Using Rasch Modeling and Option Probability Curves to Diagnose Students' Misconceptions / Cari F. Herrmann-Abell and George E. DeBoer.
Understanding students' misconceptions and how they change is an essential part of supporting students in their science learning. This paper presents results from distractor-driven multiple-choice assessments that target students' misconceptions about energy. Over 20,000 elementary, middle...
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| Language: | English |
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| 100 | 1 | |a Herrmann-Abell, Cari F. | |
| 245 | 1 | 0 | |a Using Rasch Modeling and Option Probability Curves to Diagnose Students' Misconceptions / |c Cari F. Herrmann-Abell and George E. DeBoer. |
| 264 | 1 | |a [Place of publication not identified] : |b Distributed by ERIC Clearinghouse, |c 2016. | |
| 300 | |a 1 online resource (12 pages) | ||
| 336 | |a text |b txt |2 rdacontent. | ||
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| 500 | |a Contract Number: R305A120138. |5 ericd. | ||
| 500 | |a Abstractor: As Provided. |5 ericd. | ||
| 500 | |a Educational level discussed: Elementary Education. | ||
| 500 | |a Educational level discussed: Middle Schools. | ||
| 500 | |a Educational level discussed: Secondary Education. | ||
| 500 | |a Educational level discussed: Junior High Schools. | ||
| 516 | |a Text (Speeches/Meeting Papers) | ||
| 516 | |a Text (Reports, Research) | ||
| 520 | |a Understanding students' misconceptions and how they change is an essential part of supporting students in their science learning. This paper presents results from distractor-driven multiple-choice assessments that target students' misconceptions about energy. Over 20,000 elementary, middle and high school students from across the U.S. participated in the study. Rasch modeling was used to estimate item and student measures. Option probability curves were used to represent the distribution of correct answers and misconceptions across the range of student achievement levels. Analysis of the shapes of the curves and where they occur as a function of student achievement provides insights on changes in students' thinking as they learn more about a topic. These data can then be used to inform instruction. | ||
| 524 | |a Grantee Submission, Paper presented at the Annual Meeting of the American Educational Research Association (Washington, DC, Apr 8-12, 2016). |2 ericd. | ||
| 650 | 0 | 7 | |a Item Response Theory. |2 ericd. |
| 650 | 0 | 7 | |a Probability. |2 ericd. |
| 650 | 0 | 7 | |a Elementary School Students. |2 ericd. |
| 650 | 0 | 7 | |a Middle School Students. |2 ericd. |
| 650 | 0 | 7 | |a Misconceptions. |2 ericd. |
| 650 | 0 | 7 | |a Scientific Concepts. |2 ericd. |
| 650 | 0 | 7 | |a Energy. |2 ericd. |
| 650 | 0 | 7 | |a Instructional Program Divisions. |2 ericd. |
| 650 | 0 | 7 | |a Statistical Analysis. |2 ericd. |
| 650 | 0 | 7 | |a Multiple Choice Tests. |2 ericd. |
| 700 | 1 | |a DeBoer, George E., |e author. | |
| 856 | 4 | 0 | |u http://files.eric.ed.gov/fulltext/ED572821.pdf |z Full Text (via ERIC) |
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