AI-ENHANCED PERSONALIZED LEARNING: THE TRANSFORMATIVE ROLE OF ADAPTIVE ALGORITHMS IN K-12 EDUCATIONAL OUTCOMES
Abstract
The landscape of K-12 education is undergoing a substantial transformation, driven by the integration of artificial intelligence (AI) and its capacity for personalized learning. Traditional didactic models often struggle to accommodate the heterogeneous learning paces and styles inherent in student populations (Liu et al., 2020). Personalized learning, in its essence, customizes educational experiences to individual student needs, interests, and strengths (Johnsen, 2016). Historically, this concept has been explored through various pedagogical approaches, emphasizing individualized instruction and student-centric methods (Jenkins, 1998). The advent of AI-enhanced adaptive algorithms provides novel avenues for realizing this long-held educational aspiration at scale.
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