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Pedagogical content knowledge (PCK) is specialized knowledge necessary to teach a subject. PCK integrates subject-matter content knowledge with knowledge of students and of teaching strategies so that teachers can perform the daily tasks of teaching. Studies in mathematics education have found correlations between measures of PCK and student learning. Finding robust, scalable ways for developing and measuring computer science (CS) teachers’ PCK is particularly important in CS education in the United States, given the lack of formal CS teacher preparation programs and certifications. However, measuring pedagogical content knowledge is a challenge for all subject areas. It can be difficult to write assessment items that elicit the different aspects of PCK and there are often multiple appropriate pedagogical choices in any given teaching scenario. In this paper, we describe a framework and pilot data from a questionnaire intended to elicit PCK from teachers of high school introductory CS courses and we propose future directions for this work.
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Design considerations for a middle school computer science pedagogical content knowledge instrument.
K-12 Computer Science (CS) education is developing rapidly but still lacks a comprehensive measure for CS teachers’ pedagogical content knowledge (PCK). We respond to this need by describing the design of a CS-PCK instrument for ‘Algorithms and Programming’ that measures three broad constructs: (a) teachers’ understanding of standards and standards alignment, (b) teachers’ formative assessment practices, and (c) teachers’ self-efficacy for teaching and assessing CS.
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- Award ID(s):
- 2010591
- PAR ID:
- 10410027
- Publisher / Repository:
- International Society of the learning Sciences, ICLS 2022 Proceedings
- Date Published:
- Journal Name:
- 16th International Conference of the Learning Sciences (ICLS) – Proceedings
- Page Range / eLocation ID:
- 2176-2177
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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