Doubled up all over again: borrowing, sound change and reduplication in Iwaidja

This article examines the interactions between reduplication, sound change, and borrowing, as played out in the Iwaidja language of Cobourg Peninsula, Arnhem Land, in Northern Australia, a non-Pama-Nyungan language of the Iwaidjan family. While Iwaidja traditionally makes use of (various types of) right-reduplication, contact with two other left-reduplicating languages-one Australian (Bininj Gun-wok) and one Austronesian (Makassarese)-has led to the introduction of several (non-productive) left-reduplicating patterns. At the same time as these new patterns have been entering the language, the cumulative effect of sweeping sound changes within Iwaidja has complicated the transparency of reduplicative outputs. This has left the language with an extremely varied and complicated set of reduplication types, for some of which the analysis is no longer synchronically recoverable by children

Designing a programming-based approach for modelling scientific phenomena

We describe an iteratively designed sequence of activities involving the modelling of 1- dimensional collisions between moving objects based on programming in ToonTalk. Students aged 13-14 in two settings (London and Cyprus) investigated a number of collision situations, classified into six classes based on the relative velocities and masses of the colliding objects. We describe iterations of the system in which students engaged in a repeating cycle of activity for each collision class: prediction of object behaviour from given collision conditions, observation of a relevant video clip, building a model to represent the phenomena, testing, validating and refining their model, and publishing it – together with comments – on our web-based collaboration system, WebReports. Students were encouraged to consider the limitations of their current model, with the aim that they would eventually appreciate the benefit of constructing a general model that would work for all collision classes, rather than a different model for each class. We describe how our intention to engage students with the underlying concepts of conservation, closed systems and system states was instantiated in the activity design, and how the modelling activities afforded an alternative representational framework to traditional algebraic description

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

Unsupervised Neural Machine Translation with SMT as Posterior Regularization

Without real bilingual corpus available, unsupervised Neural Machine Translation (NMT) typically requires pseudo parallel data generated with the back-translation method for the model training. However, due to weak supervision, the pseudo data inevitably contain noises and errors that will be accumulated and reinforced in the subsequent training process, leading to bad translation performance. To address this issue, we introduce phrase based Statistic Machine Translation (SMT) models which are robust to noisy data, as posterior regularizations to guide the training of unsupervised NMT models in the iterative back-translation process. Our method starts from SMT models built with pre-trained language models and word-level translation tables inferred from cross-lingual embeddings. Then SMT and NMT models are optimized jointly and boost each other incrementally in a unified EM framework. In this way, (1) the negative effect caused by errors in the iterative back-translation process can be alleviated timely by SMT filtering noises from its phrase tables; meanwhile, (2) NMT can compensate for the deficiency of fluency inherent in SMT. Experiments conducted on en-fr and en-de translation tasks show that our method outperforms the strong baseline and achieves new state-of-the-art unsupervised machine translation performance.Comment: To be presented at AAAI 2019; 9 pages, 4 figure