Search Results for author: Luca Lugini

Found 6 papers, 0 papers with code

Contextual Argument Component Classification for Class Discussions

no code implementations COLING 2020 Luca Lugini, Diane Litman

Argument mining systems often consider contextual information, i. e. information outside of an argumentative discourse unit, when trained to accomplish tasks such as argument component identification, classification, and relation extraction.

Classification Component Classification +2

The Discussion Tracker Corpus of Collaborative Argumentation

no code implementations LREC 2020 Christopher Olshefski, Luca Lugini, Ravneet Singh, Diane Litman, Amanda Godley

Although Natural Language Processing (NLP) research on argument mining has advanced considerably in recent years, most studies draw on corpora of asynchronous and written texts, often produced by individuals.

Argument Mining Multi-Task Learning

Argument Component Classification for Classroom Discussions

no code implementations WS 2018 Luca Lugini, Diane Litman

This paper focuses on argument component classification for transcribed spoken classroom discussions, with the goal of automatically classifying student utterances into claims, evidence, and warrants.

Classification Component Classification +1

Annotating Student Talk in Text-based Classroom Discussions

no code implementations WS 2018 Luca Lugini, Diane Litman, Amanda Godley, Christopher Olshefski

Classroom discussions in English Language Arts have a positive effect on students' reading, writing and reasoning skills.

Predicting Specificity in Classroom Discussion

no code implementations WS 2017 Luca Lugini, Diane Litman

High quality classroom discussion is important to student development, enhancing abilities to express claims, reason about other students' claims, and retain information for longer periods of time.

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