligence

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Y2 - 26 August 2019 through 26 August 2019

ER -

Designing Personalized Learning Environments throughMonitoring and Guiding User Interactions with Code andNatural Language

Abstract

Workshop

Keywords

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Cite this