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2. Automated Essay Scoring and the Deep Learning Black Box: How Are Rubric Scores Determined?

Author

Kumar, Vivekanandan S. and Boulanger, David

Abstract

This article investigates the feasibility of using automated scoring methods to evaluate the quality of student-written essays. In 2012, Kaggle hosted an Automated Student Assessment Prize contest to find effective solutions to automated testing and grading. This article: a) analyzes the datasets from the contest -- which contained hand-graded essays -- to measure their suitability for developing competent automated grading tools; b) evaluates the potential for deep learning in automated essay scoring (AES) to produce sophisticated testing and grading algorithms; c) advocates for thorough and transparent performance reports on AES research, which will facilitate fairer comparisons among various AES systems and permit study replication; d) uses both deep neural networks and state-of-the-art NLP tools to predict finer-grained rubric scores, to illustrate how rubric scores are determined from a linguistic perspective, and to uncover important features of an effective rubric scoring model. This study's findings first highlight the level of agreement that exists between two human raters for each rubric as captured in the investigated essay dataset, that is, 0.60 on average as measured by the quadratic weighted kappa (QWK). Only one related study has been found in the literature which also performed rubric score predictions through models trained on the same dataset. At best, the predictive models had an average agreement level (QWK) of 0.53 with the human raters, below the level of agreement among human raters. In contrast, this research's findings report an average agreement level per rubric with the two human raters' resolved scores of 0.72 (QWK), well beyond the agreement level between the two human raters. Further, the AES system proposed in this article predicts holistic essay scores through its predicted rubric scores and produces a QWK of 0.78, a competitive performance according to recent literature where cutting-edge AES tools generate agreement levels between 0.77 and 0.81, results computed as per the same procedure as in this article. This study's AES system goes one step further toward interpretability and the provision of high-level explanations to justify the predicted holistic and rubric scores. It contends that predicting rubric scores is essential to automated essay scoring, because it reveals the reasoning behind AIED-based AES systems. Will building AIED accountability improve the trustworthiness of the formative feedback generated by AES? Will AIED-empowered AES systems thoroughly mimic, or even outperform, a competent human rater? Will such machine-grading systems be subjected to verification by human raters, thus paving the way for a human-in-the-loop assessment mechanism? Will trust in new generations of AES systems be improved with the addition of models that explain the inner workings of a deep learning black box? This study seeks to expand these horizons of AES to make the technique practical, explainable, and trustable.

Published
2021
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3. SHAPed Automated Essay Scoring: Explaining Writing Features’ Contributions to English Writing Organization

Author

Boulanger, David, Kumar, Vivekanandan, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Kumar, Vivekanandan, editor, and Troussas, Christos, editor

Published
2020
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4. Challenges in recruiting and retaining participants for smart learning environment studies

Author

Guillot, Isabelle, Guillot, Claudia, Guillot, Rébecca, Seanosky, Jérémie, Boulanger, David, Fraser, Shawn N., Kumar, Vivekanandan, Kinshuk, Huang, Ronghuai, Series Editor, Kinshuk, Series Editor, Jemni, Mohamed, Series Editor, Chen, Nian-Shing, Series Editor, Spector, J. Michael, Series Editor, Chang, Maiga, editor, Popescu, Elvira, editor, and Sampson, Demetrios G., editor

Published
2019
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6. Learning Traces, Competence Assessment, and Causal Inference for English Composition

Author

Clemens, Clayton, Kumar, Vivekanandan, Boulanger, David, Seanosky, Jérémie, Kinshuk, Huang, Ronghuai, Series Editor, Kinshuk, Series Editor, Jemni, Mohamed, Series Editor, Chen, Nian-Shing, Series Editor, Spector, J. Michael, Series Editor, Kumar, Vivekanandan, editor, Essa, Alfred, editor, Huang, Yueh-Min, editor, Koper, Rob, editor, Tortorella, Richard A. W., editor, Chang, Ting-Wen, editor, Li, Yanyan, editor, and Zhang, Zhizhen, editor

Published
2018
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8. Deep Learning in Automated Essay Scoring

Author

Boulanger, David, Kumar, Vivekanandan, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Nkambou, Roger, editor, Azevedo, Roger, editor, and Vassileva, Julita, editor

Published
2018
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10. Assessing Learners’ Progress in a Smart Learning Environment using Bio-Inspired Clustering Mechanism

Author

Govindarajan, Kannan, Boulanger, David, Seanosky, Jérémie, Bell, Jason, Pinnell, Colin, Suresh Kumar, Vivekanandan, Kinshuk, Huang, Ronghuai, Series editor, Kinshuk, Series editor, Jemni, Mohamed, Series editor, Chen, Nian-Shing, Series editor, Spector, J. Michael, Series editor, Popescu, Elvira, editor, Khribi, Mohamed Koutheair, editor, and Sampson, Demetrios G., editor

Published
2017
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11. Breadth and Depth of Learning Analytics

Author

Boulanger, David, Seanosky, Jeremie, Guillot, Rebecca, Kumar, Vivekanandan Suresh, Kinshuk, Huang, Ronghuai, Series editor, Kinshuk, Series editor, Jemni, Mohamed, Series editor, Chen, Nian-Shing, Series editor, Spector, J. Michael, Series editor, Popescu, Elvira, editor, Khribi, Mohamed Koutheair, editor, and Sampson, Demetrios G., editor

Published
2017
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12. Software-Defined Networking (SDN)-Based Network Services for Smart Learning Environment

Author

Govindarajan, Kannan, Kumar, Vivekanandan Suresh, Boulanger, David, Seanosky, Jérémie, Bell, Jason, Pinnell, Colin, Kinshuk, Somasundaram, Thamarai Selvi, Huang, Ronghuai, Series editor, Kinshuk, Series editor, Jemni, Mohamed, Series editor, Chen, Nian-Shing, Series editor, Spector, J. Michael, Series editor, Li, Yanyan, editor, Chang, Maiga, editor, Kravcik, Milos, editor, and Popescu, Elvira, editor

Published
2016
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13. SCALE: A Competence Analytics Framework

Author

Boulanger, David, Seanosky, Jérémie, Pinnell, Colin, Bell, Jason, Kumar, Vivekanandan, Kinshuk, Huang, Ronghuai, Series editor, Kinshuk, Series editor, Jemni, Mohamed, Series editor, Chen, Nian-Shing, Series editor, Spector, J. Michael, Series editor, Li, Yanyan, editor, Chang, Maiga, editor, Kravcik, Milos, editor, and Popescu, Elvira, editor

Published
2016
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14. Measurement of Quality of a Course : Analysis to Analytics

Author

Seanosky, Jérémie, Boulanger, David, Pinnell, Colin, Bell, Jason, Forner, Lino, Baddeley, Michael, Kinshuk, Kumar, Vivekanandan Suresh, Huang, Ronghuai, Series editor, Kinshuk, Series editor, Jemni, Mohamed, Series editor, Chen, Nian-Shing, Series editor, Spector, J. Michael, Series editor, Gros, Begoña, editor, and Maina, Marcelo, editor

Published
2016
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15. Big Data Learning Analytics: A New Perpsective

Author

Kumar, Vivekanandan Suresh, Kinshuk, Somasundaram, Thamarai Selvi, Boulanger, David, Seanosky, Jérémie, Vilela, Marcello F., Huang, Ronghuai, Series editor, Kinshuk, Series editor, Jemni, Mohamed, Series editor, Chen, Nian-Shing, Series editor, and Spector, J. Michael, Series editor

Published
2015
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16. An Approach to Measure Coding Competency Evolution : Toward Learning Analytics

Author

Kumar, Vive, Kinshuk, Somasundaram, Thamaraiselvi, Harris, Steve, Boulanger, David, Seanosky, Jeremie, Paulmani, Geetha, Panneerselvam, Karthikeyan, Huang, Ronghuai, Series editor, Kinshuk, Series editor, Jemni, Mohamed, Series editor, Chen, Nian-Shing, Series editor, Spector, J. Michael, Series editor, Chang, Maiga, editor, and Li, Yanyan, editor

Published
2015
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17. Unfolding Learning Analytics for Big Data

Author

Seanosky, Jeremie, Boulanger, David, Kumar, Vivekanandan, Kinshuk, Huang, Ronghuai, Series editor, Kinshuk, Series editor, Jemni, Mohamed, Series editor, Chen, Nian-Shing, Series editor, Spector, J. Michael, Series editor, Chen, Guang, editor, Kumar, Vive, editor, and Kong, Siu Cheung, editor

Published
2015
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18. Smart Learning Analytics

Author

Boulanger, David, Seanosky, Jeremie, Kumar, Vive, Kinshuk, Panneerselvam, Karthikeyan, Thamarai Selvi Somasundaram, Huang, Ronghuai, Series editor, Kinshuk, Series editor, Jemni, Mohamed, Series editor, Chen, Nian-Shing, Series editor, Spector, J. Michael, Series editor, Chen, Guang, editor, Kumar, Vive, editor, and Kong, Siu Cheung, editor

Published
2015
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21. Competence analytics

Author

Kumar, Vivekanandan, Boulanger, David, Seanosky, Jeremie, Kinshuk, Panneerselvam, Karthikeyan, and Somasundaram, Thamarai Selvi

Published
2014
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36. L'entrée en vigueur de la Convention de La Haye du 14 mars 1978 sur la loi applicable aux régimes matrimoniaux

Author

Boulanger, David, Université d'Artois (UA), Centre de Recherche en Droit Ethique et Procédures (CDEP), and collaboration or project value

Subjects
TRAITE INTERNATIONAL, Loi applicable, Convention de La Haye du 14 mars 1978, [SHS.DROIT]Humanities and Social Sciences/Law, Mariage, Régime matrimonial, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
1993

38. Breeding new CRM consultants

Author

Boulanger, David

Subjects
Customer relationship management software, Customer relationship management, Customer relationship management, Customer relationship management software, Consulting services
Abstract

I THOUGHT 'The New Breed of CRM Consultant' (October 2008, http://snurl.com/ 1008mckay) was great! As an ex-PricewaterhouseCoopers/ IBMer who has implemented some of the most complex SAP/Oracle CRM implementations around, […]

Published
2009

39. Making Magazines.

Author

Boulanger, David R.

Abstract

Describes an assignment that urges expository writers to pursue their own interests and create a fully developed prose project that they will be eager to share. (HTH)

Published
1987

40. FEEDBACK.

Author

Thatte, Ashutosh, Galbreath, Bill, Boulanger, David, Suddreth, Greg, and Larson, Dean

Subjects
LETTERS to the editor, MARKETING, ARCHITECTURE, BUSINESS enterprises, CONSUMERS
Abstract

Several letters to the editor are presented in response to articles in previous issues including "There's No Place Like Home," "These Marketing Messages Go to 11," both in the October 2008 issue, and "The Buzz Around Business Architecture" in the October 27, 2008 issue.

Published
2009

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