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The expansion of computer science (CS) into K-12 contexts has resulted in a diverse ecosystem of curricula designed for various grade levels, teaching a variety of concepts, and using a wide array of different programming languages and environments. Many students will learn more than one programming language over the course of their studies. There is a growing need for computer science assessment that can measure student learning over time, but the multilingual learning pathways create two challenges for assessment in computer science. First, there are not validated assessments for all of the programming languages used in CS classrooms. Second, it is difficult to measure growth in student understanding over time when students move between programming languages as they progress in their CS education. In this position paper, we argue that the field of computing education research needs to develop methods and tools to better measure students' learning over time and across the different programming languages they learn along the way. In presenting this position, we share data that shows students approach assessment problems differently depending on the programming language, even when the problems are conceptually isomorphic, and discuss some approaches for developing multilingual assessments of student learning over time.
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Programming Language Knowledge Transfer that Teachers Observe in their Classrooms
There has been significant progress in increasing the access to computing education for many K-12 students, including states adopting computer science (CS) standards and/or requiring CS courses. This includes the creation of block-based programming languages to make programming more accessible to younger students. Despite this progress, a new challenge has emerged: Students often struggle to transfer conceptual knowledge when transitioning to a new programming language (e.g., transitioning to a text-based programming after learning a block-based programming language). This poster presents the results of teacher interviews regarding the examples of knowledge transfer they observe in their classrooms. These interviews are part of an overarching project that aims to address the challenge of knowledge transfer between programming languages by developing a framework to support such transfer and deliver curricular supports that can be used to aid students’ productive knowledge transfer between programming languages.
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- Award ID(s):
- 2201209
- PAR ID:
- 10590336
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400704246
- Page Range / eLocation ID:
- 1690 to 1691
- Format(s):
- Medium: X
- Location:
- Portland OR USA
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3626253.3635570
