Content area
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.
Details
Educational Research;
Science Education;
Academic Achievement;
School Administration;
Language Patterns;
Interpersonal Relationship;
Natural Language Processing;
Educational Assessment;
Formative Evaluation;
Language Processing;
Learner Engagement;
Linguistics;
Cognitive Development;
Language Usage;
Influence of Technology;
Learning Strategies;
Cultural Background;
Learning Theories;
Multilingualism;
Middle Schools;
Feedback (Response);
Data Analysis;
Learning Readiness;
Academic Standards
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
1 Meadows Center for Preventing Educational Risk, College of Education, The University of Texas at Austin, Austin, TX 78712, USA; [email protected] (C.B.H.); [email protected] (D.L.B.)
2 Department of Teaching, Learning & Culture, College of Education & Human Development, Texas A&M University, College Station, TX 77840, USA; [email protected]
3 Computer Science Department, Lyle School of Engineering, Southern Methodist University, Dallas, TX 75205, USA; [email protected] (Z.W.); [email protected] (E.C.L.)