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Pregled bibliografske jedinice broj: 1270188

Source Code Analysis in Programming Education: Evaluating Learning Content with Self-Organizing Maps


Jevtić, Marko; Mladenović, Saša; Granić, Andrina
Source Code Analysis in Programming Education: Evaluating Learning Content with Self-Organizing Maps // Applied sciences (Basel), 13 (2023), 9; 5719, 15 doi:10.3390/app13095719 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1270188 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Source Code Analysis in Programming Education: Evaluating Learning Content with Self-Organizing Maps

Autori
Jevtić, Marko ; Mladenović, Saša ; Granić, Andrina

Izvornik
Applied sciences (Basel) (2076-3417) 13 (2023), 9; 5719, 15

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
content management ; computer programming education ; source code analysis ; self organizing maps ; artificial intelligence ; neural networks

Sažetak
Due to the everchanging and evergrowing nature of programming technologies, the gap between the programming industry’s needs and the educational capabilities of both formal and informal educational environments has never been wider. However, the need to learn computer programming has never been greater, regardless of the motivation behind it. The number of programming concepts to be taught is increasing over time, while the amount of time available for education and training usually remains the same. The objective of this research was to analyze the source codes used in many educational systems to teach fundamental programming concepts to learners, regardless of their prior experience in programming. A total of 25 repositories containing 3882 Python modules were collected for the analysis. Through self-organization of the collected content, we obtained very compelling results about code structure, distribution, and differences. Based on those results, we concluded that Self-Organizing Maps are a powerful tool for both content and knowledge management, because they can highlight problems in the curriculum’s density as well as transparently indicate which programming concepts it has successfully observed and learned to recognize. Based on the level of transparency exhibited by Self- Organizing Maps, it is safe to say that they could be used in future research to enhance both human and machine learning of computer programming. By achieving this level of transparency, such an Artificial Intelligence system would be able to assist in overall computer programming education by communicating what should be taught, what needs to be learned, and what is known.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti



POVEZANOST RADA


Ustanove:
Prirodoslovno-matematički fakultet, Split

Profili:

Avatar Url Saša Mladenović (autor)

Avatar Url Marko Jevtić (autor)

Avatar Url Andrina Granić (autor)

Poveznice na cjeloviti tekst rada:

doi www.mdpi.com

Citiraj ovu publikaciju:

Jevtić, Marko; Mladenović, Saša; Granić, Andrina
Source Code Analysis in Programming Education: Evaluating Learning Content with Self-Organizing Maps // Applied sciences (Basel), 13 (2023), 9; 5719, 15 doi:10.3390/app13095719 (međunarodna recenzija, članak, znanstveni)
Jevtić, M., Mladenović, S. & Granić, A. (2023) Source Code Analysis in Programming Education: Evaluating Learning Content with Self-Organizing Maps. Applied sciences (Basel), 13 (9), 5719, 15 doi:10.3390/app13095719.
@article{article, author = {Jevti\'{c}, Marko and Mladenovi\'{c}, Sa\v{s}a and Grani\'{c}, Andrina}, year = {2023}, pages = {15}, DOI = {10.3390/app13095719}, chapter = {5719}, keywords = {content management, computer programming education, source code analysis, self organizing maps, artificial intelligence, neural networks}, journal = {Applied sciences (Basel)}, doi = {10.3390/app13095719}, volume = {13}, number = {9}, issn = {2076-3417}, title = {Source Code Analysis in Programming Education: Evaluating Learning Content with Self-Organizing Maps}, keyword = {content management, computer programming education, source code analysis, self organizing maps, artificial intelligence, neural networks}, chapternumber = {5719} }
@article{article, author = {Jevti\'{c}, Marko and Mladenovi\'{c}, Sa\v{s}a and Grani\'{c}, Andrina}, year = {2023}, pages = {15}, DOI = {10.3390/app13095719}, chapter = {5719}, keywords = {content management, computer programming education, source code analysis, self organizing maps, artificial intelligence, neural networks}, journal = {Applied sciences (Basel)}, doi = {10.3390/app13095719}, volume = {13}, number = {9}, issn = {2076-3417}, title = {Source Code Analysis in Programming Education: Evaluating Learning Content with Self-Organizing Maps}, keyword = {content management, computer programming education, source code analysis, self organizing maps, artificial intelligence, neural networks}, chapternumber = {5719} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • Social Science Citation Index (SSCI)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Citati:





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