Applications of Hebrew NLP to Formative Assessment of Open-ended Questions

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Summary

Formative feedback on scientific explanation can improve the ability of students to organize and express their knowledge in a clear and persuasive manner. However, teachers are rarely able to provide timely and personalized feedback.

Recent advances in Natural Language Processing (NLP)  show great potential in regards to the analysis of educational texts. Our work focuses on leveraging such technologies in order to develop algorithms and tools that can assist teachers in assessing and providing feedback on open-ended questions in scientific domains.

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