no code implementations • ACL 2022 • Subhadarshi Panda, Frank Palma Gomez, Michael Flor, Alla Rozovskaya
In a fill-in-the-blank exercise, a student is presented with a carrier sentence with one word hidden, and a multiple-choice list that includes the correct answer and several inappropriate options, called distractors.
no code implementations • WS 2020 • Xianyang Chen, Chee Wee (Ben) Leong, Michael Flor, Beata Beigman Klebanov
This paper describes the ETS entry to the 2020 Metaphor Detection shared task.
no code implementations • WS 2020 • Swapna Somasundaran, Xianyang Chen, Michael Flor
This paper studies emotion arcs in student narratives.
no code implementations • WS 2019 • Michael Flor, Swapna Somasundaran
This study explores the relation between lexical concreteness and narrative text quality.
no code implementations • WS 2019 • Brian Riordan, Michael Flor, Robert Pugh
Character-based representations in neural models have been claimed to be a tool to overcome spelling variation in in word token-based input.
1 code implementation • WS 2019 • Michael Flor, Michael Fried, Alla Rozovskaya
We also develop a minimallysupervised context-aware approach to spelling correction.
no code implementations • ACL 2019 • Nitin Madnani, Beata Beigman Klebanov, Anastassia Loukina, Binod Gyawali, Patrick Lange, John Sabatini, Michael Flor
Literacy is crucial for functioning in modern society.
no code implementations • WS 2018 • Michael Flor, Brian Riordan
We present a novel rule-based system for automatic generation of factual questions from sentences, using semantic role labeling (SRL) as the main form of text analysis.
no code implementations • WS 2018 • Michael Flor, Beata Beigman Klebanov
The study used a corpus of essays written during a standardized examination of English language proficiency.
no code implementations • NAACL 2018 • Beata Beigman Klebanov, Chee Wee (Ben) Leong, Michael Flor
We present a corpus of 240 argumentative essays written by non-native speakers of English annotated for metaphor.
no code implementations • TACL 2018 • Swapna Somasundaran, Michael Flor, Martin Chodorow, Hillary Molloy, Binod Gyawali, Laura McCulla
This work lays the foundation for automated assessments of narrative quality in student writing.
no code implementations • WS 2017 • Michael Flor, Swapna Somasundaran
Our lexical cohesion system achieves accuracy comparable to previously published baseline results.
no code implementations • 4 Mar 2014 • Derrick Higgins, Chris Brew, Michael Heilman, Ramon Ziai, Lei Chen, Aoife Cahill, Michael Flor, Nitin Madnani, Joel Tetreault, Daniel Blanchard, Diane Napolitano, Chong MIn Lee, John Blackmore
Developments in the educational landscape have spurred greater interest in the problem of automatically scoring short answer questions.