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Online Assessment of Students' Text Comprehension: Explorations into the Automated Scoring of Constructed Responses

EasyChair Preprint no. 3870

8 pagesDate: July 14, 2020

Abstract

Effective computerized reading comprehension strategy training requires an ability to provided automated an accurate to students as they answer open-ended comprehension question. This study explored different approaches to machine scoring as part of a larger research and development project. Two units involving 4 open-ended questions were used for initial testing. A comparison of simple frequency and deep learning techniques suggest that the latter have more potential to provide accurate feedback on response correctness.

Keyphrases: assessment, deep learning, machine learning, Question Answering, reading comprehension

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:3870,
  author = {Jean-François Rouet and Peter Hastings and Mônica Macedo-Rouet and Anna Potocki and M. Anne Britt},
  title = {Online Assessment of Students' Text Comprehension: Explorations into the Automated Scoring of Constructed Responses},
  howpublished = {EasyChair Preprint no. 3870},

  year = {EasyChair, 2020}}
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