G. Falloon

The University of Waikato (NEW ZEALAND)
The recent inclusion of computational skills in core curriculum by governments in the UK and Australia, has been linked to industry calls for schools to better equip young people with capabilities and dispositions aligned with needs of future high-tech industries and rapidly changing workplaces. This move has stimulated much interest in New Zealand, and while lacking any compulsory curriculum mandate, many teachers in K-12 classrooms are exploring the potential of coding tasks for developing computational skills as part of their mathematics, science and technology curricula.

Cuny, Snyder and Wing (2010) define computational thinking as “the thought processes involved in formulating problems and their solutions so that solutions are represented in a form that can be effectively carried out by an information-processing agent” (p.1). Typically at K-6 level, this has involved students in authoring basic code using applications such as Tynker, Kodable, Cargobot, Hopscotch and Lightbot to develop automated procedures to solve design or navigation challenges. At more advanced levels, apps such as Scratch, Scratch Jnr. and Gamepress allow students more latitude to create their own projects, collaborating and sharing these with others worldwide. The advent of 1:1 devices such as iPads makes undertaking such activities in conventional classrooms more viable. However while much activity is occurring in classrooms and beyond, limited research has been completed exploring the nature of thinking and the strategies students use when undertaking these activities.

This paper reports findings from a study that used a unique data capture app embedded in iPads to record 5&6 and 9&10 year old students while they used them for programming tasks. Using Studiocode video analysis software, data were analysed using a coding regime developed from Brennan and Resnick’s (2012) three dimensions of computational thinking (concepts, practices and perspectives), to learn more about how these students solved programming problems, and the sort of knowledge and skills they applied when doing so. Outcomes indicated significant variations in, and the complex nature of strategies students applied, and the powerful role of networking to help solve problems. They also suggest individual disposition and attitudinal elements are critical, and argues for these to be added as a fourth dimension when evaluating student learning within computational tasks. Practical advice for teachers considering integrating coding into their curriculum is also provided.