Learning analytics to improve academic performance among high school students
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In secondary education, academic performance is often analyzed too late and in a fragmented manner, which limits the timely identification of difficulties and the implementation of effective pedagogical decisions. In light of this, the study aimed to critically analyze how learning analytics can contribute to improving the academic performance of students at this level. Methodologically, an exploratory, descriptive, and analytical literature review was conducted, based on the search, selection, and synthesis of specialized academic literature. The results show that learning analytics contributes primarily in three areas: the early detection of at-risk students, the understanding of the relationship between digital engagement, commitment, and performance, and the personalization of teaching through data. The discussion highlights that these benefits depend not only on technology but also on the pedagogical interpretation of data, teacher literacy, and appropriate ethical and institutional conditions. In conclusion, learning analytics can enhance academic performance in secondary school, provided it is used to support teacher judgment and not as an automatic or decontextualized solution.
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