The Transformative Collaboration of Human Intelligence and Artificial Intelligence in Designing Equitable Next-Generation Science Assessments

• In Event: The Role of Artificial Intelligence in Transforming Learning, Assessment, and Educational Practices

Abstract

This study investigates the intersection of human and artificial intelligence (AI) to design knowledge-in-use science assessments, supporting deep science learning and equitable opportunities for diverse learners. Anchored in the Next Generation Science Assessment and evidence-centered design, it integrates AI's computational strengths with human expertise. The study leverages Hybrid Intelligence, Distributed Cognition, and Self-Regulated Learning theories, employing a Design-Based Research approach across three stages: (1) iteratively training GPT models for assessment design, (2) gathering multidisciplinary expert feedback, and (3) developing domain-specific GPT models. Using thematic analysis, descriptive statistics, hierarchical coding, and user experience feedback, the study aims to create tailored assessments that emphasize equity, adaptability, and inclusivity, enhancing the educational landscape.

Author

• Tingting Li, Washington State University