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Text mining in the context of technical education and natural language processing refers to the application of computational methods to extract meaningful patterns and insights from unstructured text data related to education, such as student essays, class notes, or discussion forums. It involves analyzing textual content using statistical techniques to identify trends, sentiments, or relationships that can inform educational research, improve teaching practices, or support learning outcomes. The process often includes text preprocessing, feature extraction, and modeling, ultimately generating actionable insights to benefit educators, administrators, and students alike.