Developing computational thinking in the classroom: a framework

Computational thinking sits at the heart of the new statutory programme of study for Computing: “A high quality computing education equips pupils to use computational thinking and creativity to understand and change the world” (Department for Education, 2013, p. 188). This document aims to support teachers to teach computational thinking. It describes a framework that helps explain what computational thinking is, describes pedagogic approaches for teaching it and gives ways to assess it. Pupil progression with the previous ICT curriculum was often demonstrated through ‘how’ (for example, a software usage skill) or ‘what’ the pupil produced (for example, a poster). This was partly due to the needs of the business world for office skills. Such use of precious curriculum time however has several weaknesses. Firstly, the country’s economy depends on technological innovation not just on use of technology. Secondly, the pace of technology and organisational change is fast in that the ICT skills learnt are out of date before a pupil leaves school. Thirdly, technology invades all aspects of our life and the typically taught office practice is only a small part of technology use today

Teaching programming with computational and informational thinking

Computers are the dominant technology of the early 21st century: pretty well all aspects of economic, social and personal life are now unthinkable without them. In turn, computer hardware is controlled by software, that is, codes written in programming languages. Programming, the construction of software, is thus a fundamental activity, in which millions of people are engaged worldwide, and the teaching of programming is long established in international secondary and higher education. Yet, going on 70 years after the first computers were built, there is no well-established pedagogy for teaching programming. There has certainly been no shortage of approaches. However, these have often been driven by fashion, an enthusiastic amateurism or a wish to follow best industrial practice, which, while appropriate for mature professionals, is poorly suited to novice programmers. Much of the difficulty lies in the very close relationship between problem solving and programming. Once a problem is well characterised it is relatively straightforward to realise a solution in software. However, teaching problem solving is, if anything, less well understood than teaching programming. Problem solving seems to be a creative, holistic, dialectical, multi-dimensional, iterative process. While there are well established techniques for analysing problems, arbitrary problems cannot be solved by rote, by mechanically applying techniques in some prescribed linear order. Furthermore, historically, approaches to teaching programming have failed to account for this complexity in problem solving, focusing strongly on programming itself and, if at all, only partially and superficially exploring problem solving. Recently, an integrated approach to problem solving and programming called Computational Thinking (CT) (Wing, 2006) has gained considerable currency. CT has the enormous advantage over prior approaches of strongly emphasising problem solving and of making explicit core techniques. Nonetheless, there is still a tendency to view CT as prescriptive rather than creative, engendering scholastic arguments about the nature and status of CT techniques. Programming at heart is concerned with processing information but many accounts of CT emphasise processing over information rather than seeing then as intimately related. In this paper, while acknowledging and building on the strengths of CT, I argue that understanding the form and structure of information should be primary in any pedagogy of programming

Curriculum Guidelines for Undergraduate Programs in Data Science

The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program met for the purpose of composing guidelines for undergraduate programs in Data Science. The group consisted of 25 undergraduate faculty from a variety of institutions in the U.S., primarily from the disciplines of mathematics, statistics and computer science. These guidelines are meant to provide some structure for institutions planning for or revising a major in Data Science

Soft thought (in architecture and choreography)

This article is an introduction to and exploration of the concept of ‘soft thought’. What we want to propose through the definition of this concept is an aesthetic of digital code that does not necessarily presuppose a relation with the generative aspects of coding, nor with its sensorial perception and evaluation. Numbers do not have to produce something, and do not need to be transduced into colours and sounds, in order to be considered as aesthetic objects. Starting from this assumption, our main aim will be to reconnect the numerical aesthetic of code with a more ‘abstract’ kind of feeling, the feeling of numbers indirectly felt as conceptual contagions’, that are ‘conceptually felt but not directly sensed. The following pages will be dedicated to the explication and exemplification of this particular mode of feeling, and to its possible definition as ‘soft thought’

Pirate plunder: game-based computational thinking using scratch blocks

Policy makers worldwide argue that children should be taught how technology works, and that the ‘computational thinking’ skills developed through programming are useful in a wider context. This is causing an increased focus on computer science in primary and secondary education. Block-based programming tools, like Scratch, have become ubiquitous in primary education (5 to 11-years-old) throughout the UK. However, Scratch users often struggle to detect and correct ‘code smells’ (bad programming practices) such as duplicated blocks and large scripts, which can lead to programs that are difficult to understand. These ‘smells’ are caused by a lack of abstraction and decomposition in programs; skills that play a key role in computational thinking. In Scratch, repeats (loops), custom blocks (procedures) and clones (instances) can be used to correct these smells. Yet, custom blocks and clones are rarely taught to children under 11-years-old. We describe the design of a novel educational block-based programming game, Pirate Plunder, which aims to teach these skills to children aged 9-11. Players use Scratch blocks to navigate around a grid, collect items and interact with obstacles. Blocks are explained in ‘tutorials’; the player then completes a series of ‘challenges’ before attempting the next tutorial. A set of Scratch blocks, including repeats, custom blocks and clones, are introduced in a linear difficulty progression. There are two versions of Pirate Plunder; one that uses a debugging-first approach, where the player is given a program that is incomplete or incorrect, and one where each level begins with an empty program. The game design has been developed through iterative playtesting. The observations made during this process have influenced key design decisions such as Scratch integration, difficulty progression and reward system. In future, we will evaluate Pirate Plunder against a traditional Scratch curriculum and compare the debugging-first and non-debugging versions in a series of studies