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ERIC Number: EJ1031350
Record Type: Journal
Publication Date: 2014
Pages: 10
Abstractor: As Provided
Reference Count: N/A
ISSN: ISSN-0731-1745
Automated Scoring of Constructed-Response Science Items: Prospects and Obstacles
Liu, Ou Lydia; Brew, Chris; Blackmore, John; Gerard, Libby; Madhok, Jacquie; Linn, Marcia C.
Educational Measurement: Issues and Practice, v33 n2 p19-28 Sum 2014
Content-based automated scoring has been applied in a variety of science domains. However, many prior applications involved simplified scoring rubrics without considering rubrics representing multiple levels of understanding. This study tested a concept-based scoring tool for content-based scoring, c-raterâ„¢, for four science items with rubrics aiming to differentiate among multiple levels of understanding. The items showed moderate to good agreement with human scores. The findings suggest that automated scoring has the potential to score constructed-response items with complex scoring rubrics, but in its current design cannot replace human raters. This article discusses sources of disagreement and factors that could potentially improve the accuracy of concept-based automated scoring.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A