Using Expert Interviews, Automated Search and Natural Language Processing to Identify Content for Instructional Materials and Assessment Development
UCLA’s Center for Research on Evaluation, Standards, and Testing (CRESST), working with its partner organization, the Center for Advanced Technology in Schools (CATS), has developed an innovative approach to identifying the conceptual content for inclusion in instruction and assessment.
With funding from the Institute of Education Sciences, CATS is developing learning games focused on acquiring pre-algebra schema and skills. For this effort, CRESST designed approaches to build in valid outcome development and then strategies to compare means that lead to the most effective learning.
To develop the goals for the games and to make them congruent with Common Core State Standards, the R&D team used the design of ontology to translate the verbal standards statements into network representations that define the universe of content and cognition included in the standards. READ MORE
