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The need for a single NLP offering for a diverse mix of graduate students (including computer scientists, information scientists, and linguists) has motivated us to develop a course that provides students with a breadth of understanding of the scope of real world applications, as well as depth of knowledge of the computational techniques on which to build in later experiences. We describe the three hands-on tasks for the course that have proven successful, namely: 1) in-class group simulations of computational processes; 2) team posters and public presentations on state-of-the-art commercial NLP applications, and; 3) team projects implementing various levels of human language processing using open-source software on large textual collections. Methods of evaluation and indicators of success are also described.
Liddy et al. (Sat,) studied this question.