APPLICATION OF ARTIFICIAL INTELLIGENCE IN PROGRAMMING EDUCATION WITHIN A BLENDED LEARNING ENVIRONMENT
Blended learning, which combines traditional teaching methods with online tools, requires effective technological solutions, particularly for ensuring continuous feedback between teachers and students. This article analyzes the current state of organizing blended learning and explores the use of mod...
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| Vydáno v: | Vìdkrite osvìtnê e-seredoviŝe sučasnogo unìversitetu číslo 17; s. 65 - 78 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
2024
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| ISSN: | 2414-0325, 2414-0325 |
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| Abstract | Blended learning, which combines traditional teaching methods with online tools, requires effective technological solutions, particularly for ensuring continuous feedback between teachers and students. This article analyzes the current state of organizing blended learning and explores the use of modern information technologies, specifically artificial intelligence and neural networks, in programming education. The authors present a detailed description of the educational platform VirtualLaboratories, a concept for a programming education platform that leverages artificial intelligence, particularly neural networks, to automate various aspects of coding, assessment, and evaluation of completed programming solutions.
The platform supports multiple programming languages, such as C#, SQL, and Python, and integrates leading neural networks for code analysis, optimization, and quality improvement. This includes models like GPT-4 Code, CodeBERT, and CodeT5, which provide not only automatic code analysis but also recommendations for improvement and optimization. These capabilities allow teachers to focus on individualized work with students by tracking their progress, while students can tackle assignments at their convenience and receive objective, high-precision analyses of their solutions.
The article also provides examples of neural network integration for automating code evaluation processes, which significantly reduces the time required for reviewing work and minimizes errors. It describes the main functional features of the platform, which enable the creation of multi-level programming tasks, real-time feedback, and error analysis to improve programming solutions. Additionally, the article outlines prospects for further research on implementing new artificial intelligence algorithms and expanding the platform’s capabilities to support more complex tasks and programming languages. |
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| AbstractList | Blended learning, which combines traditional teaching methods with online tools, requires effective technological solutions, particularly for ensuring continuous feedback between teachers and students. This article analyzes the current state of organizing blended learning and explores the use of modern information technologies, specifically artificial intelligence and neural networks, in programming education. The authors present a detailed description of the educational platform VirtualLaboratories, a concept for a programming education platform that leverages artificial intelligence, particularly neural networks, to automate various aspects of coding, assessment, and evaluation of completed programming solutions.
The platform supports multiple programming languages, such as C#, SQL, and Python, and integrates leading neural networks for code analysis, optimization, and quality improvement. This includes models like GPT-4 Code, CodeBERT, and CodeT5, which provide not only automatic code analysis but also recommendations for improvement and optimization. These capabilities allow teachers to focus on individualized work with students by tracking their progress, while students can tackle assignments at their convenience and receive objective, high-precision analyses of their solutions.
The article also provides examples of neural network integration for automating code evaluation processes, which significantly reduces the time required for reviewing work and minimizes errors. It describes the main functional features of the platform, which enable the creation of multi-level programming tasks, real-time feedback, and error analysis to improve programming solutions. Additionally, the article outlines prospects for further research on implementing new artificial intelligence algorithms and expanding the platform’s capabilities to support more complex tasks and programming languages. |
| Author | Koval, Oleksandr |
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| Cites_doi | 10.1186/s41239-017-0087-5 10.1007/s12528-013-9077-3 10.32840/1992-5786.2022.81.44 10.1016/j.iheduc.2004.02.001 10.1007/978-1-4842-7957-1 10.55056/cte.231 10.1007/s11528-019-00375-5 10.1016/j.edurev.2017.06.001 10.28925/2414-0325.2024.166 |
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| References | ref13 ref35 ref12 ref34 ref15 ref14 ref30 ref11 ref33 ref10 ref32 ref0 ref2 ref1 ref17 ref16 ref19 ref18 ref24 ref23 ref26 ref25 ref20 ref22 ref21 Osadcha (ref3) 2022 ref28 Boelens (ref29) 2017; 22 ref27 ref8 ref7 ref9 ref4 ref6 ref5 Dziuban (ref31) 2018 |
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