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| Content Provider | Springer Nature Link |
|---|---|
| Author | Dam, Gregory Kaufmann, Stefan |
| Copyright Year | 2008 |
| Abstract | Clinical interviews are a powerful method for assessing students’ knowledge and conceptual development. However, the analysis of the resulting data is time-consuming and can create a “bottleneck” in large-scale studies. This article demonstrates the utility of computational methods in supporting such an analysis. Thirty-four 7th-grade student explanations of the causes of Earth’s seasons were assessed using latent semantic analysis (LSA). Analyses were performed on transcriptions of student responses during interviews administered, prior to (n = 21) and after (n = 13) receiving earth science instruction. An instrument that uses LSA technology was developed to identify misconceptions and assess conceptual change in students’ thinking. Its accuracy, as determined by comparing its classifications to the independent coding performed by four human raters, reached 90%. Techniques for adapting LSA technology to support the analysis of interview data, as well as some limitations, are discussed. |
| Starting Page | 8 |
| Ending Page | 20 |
| Page Count | 13 |
| File Format | |
| ISSN | 1554351X |
| Journal | Behavior Research Methods |
| Volume Number | 40 |
| Issue Number | 1 |
| e-ISSN | 15543528 |
| Language | English |
| Publisher | Springer-Verlag |
| Publisher Date | 2008-01-01 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Cognitive Psychology |
| Content Type | Text |
| Resource Type | Article |
| Subject | Experimental and Cognitive Psychology Arts and Humanities Developmental and Educational Psychology |
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