Can AI be racist? Color‐evasiveness in the application of machine learning to science assessments
Datos Bibliográficos
| ID | 21392631 |
|---|---|
| Autores | Tina Cheuk (0000-0001-7841-2492, School of Education, College of Science and Mathematics California Polytechnic State University San Luis Obispo California USA, autor de correspondencia) |
| Año | 2021 |
| Volumen | 105 |
| Número | 5 |
| Páginas | 825-836 |
| Fecha de publicación | 2021-09-01 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Science Education (JOURNAL) |
| Identificadores de la revista | ISSN: 0036-8326 • E-ISSN: 1098-237X |
| Editorial | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/sce.21671 |
| OpenAlex | W3191550339 |
| Idioma | EN |
| Citas recibidas | 21 |
| Referencias citadas | 58 |
Assessment developers are increasingly using the developing technology of machine learning in transforming how to assess students in their science learning. I argue that these algorithmic models further embed the structures of inequality that are pervasive in the development of science assessments in how they legitimize certain language practices that protect the hierarchical standing of status quo interests. My argument is situated within the broader emerging ethical challenges around this new technology. I apply a raciolinguistic equity analysis framework in critiquing the “new black box” that reinforces structural forms of discrimination against the linguistic repertoires of racially marginalized student populations. The article ends with me sharing a set of tactical shifts that can be deployed to form a more equitable and socially‐just field of machine learning enhanced science assessments
Argument (complex analysis) · Computational sociology · Epistemology · Equity (law) · Field (mathematics) · Inequality · Pedagogy · Political science · Science education · Set (abstract data type) · Situated · Social science · Sociology · Status quo · Artificial Intelligence · Computer Science · Educational Theory and Curriculum Studies · Law · Second Language Learning and Teaching · Student Assessment and Feedback
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Bridging Theory and Practice
Integrating artificial intelligence into early childhood teacher education
Talking through the “messy middle” of partnerships in science education
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Informing research on generative artificial intelligence from a language and literacy perspective
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At Last
A closer look at linguistic complexity
Conceptualizing color-evasiveness
Whiteness as Property
A Sociocognitive Perspective on Assessing EL Students in the Age of Common Core and Next Generation Science Standards
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Examining Language in Context
Critical Analysis of Problems Encountered in Incorporating Indigenous Knowledge in Science Teaching by Primary School Teachers in Zimbabwe
Mapping the Margins
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Automating Inequality
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Undoing Appropriateness
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Unsettling race and language
| Obras citantes distintas | 21 |
|---|---|
| Citas por año | 5,25 |
| Intervalo de citas | 2022 - 2026 (5) |
| Velocidad de citación | current |
| Altamente citado | No |
| Tipos de cita | Neutras: 21 |