Computer Science

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.

The rapid expansion of K-12 CS education has made it critical to support CS teachers, many of whom are new to teaching CS, with the necessary resources and training to strengthen their understanding of CS concepts and how to effectively teach CS. CS teachers are often tasked with teaching different curricula using different programming languages in different grades or during different school years, and tend to receive different professional development (PD) for each curriculum they are required to teach.

We explored how preservice teachers in a middle school science methods course learned and applied computational thinking (CT) concepts and activities during a month-long
intervention. In the intervention, preservice teachers learned about CT concepts through an hour-long lecture in their methods class, practiced a computing-integration activity for

Teaching about wave structure and function is a critical element of any physical science curriculum and supported by Next Generation Science Standards (NGSS) PS4: Waves and Their Applications in Technologies for Information Transfer. Often, instruction focused on these concepts involves identifying and describing several aspects of wave structure, including amplitude, frequency, and wavelength. To support students’ learning of these ideas, teachers often rely on developing graphic models of a wave with students identifying different aspects of wave structure.

Background and Context
Students’ self-efficacy toward computing affect their participation in related tasks and courses. Self-efficacy is likely influenced by students’ initial experiences and exposure to computer science (CS) activities. Moreover, student interest in a subject likely informs their ability to effectively regulate their learning in that domain. One way to enhance interest in CS is through using collaborative pair programming.

Background and Context
Students’ self-efficacy toward computing affect their participation in related tasks and courses. Self-efficacy is likely influenced by students’ initial experiences and exposure to computer science (CS) activities. Moreover, student interest in a subject likely informs their ability to effectively regulate their learning in that domain. One way to enhance interest in CS is through using collaborative pair programming.

The COVID-19 pandemic shifted many U.S. schools from in-person to remote instruction. While collaborative CS activities had become increasingly common in classrooms prior to the pandemic, the sudden shift to remote learning presented challenges for both teachers and students in implementing and supporting collaborative learning. Though some research on remote collaborative CS learning has been conducted with adult learners, less has been done with younger learners such as elementary school students.