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Rich classroom discussion, or discourse, has long been a recommended pedagogical practice in K-12 math and science education. Research shows that discourse is beneficial for all learners, but especially for English learners and minoritized students in STEM. Discourse helps develop students' agency, academic language, and conceptual understanding. Some K-12 computer science (CS) curricula incorporate student discourse, but we believe it is under-used. In this paper, we review how discourse helps students learn, discuss the use of discourse in CS and math education, share ideas for promoting discourse in CS classrooms, and call on curriculum developers, teacher professional learning providers, and researchers to support the increased use of discourse in K-12 CS education. 

Data science education can help broaden participation in computer science (CS) because it provides rich, authentic contexts for students to apply their computing knowledge. Data literacy, particularly among underrepresented students, is critical to everyone in this increasingly digital world. However, the integration of data science into K-12 schools is nascent, and the pedagogical training of CS teachers in data science remains limited. Our research-practice partnership modified an existing data science unit to include two pedagogical techniques known to support minoritized students: rich classroom discourse and personally-relevant problem-solving. This paper describes the iterative design process we used to revise and pilot this new data science unit. 

Decades of motivation research have yielded a set of Motivation Design Principles (MDPs) that can be leveraged to support the development of student motivation and engagement in the classroom. This article addresses the translation of these guiding principles to teacher professional learning and subsequently, classroom practice. Drawing from published literature, as well as the experiences of a co-design team of motivation and science education researchers and middle school science teachers, we address the landscape of decision points for designing and implementing professional learning focused on supporting middle school students’ motivation in science. We identify 3 key decision points: (1) the extent to which professional learning should focus on general principles or specific practices; (2) the appropriate level(s) for translation of the MDPs into practice; and (3) the creation of opportunities for teacher reflection and self-assessment of their practice on student motivation and engagement.