Enfoque Odychess: Un método dialéctico, constructivista y adaptativo para la enseñanza del ajedrez con inteligencias artificiales generativas
Project Overview
The document outlines the Odychess approach, a novel pedagogical method that incorporates generative artificial intelligence (AI) into the teaching of chess to improve students' knowledge, strategic thinking, and metacognitive skills. A quasi-experimental study involving a control group revealed significant advancements in these domains, demonstrating the effectiveness of the Odychess method, which merges dialectical and constructivist educational principles with AI-driven tutoring. This approach prioritizes active learning, critical discussions, and personalized instruction, highlighting the transformative potential of generative AI in educational settings. The findings from the study underscore how such AI integration not only enriches the learning experience in chess but also serves as a model for applying AI in diverse educational contexts, paving the way for enhanced engagement and deeper understanding among learners.
Key Applications
Odychess method integrating generative AI for chess education
Context: Secondary education for students aged 13-15 with beginner to intermediate chess skills
Implementation: A quasi-experimental design was used, with students in the experimental group receiving instruction through the Odychess method utilizing the Odychess-Tutor AI, while the control group followed traditional teaching methods.
Outcomes: Significant improvements in chess knowledge, strategic understanding, and metacognitive skills in the experimental group compared to the control group. Increased intrinsic motivation and engagement were also reported.
Challenges: Limited sample size and lack of random assignment may affect the generalizability of the findings.
Implementation Barriers
Implementation barrier
The lack of familiarity with AI tools among educators may hinder effective implementation.
Proposed Solutions: Providing training and resources for educators to effectively integrate AI tools into their teaching practices.
Technical barrier
Limited access to computational resources may restrict the use of complex AI models in educational settings.
Proposed Solutions: Utilizing cloud-based resources or optimizing models for performance on lower-spec hardware.
Project Team
Ernesto Giralt Hernandez
Researcher
Lazaro Antonio Bueno Perez
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Ernesto Giralt Hernandez, Lazaro Antonio Bueno Perez
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai