Learning to communicate computationally with Flip: a bi-modal programming language for game creation

Teaching basic computational concepts and skills to school children is currently a curricular focus in many countries. Running parallel to this trend are advances in programming environments and teaching methods which aim to make computer science more accessible, and more motivating. In this paper, we describe the design and evaluation of Flip, a programming language that aims to help 11–15 year olds develop computational skills through creating their own 3D role-playing games. Flip has two main components: 1) a visual language (based on an interlocking blocks design common to many current visual languages), and 2) a dynamically updating natural language version of the script under creation. This programming-language/natural-language pairing is a unique feature of Flip, designed to allow learners to draw upon their familiarity with natural language to “decode the code”. Flip aims to support young people in developing an understanding of computational concepts as well as the skills to use and communicate these concepts effectively. This paper investigates the extent to which Flip can be used by young people to create working scripts, and examines improvements in their expression of computational rules and concepts after using the tool. We provide an overview of the design and implementation of Flip before describing an evaluation study carried out with 12–13 year olds in a naturalistic setting. Over the course of 8 weeks, the majority of students were able to use Flip to write small programs to bring about interactive behaviours in the games they created. Furthermore, there was a significant improvement in their computational communication after using Flip (as measured by a pre/post-test). An additional finding was that girls wrote more, and more complex, scripts than did boys, and there was a trend for girls to show greater learning gains relative to the boys

Review of ‘Philosophy in a New Century’ by John Searle (2008) (review revised 2019)

Before commenting on the book, I offer comments on Wittgenstein and Searle and the logical structure of rationality. The essays here are mostly already published during the last decade (though some have been updated), along with one unpublished item, and nothing here will come as a surprise to those who have kept up with his work. Like W, he is regarded as the best standup philosopher of his time and his written work is solid as a rock and groundbreaking throughout. However, his failure to take the later W seriously enough leads to some mistakes and confusions. Just a few examples: on p7 he twice notes that our certainty about basic facts is due to the overwhelming weight of reason supporting our claims, but W showed definitively in ‘On Certainty’ that there is no possibility of doubting the true-only axiomatic structure of our System 1 perceptions, memories and thoughts, since it is itself the basis for judgment and cannot itself be judged. In the first sentence on p8 he tells us that certainty is revisable, but this kind of ‘certainty’, which we might call Certainty2, is the result of extending our axiomatic and nonrevisable certainty (Certainty1) via experience and is utterly different as it is propositional (true or false). This is of course a classic example of the “battle against the bewitchment of our intelligence by language” which W demonstrated over and over again. One word- two (or many) distinct uses. His last chapter “The Unity of the Proposition” (previously unpublished) would also benefit greatly from reading W’s “On Certainty” or DMS’s two books on OC (see my reviews) as they make clear the difference between true only sentences describing S1 and true or false propositions describing S2. This strikes me as a far superior approach to S’s taking S1 perceptions as propositional since they only become T or F after one begins thinking about them in S2. However, his point that propositions permit statements of actual or potential truth and falsity, of past and future and fantasy, and thus provide a huge advance over pre or protolinguistic society, is cogent. As he states it “A proposition is anything at all that can determine a condition of satisfaction…and a condition of satisfaction… is that such and such is the case.” Or, one needs to add, that might be or might have been or might be imagined to be the case. Overall, PNC is a good summary of the many substantial advances over Wittgenstein resulting from S’s half century of work, but in my view, W still is unequaled once you grasp what he is saying. Ideally, they should be read together: Searle for the clear coherent prose and generalizations, illustrated with W’s perspicacious examples and brilliant aphorisms. If I were much younger I would write a book doing exactly that. Those wishing a comprehensive up to date framework for human behavior from the modern two systems view may consult my book ‘The Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searle’ 2nd ed (2019). Those interested in more of my writings may see ‘Talking Monkeys--Philosophy, Psychology, Science, Religion and Politics on a Doomed Planet--Articles and Reviews 2006-2019 3rd ed (2019), The Logical Structure of Human Behavior (2019), and Suicidal Utopian Delusions in the 21st Century 4th ed (2019

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

Epistemic virtues, metavirtues, and computational complexity

I argue that considerations about computational complexity show that all finite agents need characteristics like those that have been called epistemic virtues. The necessity of these virtues follows in part from the nonexistence of shortcuts, or efficient ways of finding shortcuts, to cognitively expensive routines. It follows that agents must possess the capacities – metavirtues –of developing in advance the cognitive virtues they will need when time and memory are at a premium

Developing Learning Trajectory For Enhancing Students’ Relational Thinking

Algebra is part of Mathematics learning in Indonesian curriculum. It takes one half of the teaching hours in senior high school, and one third in junior high school. However, the learning trajectory of Algebra needs to be improved because teachers teach computational thinking by applying paper-and-pencil strategy combining with the concepts-operations-example-drilling approach. Mathematics textbooks do not give enough guidance for teachers to conduct good activities in the classroom to promote algebraic thinking especially in the primary schools. To reach Indonesian Mathematics teaching goals, teachers should develop learning trajectories based on pedagogical and theoretical backgrounds. Teachers need to have knowledge of student’s developmental progressions and understanding of mathematics concepts and students’ thinking. Research shows that teachers’ knowledge of student’s mathematical development is related to their students’ achievement. In fostering a greater emphasis on algebraic thinking, teachers and textbooks need to work more closely together to develop a clearer learning trajectory. Having this algebraic thinking, students developed not only their own character of learning and thinking but also their attitude, attention and discipline. Key Words: Learning Trajectory, Relational Thinkin

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

ScratchMaths: evaluation report and executive summary

Since 2014, computing has been part of the primary curriculum. ‘Scratch’ is frequently used by schools, and the EEF funded this trial to test whether the platform could be used to improve pupils’ computational thinking skills, and whether this in turn could have a positive impact on Key Stage 2 maths attainment. Good computational thinking skills mean pupils can use problem solving methods that involve expressing problems and their solutions in ways that a computer could execute – for example, recognising patterns. Previous research has shown that pupils with better computational thinking skills do better in maths. The study found a positive impact on computational thinking skills at the end of Year 5 – particularly for pupils who have ever been eligible for free school meals. However, there was no evidence of an impact on Key Stage 2 maths attainment when pupils were tested at the end of Year 6. Many of the schools in the trial did not fully implement ScratchMaths, particularly in Year 6, where teachers expressed concerns about the pressure of Key Stage 2 SATs. But there was no evidence that schools which did implement the programme had better maths results. Schools may be interested in ScratchMaths as an affordable way to cover aspects of the primary computing curriculum in maths lessons without any adverse effect on core maths outcomes. This trial, however, did not provide evidence that ScratchMaths is an effective way to improve maths outcomes

The "Artificial Mathematician" Objection: Exploring the (Im)possibility of Automating Mathematical Understanding

Reuben Hersh confided to us that, about forty years ago, the late Paul Cohen predicted to him that at some unspecified point in the future, mathematicians would be replaced by computers. Rather than focus on computers replacing mathematicians, however, our aim is to consider the (im)possibility of human mathematicians being joined by “artificial mathematicians” in the proving practice—not just as a method of inquiry but as a fellow inquirer