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ERIC Number: ED560571
Record Type: Non-Journal
Publication Date: 2015-Jun
Pages: 8
Abstractor: As Provided
Reference Count: 21
Automatic Identification of Nutritious Contexts for Learning Vocabulary Words
Mostow, Jack; Gates, Donna; Ellison, Ross; Goutam, Rahul
International Educational Data Mining Society, Paper presented at the International Conference on Educational Data Mining (EDM) (8th, Madrid, Spain, Jun 26-29, 2015)
Vocabulary knowledge is crucial to literacy development and academic success. Previous research has shown learning the meaning of a word requires encountering it in diverse informative contexts. In this work, we try to identify "nutritious" contexts for a word--contexts that help students build a rich mental representation of the word's meaning. Using crowdsourced ratings of vocabulary contexts retrieved from the web, AVER learns models to score unseen contexts for unseen words. We specify the features used in the models, measure their individual informativeness, evaluate AVER's cross-validated accuracy in scoring contexts for unseen words, and compare its agreement with the human ratings against the humans' agreement with each other. The automated scores are not good enough to replace human ratings, but should reduce human effort by identifying contexts likely to be worth rating by hand, subject to a tradeoff between the number of contexts inspected by hand, and how many of them a human judge will consider nutritious. [For complete proceedings, see ED560503.]
International Educational Data Mining Society. e-mail:; Web site:
Publication Type: Speeches/Meeting Papers; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: Institute of Education Sciences (ED)
Authoring Institution: International Educational Data Mining Society
Identifiers - Assessments and Surveys: Flesch Kincaid Grade Level Formula
IES Funded: Yes
Grant or Contract Numbers: R305A130467