Imagen de Portada

Advancing Formative Assessment: Using Natural Language Processing Within a Sociocultural Context to Measure Multilingual Student Science Word Knowledge

Guardado en:
Publicado en:Education Sciences vol. 15, no. 12 (2025), p. 1668-1687
Autor principal: Kowalkowski, Holland P
Otros Autores: Palma, Jose, Herrera, Cinthia B, Baker, Doris Luft, Wu Zhongdi, Larson, Eric C
Publicado:
MDPI AG
Materias:
Teaching
Students
Politics
Cognitive development
Influence
Teachers
Cognition & reasoning
System theory
Science education
Cultural factors
Knowledge
Vocabulary development
Linguistics
Learning
Language
Literacy
Sociocultural factors
Formative evaluation
Automation
Ecosystems
Artificial intelligence
Natural language processing
Integrated approach
Multilingualism
Social factors
Multiculturalism & pluralism
Mixed methods research
Socioeconomic factors
Oral Language
Educational Research
Academic Achievement
School Administration
Language Patterns
Interpersonal Relationship
Educational Assessment
Language Processing
Learner Engagement
Language Usage
Influence of Technology
Learning Strategies
Cultural Background
Learning Theories
Middle Schools
Feedback (Response)
Data Analysis
Learning Readiness
Academic Standards
Acceso en línea:Citation/Abstract
Full Text + Graphics
Full Text - PDF
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Resumen:This study investigates how natural language processing (NLP) can support the assessment and learning of science vocabulary among multilingual and multicultural learners, drawing on data from two federally funded studies in the United States. Students define and use target vocabulary in a sentence, with responses transcribed and scored using NLP tools. Employing a mixed-methods design and guided by established socioecological theoretical frameworks, we examine how students’ sociocultural contexts and background knowledge influence their understanding of science word knowledge and applicability. Our findings highlight both the potential and challenges of using AI tools in equitable and culturally responsive ways, offering insights to improve NPL-based assessment tools that support literacy teaching and learning in diverse student populations.
ISSN:2227-7102
2076-3344
DOI:10.3390/educsci15121668
Fuente:Education Database