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Navigating Bias in Educational Algorithms
This chapter examines the interplay between artificial intelligence and education, focusing on the biases that can emerge from algorithmic practices in digital learning environments. It highlights significant concepts such as educational data mining and addresses the implications of algorithmic bias on diverse student groups. Through case studies, the chapter emphasizes the need for tailored approaches to mitigate bias and improve educational outcomes.