CRAILF: A Zero-Cost Python-Based Gamified Framework for Enhancing AI Literacy Among Rural High School Students

Xia Yang

doi:10.37497/rev.artif.intell.educ.v7ii.75

Autores

Xia Yang School of Public Administration, Hebei University, Baoding, Hebei Province https://orcid.org/0009-0004-1395-1638

DOI:

https://doi.org/10.37497/rev.artif.intell.educ.v7ii.75

Palavras-chave:

Literacia em inteligência artificial, Ensino médio rural, Aprendizagem gamificada, Scaffolding personalizado

Resumo

Objetivo: A literacia em inteligência artificial tornou-se uma competência central na educação básica; contudo, estudantes do ensino médio em áreas rurais na China enfrentam severas barreiras de equidade devido à escassez de recursos e ao alto custo de ferramentas. Os frameworks existentes dependem fortemente de softwares comerciais e carecem de narrativas gamificadas, scaffolding personalizado, aprofundamento ético e avaliação de processos. Este estudo propõe e avalia o Cyber Rural AI Literacy Framework (CRAILF) — um framework gamificado, baseado exclusivamente em Python e de custo zero — para reduzir essas lacunas e analisar seu impacto na literacia em IA, aceitação tecnológica e consciência ética em contextos rurais de baixa disponibilidade de recursos.

Metodologia: Foi adotado um desenho quase-experimental de grupo único com pré e pós-teste, utilizando métodos mistos e acompanhamento de processo. Vinte estudantes do ensino médio rural da Província de Hebei participaram de uma intervenção offline de seis semanas, utilizando bibliotecas open source em Python (networkx, matplotlib, pygame). Os dados incluíram registros (logs), questionários, mapas de calor/gráficos radar e instrumentos baseados no TAM, sendo analisados por meio de estatísticas descritivas, tamanhos de efeito, testes t e codificação qualitativa.

Resultados: Observou-se alta aceitação tecnológica (média TAM de 5,8/7; d de Cohen = 0,92), com aumento de 28% na literacia em IA (d = 0,85). Os domínios de percepção/aprendizagem apresentaram pontuações entre 80–82, enquanto o domínio ético atingiu 68 (com aumento de 15% na reflexão sobre vieses). O scaffolding personalizado foi ativado em 65% dos casos, e estudantes em maior desvantagem apresentaram melhoria de 25%.

Originalidade/Valor: O estudo apresenta o primeiro framework gamificado de literacia em IA baseado exclusivamente em Python e de custo zero, integrando cenários imersivos e visualização dinâmica. Contribui para a ampliação da teoria da literacia em IA e do modelo I-TPACK, além de oferecer um caminho replicável e acessível para a promoção de educação em IA de forma equitativa em regiões em desenvolvimento.

Biografia do Autor

Xia Yang, School of Public Administration, Hebei University, Baoding, Hebei Province

Dr. Xia Yang is currently affiliated with the School of Public Administration at Hebei University. His research focuses on AI education equity, rural digital inclusion, and multimodal large language model applications. He has published several papers in related fields and is committed to promoting AI literacy education in low-resource environments.

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