Educational software supported by Artificial Intelligence techniques to strengthen teaching and learning in the subject of programming I
The research focused on the creation of an educational platform that offers interactive and personalized content, allowing the tool to adapt to the student's level, with the goal of optimizing the learning of key programming concepts. The type of research used was applied research, given that software was designed and built and implemented in a real-life public setting in a real-life educational context. A mixed-method experimental design was also employed, using quantitative and qualitative methods to evaluate both the numerical results of students' academic performance and the students' subjective perceptions and experiences when using the platform. NeuroCode was designed and built, with the support of artificial intelligence techniques, to improve teaching and learning in the Programming I course. This educational software includes an intelligent chatbot that provides real-time support to students, accurately resolving any questions they may have about programming concepts and/or logic problems. The chatbot adapts to the student's needs, providing personalized responses and helping to maintain uninterrupted learning continuity. In conclusion, the implementation of AI-based educational software is an effective tool for enhancing the teaching-learning process, as it provides students with a more interactive and efficient experience while also assisting teachers in their educational work.
Authors
- Luis Manuel Palmera Quintero (ORCID: https://orcid.org/0000-0002-3242-2115)
- Luiz Pedro Guerra
- Daniel Román-Acosta (ORCID: https://orcid.org/0000-0002-4300-9174)
- Lilian Natalia Sayago Velasquez (ORCID: https://orcid.org/0000-0002-5005-3042)
Institutions
- Popular University of Cesar (CO)
- Acciona (Spain) (ES)
Publication Details
- Journal
- Metaverse Basic and Applied Research
- Published
- 2024-12-30
- DOI
- https://doi.org/10.56294/mr2024133
- Primary Topic
- Online Learning and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 0.00