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Permanent link (DOI): https://doi.org/10.7939/R3MP4VV1W

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Automated Essay Scoring Framework for a Multilingual Medical Licensing Examination Open Access

Descriptions

Other title
Subject/Keyword
classification
automated scoring
technology-enhanced assessments
large-scale assessment
scoring
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Latifi, Syed Muhammad Fahad
Supervisor and department
Dr. Mark J. Gierl, Department of Educational Psychology
Examining committee member and department
Dr. Hollis Lai, Undergraduate Medical Education, Faculty of Medicine & Dentistry
Dr. Damien Cormier, Department of Educational Psychology
Department
Department of Educational Psychology
Specialization
Measurement, Evaluation and Cognition
Date accepted
2013-12-19T11:53:54Z
Graduation date
2014-06
Degree
Master of Education
Degree level
Master's
Abstract
Automated essay scoring (AES) is a technology that efficiently and economically score written responses by emulating intelligence of human scorer. Present study had employed open-source Natural Language Processing technologies for developing AES framework, to score multilingual medical licensing examination. English, French, and translated-French responses of constructed-response items were scored automatically, and the strength of multilingual automated scoring framework were evaluated in relation to human scoring. Machine-translation was also contextualized for raising AES performance, when restricted sample size counters the performance of AES software. Specific feature extraction and model building strategies resulted in high concordance between AES and human scoring, with average maximum human-machine accuracy of 95.7%, which was in almost perfect agreement with human markers. Results also revealed that the machine-translator had raised predictive consistency but negatively influenced the predictive accuracy. Implications of results for practice, as well as directions for future research are also presented.
Language
English
DOI
doi:10.7939/R3MP4VV1W
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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2014-06-15T07:10:34.861+00:00
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File format: pdf (Portable Document Format)
Mime type: application/pdf
File size: 1465641
Last modified: 2015:10:18 01:34:59-06:00
Filename: Latifi__SyedMuhammadFahad_Spring_2014.pdf
Original checksum: 08be8ee9c7fdc30e06cb8731177041a2
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File title: Chapter 1: Introduction
File title: AES_using_Three_MLAs
File author: Fahad Latifi
Page count: 61
File language: en-US
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