Proficiency in argumentative writing contributes to one's academic and professional success. However, the Nation's Report Card shows that most adolescents are not skilled in argumentation and frequently experience difficulty when comprehending arguments and constructing well-rounded essays. Traditional teaching approaches for argumentative writing often require students to practice writing a whole essay before receiving feedback, missing deliberate practice opportunities on each difficulty factor that the students experience. On the other hand, while formative and personalized feedback is useful in improving students' logical writing skills, it requires substantive efforts by instructors and causes delays in feedback. This project will generate new insights into artificial intelligence and human-computer interaction capabilities for enhancing student learning of argumentative writing. The proposed research will advance the understanding of how people learn argumentative writing and argumentation. The project will improve the state-of-the-art in natural language processing by developing techniques for argument mining and argument quality measurement. The developed argumentative writing tools can be broadly applicable to many domains, thus providing learning and practice opportunities to anyone who wants to improve their argumentative writing skills.
Long document summarization, summarization evaluation, question generation, question-answer hierarchy
NSF, Award Number: 2302564. Duration: August 1, 2023 - July 31, 2026.