Artificial intelligence based digital guide for strengthening computer competencies
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Abstract
Introduction. The incorporation of artificial intelligence in education requires teachers to articulate digital mastery, pedagogical criteria, creativity, and responsibility. Objectives. The objective is to evaluate the effectiveness of a digital guide based on artificial intelligence to strengthen the computer skills of 15 teachers from a single school. Methodology. A pre-experimental quantitative study of a particular group was structured, with pre-test and post-test measurements. The intervention was supported by activities from NotebookLM, ChatGPT, Educaplay IA and Suno. The 30-item instrument was submitted to the judgment of ten experts and reached Cronbach’s alpha of 0.87. The hypothesis stated that the post-test score would be significantly higher than that of the pre-test. Descriptive statistics, Pearson's correlation, Student’s T-test for related samples, and Cohen’s D test were applied. Results. In analytical part, the global mean increased from 51.60 to 72.60 points; the average gain was 21.00 points (95% confidence interval [18.56; 23.44]). The difference was significant, t (14) = 18.47, p < 0.001, with an exceptionally large effect, dz = 4.77. Conclusions. Creative competence showed the greatest relative change. The guide articulates situated practice, source verification, inclusive planning, and resource creation. General area of study: Education. Specific area of study: Educational technology and teacher training. Type of study: Original article.
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