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

Leading team:

Dr. Giora Alexandron
Abigail Gurin Schleifer
Gilad Hazaraty-Zohar
Asaf Salman

Former Project team:

Dr. Moriah Ariely
Dr. Cippora Hofman
Tanya Nazaretsky

Secretariat and Administration:

Avital Cohen Onn

Brief

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.