Email this article Optimization of Media Literacy Learning through Artificial Intelligence Recommendation System
Abstract
The use of technology in the digital era has transformed the way we interact with media, emphasizing the importance of media literacy in understanding and navigating information effectively. However, media literacy education faces challenges, including the rapid evolution of the media and the prevalence of misinformation. The aim of this research is to measure the effectiveness of media literacy learning through AI recommendation systems among students of the Indonesian Language and Literature Education Study Program, Unika Santu Paulus Ruteng. This study employed a quasi-experimental method with pre-test and post-test designs to evaluate the effectiveness of using artificial intelligence recommendation systems in improving students' media literacy. The research sample consisted of 2021-level students, with Class 2021A as the experimental group and Class 2021B as the control group. Data collection was conducted through descriptive and writing tests. Data analysis utilized correlation tests to examine the relationship between variables and T-tests to compare pre-test and post-test scores between the two groups. The results indicate that the class using AI recommendation systems experienced a significant improvement in media literacy skills compared to the control group. Data analysis also showed an increase in score homogeneity, confirming the effectiveness of the intervention in making learning more equitable. The implications of these findings suggest that integrating AI recommendation.
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DOI: https://doi.org/10.24036/komposisi.v25i2.129152
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