Learning Trajectories for Everyday Computing: Integrating Computational Thinking in Elementary Mathematics, is a multidisciplinary effort that will study integrated mathematics and computational thinking (CT) instruction in elementary school. The project is a partnership involving the University of Illinois-Urbana Champaign, University of Chicago STEM Education at the University of Chicago, and the Learning Sciences Research Institute at the University of Illinois-Chicago. Investigators will use prototype learning trajectories (LTs) for CT in grades K-5 to design instructional materials that integrate CT into fractions instruction in grades 3-5. By studying implementation of these materials in elementary school classrooms, the project will (a) refine the LTs, (b) better understand how synergies between elementary mathematics and CT might be leveraged to create effective and efficient integrated instruction, and (c) generate evidence related to the effect of CT-infused mathematics instruction on students' understanding of fractions.
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Learning Trajectories for Everyday Computing: Integrating Computational Thinking in Elementary Mathematics, is a multidisciplinary effort that will study integrated mathematics and computational thinking (CT) instruction in elementary school. The project is a partnership involving the University of Illinois-Urbana Champaign, University of Chicago STEM Education at the University of Chicago, and the Learning Sciences Research Institute at the University of Illinois-Chicago. Investigators will use prototype learning trajectories (LTs) for CT in grades K-5 to design instructional materials that integrate CT into fractions instruction in grades 3-5. By studying implementation of these materials in elementary school classrooms, the project will (a) refine the LTs, (b) better understand how synergies between elementary mathematics and CT might be leveraged to create effective and efficient integrated instruction, and (c) generate evidence related to the effect of CT-infused mathematics instruction on students' understanding of fractions. The project is funded by the STEM+Computing Program, which seeks to study the applied integration of computational thinking and computing within disciplinary STEM teaching and learning in early childhood education through high school (preK-12).
This project is designed to facilitate the integration of CT in mathematics in elementary school. It builds on an earlier NSF-funded exploratory project by, (a) refining and elaborating a set of CT learning trajectories for grades 3 to 5 related to CT concepts of problem decomposition, repetition/looping, conditionals, and debugging in the mathematical context of fractions and (b) carrying out research into children's learning of mathematics and CT when math + CT is taught in an integrated program. To accomplish these goals, the project will develop instructional materials that can be used to teach integrated math + CT in grades 3-5. Mathematics instruction will be based on the Common Core State Standards for Mathematics, as realized in Everyday Mathematics 4, the elementary program from the University of Chicago School Mathematics Project. The project's efforts will focus on the Common Core's Number and Operations with Fractions (NF) domain. All instructional materials will be designed to maximize accessibility and engagement of academically diverse learners by using the Universal Design for Learning framework as an instructional guide for curriculum development. The project will use a mixed-methods approach to study the mathematics and CT learning that occurs and to understand the specific challenges students encounter when interacting with the materials. Student measures will be developed using an evidence-centered design process. These assessments include CT assessments newly created or modified from currently available assessments for older students, automated static analysis of students' computational artifacts, and measures of the Common Core's NF domain based on assessments embedded in the Everyday Mathematics instructional materials. Additionally, video screen recordings of purposefully selected students will be analyzed using the Collaborative Computing Observation instrument to evaluate the effectiveness of the activities as well as successes and challenges the students experience with the CT and mathematics activities. Teacher data will include classroom observations, interviews, and teacher reflections.
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