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Title: Exploring Middle School Students’ Understanding of Algorithms Using Standards-Aligned Formative Assessments: Teacher and Researcher Perspectives
Authors: Basu, Satabdi
Rutstein, Daisy
Tate, Carol
Rachmatullah, Arif
Yang, Hui
Ortiz, Christopher
Keywords: Learning Sciences
Issue Date: 2023
Publisher: International Society of the Learning Sciences
Citation: Basu, S., Rutstein, D., Tate, C., Rachmatullah, A., Yang, H., & Ortiz, C. (2023). Exploring middle school students’ understanding of algorithms using standards-aligned formative assessments: Teacher and researcher perspectives. In Blikstein, P., Van Aalst, J., Kizito, R., & Brennan, K. (Eds.), Proceedings of the 17th International Conference of the Learning Sciences - ICLS 2023 (pp. 114-121). International Society of the Learning Sciences.
Abstract: ‘Algorithms’ is a core CS concept included in the K-12 CS standards, yet student challenges with understanding different aspects of algorithms are still not well documented, especially for younger students. This paper describes an approach to decompose the broad middle-school ‘algorithms’ standard into finer grained learning targets, develop formative assessment tasks aligned with the learning targets, and use the tasks to explore student understanding of, and challenges with, the various aspects of the standard. We present a number of student challenges revealed by our analysis of student responses to a set of standards-aligned formative assessment tasks and discuss how teachers and researchers interpreted student responses differently, even when using the same rubrics. Our study underscores the importance of carefully designed standards-aligned formative assessment tasks for monitoring student progress and demonstrates the need for teacher content knowledge to effectively use formative assessments during CS instruction.
Description: Long Paper
Appears in Collections:ISLS Annual Meeting 2023

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