Search for: All records

Abstract This paper reports on the first iteration of the Computational Thinking Summer Institute, a month‐long programme in which high school teachers co‐designed computationally enhanced mathematics and science curricula with researchers. The co‐design process itself was a constructionist learning experience for teachers resulting in constructionist curricula to be used in their own classrooms. We present three case studies to illustrate different ways teachers and researchers divided the labour of co‐design and the implications of these different co‐design styles for teacher learning and classroom enactment. Specifically, some teachers programmed their own computational tools, while others helped to conceptualise them but left the construction to their co‐design partners. Results indicate that constructionist co‐design is a promising dual approach to curriculum and professional development but that sometimes these two goals are in tension. Most teachers gained considerable confidence and skills in computational thinking, but sometimes the pressure to finish curriculum development during the institute led teachers to leave construction of computational tools to their co‐design partners, limiting their own opportunities for computational learning. Practitioner notesWhat is already known about this topic?Computational tools can support constructionist science and math learning by making powerful ideas tangible.Supporting teachers to learn computational thinking and to use constructionist pedagogies is challenging.What this paper adds?Constructionist co‐design is a promising approach to simultaneously support curriculum development and professional development, but there are tensions to navigate in trying to accomplish both goals simultaneously.Implications for practice and/or policyDesigners of professional development should consider constructionist co‐design as an approach but should be aware of potential tensions and prepare for them. 

Teachers in K-12 science classrooms play a key role in helping their students engage in computational thinking (CT) activities that reflect authentic science practices. However, we know less about how to support teachers in integrating CT into their classrooms. This paper presents a case of one science teacher over three years as she participated in a Design Based Implementation Research project focused on integrating CT into science curriculum. We analyze her professional growth as a designer and instructor as she created and implemented three computationally-enriched science units with the support of our research team. Results suggest that she became more confident in her understanding of and ability, leading to greater integration of CT in the science units. Relationships with the research team and co-design experiences mediated this growth. Findings yield implications for how best to support teachers in collaborative curriculum design. 

Code-first learning entails the use of computer code to learn a concept, and creating computational models is one such effective method for learning about scientific phenomena. Many code-first learning approaches employ the visual block-based programming paradigm in order to be accessible to school children with no prior programming experience, providing them with high- level domain-specific code-blocks that encapsulate the underlying complex programming logic. However, even with the aid of visual clues and the benefit of simpler primitives like “forward” and “repeat,” many phenomena studied in classrooms such as the behavior of gas particles in Kinetic Molecular Theory (KMT) are challenging to describe in code. We hypothesized that code blocks designed from a phenomenological perspective to model the behavior of familiar objects and events would both promote students’ authoring of computational models and their ability to encode and test their beliefs within their models. We created these phenomenological blocks within a code-first gas particle sandbox and integrated it into a KMT lesson plan. Two high school teachers taught this curriculum to 121 students, from which we gathered and analyzed video footage from lesson activities and student focus groups. We found that the phenomenological blocks gave students the ability to start programming right away and to express their intuitive understanding of KMT through computational models. This exploratory study demonstrates the potential for phenomenological programming to broaden the application and accessibility of code-first computational modeling for learning scientific phenomena. 

Integrating computational thinking (CT) in the science classroom presents the opportunity to simultaneously broaden participation in computing, enhance science content learning, and engage students in authentic scientific practice. However, there is a lot more to learn on how teachers might integrate CT activities within their existing curricula. In this work, we describe a process of co-design with researchers and teachers to develop CT-infused science curricula. Specifically, we present a case study of one veteran physics teacher whose conception of CT during a professional development institute changed over time. We use this case study to explore how CT is perceived in physics instruction, a field that has a long history of computational learning opportunities. We also discuss how a co-design process led to the development of a lens through which to identify fruitful opportunities to integrate CT activities in physics curricula which we term computational transparency–purposefully revealing the inner workings of computational tools that students already use in the classroom. 

Next Generation Science Standards foreground science practices as important goals of science education. In this paper, we discuss the design of block-based modeling environments for learning experiences that ask students to actively explore complex systems via computer programming. Specifically, we discuss the implications of the design and selection of the types of blocks given to learners in these environments and how they may affect students’ thinking about the process of modeling and theorizing. We conclude with a discussion of some preliminary findings in this design based research to inform design principles for block-based programming of science phenomena as a medium for learning to build theory.