A Learning Analytics Approach to Monitoring the Quality of Online One-to-one Tutoring

One-to-one online tutoring provided by human tutors can improve students’ learning outcomes. However, monitoring the quality of such tutoring is a significant challenge. In this paper, we propose a learning analytics approach for monitoring online one-to-one tutoring quality. The approach analyses teacher behaviours and classifies tutoring sessions into those that are effective and those that are not effective. More specifically, we use sequential behaviour pattern mining to analyse tutoring sessions using the CM-SPAM algorithm and classify tutoring sessions into effective and less effective using the J-48 and JRIP decision tree classifiers. To show the feasibility of the approach, we analysed data from 2250 minutes of online one-to-one primary Maths tutoring sessions with 44 tutors from 8 schools. The results showed that the approach can classify tutors’ effectiveness with high accuracy (F measures of 0.89 and 0.98 were achieved). The results also showed that effective tutors present significantly more frequent hint provision and proactive planning behaviours than their less effective colleagues in these online one-to-one sessions. Furthermore, effective tutors sequence their monitoring actions with appropriate pauses and initiations of students’ self-correction behaviours. We conclude that the proposed approach is feasible to monitor the quality of online one-to-one primary Maths tutoring sessions.

A Path Construction Algorithm for Translation Validation Using PRES+ Models

Multi-core and multi-processor architectures have predominated the domain of embedded systems permitting easy mapping of concurrent applications to such architectures. The programs, in general, are subjected to significant optimizing and parallelizing transformations, automated and also human guided, before being mapped to an architecture. Modelling parallel behaviour and formally verifying that their functionality is preserved during synthesis are challenging tasks. Untimed PRES+ models are found to be suitable for the specification of parallel behaviour. Path cover oriented equivalence checking methods have been found to be quite effective for sequential behaviour. Path construction for parallel behaviour, however, is significantly more complex than that for sequential behaviour due to all possible interleavings of the parallel operations. Identification of the path covers depends upon choosing appropriate cut-points. In this paper, the need for introducing cut-points dynamically has been underlined and a mechanism to achieve this task is proposed. Details on how to construct a path cover using dynamic cut-points is presented.

Variation as a cognitive device

In Languages for Specific Purposes (LSPs), variation and term formation are often seen as related phenomena, variation being interpreted as a sign of neology. In scientific discourse though, variation can play specific roles, thereby giving a different dimension to neology as a linguistic process than generally implied in terminological studies. The well-known referential function, consisting of creating new designations for naming new concepts, can be set aside in scientific texts to create space for what we define as the cognitive function: a situation where a scientist purposefully employs term variation as a means for theorising and better explaining a given concept. We argue that Halliday’s “grammatical metaphor” and “given-new” information theory provide an interesting background for understanding scientific term formation processes, and the ensuing issue of terminological variation. Consequently, in this article, we try to place the phenomenon of neology and of terminological variation within the framework of discourse analysis, by devising a method for probing sequential behaviour of terminological variants across text sections. Additionally, this study aims to improve building lexical resources within the ARTES terminological and phraseological multilingual database project, which serves as a support for developing lexicographical and translational skills in students in specialised translation.

A simple explanation for the evolution of complex song syntax in Bengalese finches

The songs of Bengalese finches ( Lonchura striata var. domestica ) have complex syntax and provide an opportunity to investigate how complex sequential behaviour emerges via the evolutionary process. In this study, we suggest that a simple mechanism, i.e. many-to-one mapping from internal states onto syllables, may underlie the emergence of apparent complex syllable sequences that have higher order history dependencies. We analysed the songs of Bengalese finches and of their wild ancestor, the white-rumped munia ( L. striata ), whose songs are more stereotypical and simpler compared with those of Bengalese finches. The many-to-one mapping mechanism sufficiently accounted for the differences in the complexity of song syllable sequences of these two strains.

Multilevel structure in behaviour and in the brain: a model of Fuster's hierarchy

A basic question, intimately tied to the problem of action selection, is that of how actions are assembled into organized sequences. Theories of routine sequential behaviour have long acknowledged that it must rely not only on environmental cues but also on some internal representation of temporal or task context. It is assumed, in most theories, that such internal representations must be organized into a strict hierarchy, mirroring the hierarchical structure of naturalistic sequential behaviour. This article reviews an alternative computational account, which asserts that the representations underlying naturalistic sequential behaviour need not, and arguably cannot, assume a strictly hierarchical form. One apparent liability of this theory is that it seems to contradict neuroscientific evidence indicating that different levels of sequential structure in behaviour are represented at different levels in a hierarchy of cortical areas. New simulations, reported here, show not only that the original computational account can be reconciled with this alignment between behavioural and neural organization, but also that it gives rise to a novel explanation for how this alignment might develop through learning.