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Autor/inn/en | Lee, Hee-Sun; Pallant, Amy; Pryputniewicz, Sarah; Lord, Trudi; Mulholland, Matthew; Liu, Ou Lydia |
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Titel | Automated Text Scoring and Real-Time Adjustable Feedback: Supporting Revision of Scientific Arguments Involving Uncertainty |
Quelle | In: Science Education, 103 (2019) 3, S.590-622 (33 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
Zusatzinformation | ORCID (Lee, Hee-Sun) |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
ISSN | 0036-8326 |
DOI | 10.1002/sce.21504 |
Schlagwörter | Middle School Students; High School Students; Student Evaluation; Science Education; Secondary School Students; Science Process Skills; Persuasive Discourse; Writing (Composition); Science Tests; Computer Assisted Testing; Scoring; Feedback (Response); Formative Evaluation; Ambiguity (Semantics); Revision (Written Composition); Scoring Rubrics; Earth Science; Environmental Education; Water Middle school; Middle schools; Student; Students; Mittelschule; Mittelstufenschule; Schüler; Schülerin; High school; High schools; Oberschule; Studentin; Schulnote; Studentische Bewertung; Naturwissenschaftliche Bildung; Sekundarschüler; Persuasion; Persuasive Kommunikation; Schreibübung; Bewertung; Korrektur; Scoring formulas; Auswertungsbogen; Earth sciences; Geowissenschaften; Umweltbildung; Umwelterziehung; Umweltpädagogik; Wasser |
Abstract | This paper describes HASbot, an automated text scoring and real-time feedback system designed to support student revision of scientific arguments. Students submit open-ended text responses to explain how their data support claims and how the limitations of their data affect the uncertainty of their explanations. HASbot automatically scores these text responses and returns the scores with feedback to students. Data were collected from 343 middle- and high-school students taught by nine teachers across seven states in the United States. A mixed methods design was applied to investigate (a) how students' utilization of HASbot impacted their development of uncertainty-infused scientific arguments; (b) how students used feedback to revise their arguments, and (c) how the current design of HASbot supported or hindered students' revisions. Paired sample t tests indicate that students made significant gains from pretest to posttest in uncertainty-infused scientific argumentation, ES = 1.52 SD, p < 0.001. Linear regression analysis results indicate that students' HASbot use significantly contributed to their posttest performance on uncertainty-infused scientific argumentation while gender, English language learner status, and prior computer experience did not. From the analysis of videos, we identified several affordances and limitations of HASbot. (As Provided). |
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Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2020/1/01 |