Happy Are Those Who Grade without Seeing: A Multi-Task Learning Approach to Grade Essays Using Gaze Behaviour

Sandeep Mathias; Rudra Murthy; Diptesh Kanojia; Abhijit Mishra; Pushpak Bhattacharyya

doi:10.48550/arXiv.2005.12078

Back

Conference proceeding

Happy Are Those Who Grade without Seeing: A Multi-Task Learning Approach to Grade Essays Using Gaze Behaviour

Sandeep Mathias, Rudra Murthy, Diptesh Kanojia, Abhijit Mishra and Pushpak Bhattacharyya

1ST CONFERENCE OF THE ASIA-PACIFIC CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS AND THE 10TH INTERNATIONAL JOINT CONFERENCE ON NATURAL LANGUAGE PROCESSING (AACL-IJCNLP 2020), pp.858-872

01/01/2020

DOI: https://doi.org/10.48550/arXiv.2005.12078

Abstract

Computer Science, Artificial Intelligence

Computer Science, Interdisciplinary Applications

Linguistics

Science & Technology

Computer Science

Social Sciences

Technology

The gaze behaviour of a reader is helpful in solving several NLP tasks such as automatic essay grading. However, collecting gaze behaviour from readers is costly in terms of time and money. In this paper, we propose a way to improve automatic essay grading using gaze behaviour, which is learnt at run time using a multi-task learning framework. To demonstrate the efficacy of this multi-task learning based approach to automatic essay grading, we collect gaze behaviour for 48 essays across 4 essay sets, and learn gaze behaviour for the rest of the essays, numbering over 7000 essays. Using the learnt gaze behaviour, we can achieve a statistically significant improvement in performance over the state-of-the-art system for the essay sets where we have gaze data. We also achieve a statistically significant improvement for 4 other essay sets, numbering about 6000 essays, where we have no gaze behaviour data available. Our approach establishes that learning gaze behaviour improves automatic essay grading.

Metrics

5 Record Views

2 Times Cited - Web of Science

Details

Title: Happy Are Those Who Grade without Seeing: A Multi-Task Learning Approach to Grade Essays Using Gaze Behaviour
Creators: Sandeep Mathias - Indian Inst Technol, Dept Comp Sci, Bombay, Maharashtra, India
Rudra Murthy - Indian Inst Technol, Dept Comp Sci, Bombay, Maharashtra, India
Diptesh Kanojia - Indian Inst Technol, Dept Comp Sci, Bombay, Maharashtra, India
Abhijit Mishra - IBM Res, Gurgaon, India
Pushpak Bhattacharyya - Indian Inst Technol, Dept Comp Sci, Bombay, Maharashtra, India
Publication Details: 1ST CONFERENCE OF THE ASIA-PACIFIC CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS AND THE 10TH INTERNATIONAL JOINT CONFERENCE ON NATURAL LANGUAGE PROCESSING (AACL-IJCNLP 2020), pp.858-872
Publisher: Assoc Computational Linguistics-Acl
Number of pages: 15
Date published: 01/01/2020
Identifiers: 99822305402346
Copyright: The URI http://arxiv.org/licenses/nonexclusive-distrib/1.0/ is used to record the fact that the submitter granted the following license to arXiv.org on submission of an article: I grant arXiv.org a perpetual, non-exclusive license to distribute this article. I certify that I have the right to grant this license. I understand that submissions cannot be completely removed once accepted. I understand that arXiv.org reserves the right to reclassify or reject any submission.
Academic Unit: School of Computer Science and Electronic Engineering
Language: English
Resource Type: Conference proceeding

Happy Are Those Who Grade without Seeing: A Multi-Task Learning Approach to Grade Essays Using Gaze Behaviour

Abstract

Metrics

Details

Usage Policy