The Effectiveness of the AI-Based Flipped Classroom Learning Model in Enhancing Students’ Digital Reading Literacy
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Abstract
This study investigates the effectiveness of the AI-based flipped classroom learning model in enhancing students’ digital reading literacy. Digital literacy has become an essential skill in the 21st century, requiring learners to comprehend, analyze, and critically evaluate information from diverse online sources. Previous studies have shown that the flipped classroom can promote active learning and engagement, while artificial intelligence (AI) offers personalized learning pathways and real-time feedback to support individual progress. This research combines both approaches to examine their impact on students’ ability to navigate digital texts. Using a quasi-experimental design, two groups of students were compared: one learning through an AI-supported flipped model and the other through traditional methods. Data were collected through pre-tests, post-tests, classroom observations, and student feedback surveys. The results reveal that students in the AI-based flipped classroom showed significantly greater improvements in digital reading literacy, including higher comprehension, critical thinking, and evaluative skills, compared to their peers in the traditional classroom. The findings suggest that the integration of AI features, such as personalization and immediate feedback, strengthened self-regulated learning, while the flipped structure optimized classroom time for collaboration and higher-order thinking. This study concludes that AI-based flipped learning represents an effective and innovative pedagogical strategy for improving digital reading literacy, with important implications for curriculum design, pedagogy, and teacher roles in the digital era.
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