INTRODUCTING A NEXT GENERATION CONCEPT INVENTORY USING CONSTRUCTED RESPONSE FOR EVALUATING STUDENT KNOWLEDGE OF COMPLEX SYSTEMS IN ENVIRONMENTAL EDUCATION

Here we present newly funded research in teaching and learning assessment. To better inform those who teach, make curricular decisions, and manage college-level environmental programs (EPs), we are investigating environmental students’ foundational knowledge and their ability to grasp complex systems-level concepts. Specifically, we propose applying an established machine learning method of evaluating constructed response (short answer) questions to create a Next Generation Concept Inventory (NGCI). This new approach to concept inventory construction creates a new set of constructed-response items and associated automated scoring models focused on the complex systems typically addressed in EPs. This work represents a partnership between universities for design and development of an assessment tool that can be used to evaluate and improve student learning. This work focuses on Food-Energy-Water Nexus systems as an initial pilot for NGCI development and involves thorough validity and reliability checks to provide an instrument of value for both research and to aid environmental educators and program administrators. This NGCI will undergo thorough validity and reliability checks to provide an instrument of value for both research and to aid environmental educators and program administrators. This work informs and advances the development of curricula and student learning outcomes for environmental programs. A potential outcome would be rigorously defended recommendations for EPs.