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Project Abstract

Programming Console
About the Project

Computational thinking (CT) is a powerful cognitive tool for solving problems, designing systems, and understanding human behaviour by drawing on concepts fundamental to computer science. It is helpful not only in maintaining competence in a technological society but also in supporting development in higher-order skills such as critical thinking, analysis, and scientific inquiry for the Science, Technology, Engineering, Mathematics (STEM) disciplines. Surrounding this, calls for incorporating CT into mathematics education are rapidly increasing. However, the mere presence of computers in the classroom does not ensure their effective use or quality education. Structural changes in the curriculum are needed to take full advantage of using CT to teach mathematics and problem solving.  

This study builds on the PI’s previously developed conception of “learning as Making” to envision a computationally enhanced mathematics curriculum—one that supports mathematical problem solving through digital Making (dM). Digital Making involves students’ active creation of both digital and tangible artefacts through block-based programming with physical input sensors and output devices. It promotes active learning and transforms mathematical problem solving beyond merely using formulae and performing arithmetic calculations procedurally. Rather, CT concepts and practices such as sequences, variable-naming, abstraction, algorithmic thinking, decomposing, and iterating are highlighted during problem-based dM activities, through which scientific inquiry, mathematical thinking, and engineering design can also be exhibited as integrated STEM learning. 

In this design-based study, a total of 20 lessons with problem-based dM tasks will be developed with content appropriate to senior primary and junior secondary mathematics curricula. These lessons will be implemented monthly to roughly 100 students in two primary and two secondary schools in Hong Kong longitudinally over two academic years. Data collection includes: (1) students’ digital artefacts and dM processes collected via code files and screen-capturing, (2) focus group interview and artefact-based interview data captured via video-recording. The study will adopt user analysis, thematic analysis, and case studies to delve into students’ acquired CT concepts, developed problem-solving practices, and formed computational perspectives in the course of the designed curriculum.  


This study will inform the “big picture” of how using computers might fundamentally change mathematics learning, with an emphasis on mathematical problem solving (and more generally, STEM education). Findings will contribute to extending academic and professional knowledge about learning mathematics with computational tools, in response to CT and Making as a social movement. Ultimately, it will provide evidence-based directions of enhancing CT as a new literacy and problem solving as a global competence in school settings. 

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