Exploring the item features of a science assessment with complex tasks
| Autor: | Tina Collier, Mark Wilson, Linda Morell |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Electrical & Electronic Engineering
Vocabulary Artificial Intelligence and Image Processing Linear logistic test model Computer science media_common.quotation_subject Item bank Context (language use) computer.software_genre Argumentation theory 0504 sociology Item response theory Selection (linguistics) Electrical and Electronic Engineering Graphics Instrumentation Item explanatory models media_common business.industry Mechanical Engineering Applied Mathematics 05 social sciences 050401 social sciences methods 050301 education Condensed Matter Physics Data science Test (assessment) Item features Artificial intelligence business 0503 education computer Natural language processing |
| Zdroj: | Collier, T; Morell, L; & Wilson, M. (2018). Exploring the item features of a science assessment with complex tasks. Measurement: Journal of the International Measurement Confederation, 114, 16-24. doi: 10.1016/j.measurement.2017.08.039. UC Berkeley: Retrieved from: http://www.escholarship.org/uc/item/1bz699tf |
| ISSN: | 0263-2241 |
| DOI: | 10.1016/j.measurement.2017.08.039 |
| Popis: | © 2017 Elsevier Ltd Item explanatory models have the potential to provide insight into why certain items are easier or more difficult than others. Through the selection of pertinent item features, one can gather validity evidence for the assessment if construct-related item characteristics are chosen. This is especially important when designing assessment tasks that address new standards. Using data from the Learning Progressions in Middle School Science Instruction and Assessment (LPS) project, this paper adopts an “item explanatory” approach and investigates whether certain item features can explain differences in item difficulties by applying an extension of the linear logistic test model. Specifically, this paper explores the effects of five features on item difficulty: type (argumentation, content, embedded content), scenario-based context, format (multiple-choice or open-ended), graphics, and academic vocabulary. Interactions between some of these features were also investigated. With the exception of context, all features had a statistically significant effect on difficulty. |
| Databáze: | OpenAIRE |
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