Scaffolding for integrated reflection

This paper presents some theoretical perspectives that might inform the design and development of information and communications technology (ICT) tools to support integrated (in-session) reflection and deep learning during e-learning. The role of why questioning provides the focus of discussion and is informed by the literature on critical thinking, sense-making, and reflective practice, as well as recent developments in knowledge management, computational linguistics and automated question generation. It is argued that there exists enormous scope for the development of ICT scaffolding targeted at supporting reflective practice during e-learning. The first generations of e-Portfolio tools provide some evidence for the significance of the benefits of integrating reflection into the design of ICT systems; however, following the review of a number of such systems, as well as a range of ICT applications and services designed to support e-learning, it is argued that the scope of implementation is limited.

The ascendancy of oracy in university courses: Implications for teachers and second language users

This chapter reports on a study of oracy in a first-year university Business course, with particular interest in the oracy demands for second language-using international students. The research is relevant at a time when Higher Education is characterised by the confluence of increased international enrolments, more dialogic teaching and learning, and imperatives for teamwork and collaboration. Data sources for the study included videotaped lectures and tutorials, course documents, student surveys, and an interview with the lecturer. The findings pointed to a complex, oracy-laden environment where interactive talk fulfilled high-stakes functions related to social inclusion, the co-construction of knowledge, and the accomplishment of assessment tasks. The salience of talk posed significant challenges for students negotiating these core functions in their second language. The study highlights the oracy demands in university courses and foregrounds the need for university teachers, curriculum writers and speaking test developers to recognise these demands and explicate them for the benefit of all students.

Their children's first educators : parents' views about child sexual abuse prevention education

In this descriptive focus group study, we investigated parents’ views about child sexual abuse prevention education at home and in schools. Focus groups were conducted with a sample of 30 Australian adults who identified as the parent or caregiver of a child/children aged 0–5 years. The study explored (1) parents’ knowledge about child sexual abuse prevention, (2) the child sexual abuse prevention messages they provided to their children and the topics they discussed, (3) their attitudes towards child sexual abuse prevention education in schools, and (4) their preferences for content. Data analysis provided seven key themes in these four areas: knowledge (the inadequacy of their own prevention education; and how important is stranger danger now?); messages (bodies, touching, and relationships; the role of protective adults; and parent–child communication); attitudes (voice and choice); and preferences (not the nitty gritty, just the basics). The findings may be useful in assisting school authorities and providers of child sexual abuse prevention programs to better understand parents’ contributions to child sexual abuse prevention education, and their perspectives in relation to provision of school-based prevention programs.

Non-compositional concepts and quantum tests

Compositionality is a frequently made assumption in linguistics, and yet many human subjects reveal highly non-compositional word associations when confronted with novel concept combinations. This article will show how a non-compositional account of concept combinations can be supplied by modelling them as interacting quantum systems.

The relationship between listening and other language skills in International English Language Testing System

Listening comprehension is the primary channel of learning a language. Yet of the four dominant macro-skills (listening, speaking, reading and writing), it is often difficult and inaccessible for second and foreign language learners due to its implicit process. The secondary skill, speaking, proceeds listening cognitively. Aural/oral skills precede the graphic skills, such as reading and writing, as they form the circle of language learning process. However, despite the significant relationship with other language skills, listening comprehension is treated lightly in the applied linguistics research. Half of our daily conversation and three quarters of classroom interaction are virtually devoted to listening comprehension. To examine the relationship of listening skill with other language skills, the outcome of 1800 Iranian participants undertaking International English Language Testing System (IELTS) in Tehran indicates the close correlation between listening comprehension and the overall language proficiency.

Is the unigram relevance model term independent? Classifying term dependencies in query expansion

This paper develops a framework for classifying term dependencies in query expansion with respect to the role terms play in structural linguistic associations. The framework is used to classify and compare the query expansion terms produced by the unigram and positional relevance models. As the unigram relevance model does not explicitly model term dependencies in its estimation process it is often thought to ignore dependencies that exist between words in natural language. The framework presented in this paper is underpinned by two types of linguistic association, namely syntagmatic and paradigmatic associations. It was found that syntagmatic associations were a more prevalent form of linguistic association used in query expansion. Paradoxically, it was the unigram model that exhibited this association more than the positional relevance model. This surprising finding has two potential implications for information retrieval models: (1) if linguistic associations underpin query expansion, then a probabilistic term dependence assumption based on position is inadequate for capturing them; (2) the unigram relevance model captures more term dependency information than its underlying theoretical model suggests, so its normative position as a baseline that ignores term dependencies should perhaps be reviewed.

A tensor encoding model for semantic processing

This paper develops and evaluates an enhanced corpus based approach for semantic processing. Corpus based models that build representations of words directly from text do not require pre-existing linguistic knowledge, and have demonstrated psychologically relevant performance on a number of cognitive tasks. However, they have been criticised in the past for not incorporating sufficient structural information. Using ideas underpinning recent attempts to overcome this weakness, we develop an enhanced tensor encoding model to build representations of word meaning for semantic processing. Our enhanced model demonstrates superior performance when compared to a robust baseline model on a number of semantic processing tasks.

Real, complex, and binary semantic vectors

This paper presents a combined structure for using real, complex, and binary valued vectors for semantic representation. The theory, implementation, and application of this structure are all significant. For the theory underlying quantum interaction, it is important to develop a core set of mathematical operators that describe systems of information, just as core mathematical operators in quantum mechanics are used to describe the behavior of physical systems. The system described in this paper enables us to compare more traditional quantum mechanical models (which use complex state vectors), alongside more generalized quantum models that use real and binary vectors. The implementation of such a system presents fundamental computational challenges. For large and sometimes sparse datasets, the demands on time and space are different for real, complex, and binary vectors. To accommodate these demands, the Semantic Vectors package has been carefully adapted and can now switch between different number types comparatively seamlessly. This paper describes the key abstract operations in our semantic vector models, and describes the implementations for real, complex, and binary vectors. We also discuss some of the key questions that arise in the field of quantum interaction and informatics, explaining how the wide availability of modelling options for different number fields will help to investigate some of these questions.

Semantic judgement of medical concepts : combining syntagmatic and paradigmatic information with the tensor encoding model

This paper outlines a novel approach for modelling semantic relationships within medical documents. Medical terminologies contain a rich source of semantic information critical to a number of techniques in medical informatics, including medical information retrieval. Recent research suggests that corpus-driven approaches are effective at automatically capturing semantic similarities between medical concepts, thus making them an attractive option for accessing semantic information. Most previous corpus-driven methods only considered syntagmatic associations. In this paper, we adapt a recent approach that explicitly models both syntagmatic and paradigmatic associations. We show that the implicit similarity between certain medical concepts can only be modelled using paradigmatic associations. In addition, the inclusion of both types of associations overcomes the sensitivity to the training corpus experienced by previous approaches, making our method both more effective and more robust. This finding may have implications for researchers in the area of medical information retrieval.

Critical theory and literacy

This handbook chapter explores the relationship between critical theory and seminal studies of literacy which investigate inequities in education. It identifies new research questions to explore the connections between literacy and power, but go beyond promises of emancipation.

Basic cognitive experiences and definitions in the Longman Dictionary of Contemporary English

This study applies theories of cognitive linguistics to the compilation of English learners’ dictionaries. Specifically, it employs the concepts of basic level categories and image schemas, two basic cognitive experiences, to examine the ‘definition proper’ of English dictionaries for foreign learners. In the study, the definition proper refers to the constituent part of a reference work that provides an explanation of the meanings of a word, phrase or term. This rationalization mainly consists of defining vocabulary, sense division and arrangement, as well as the means of defining (i.e. paraphrase, true definition, functional definition, and pictorial illustration). The aim of the study is to suggest ways of aligning the consultation and learning of definitions with dictionary users’ cognitive experiences. For this purpose, an analysis of the definition proper of the fourth edition of the Longman Dictionary of Contemporary English (LDOCE4) from the perspective of basic cognitive experiences has been undertaken. The study found that, generally, the lexicographic practices of LDOCE4 are consistent with theories of cognitive linguistics. However, there exist shortcomings that result from disregarding basic cognitive experiences.

Automatic query expansion : a structural linguistic perspective

A user’s query is considered to be an imprecise description of their information need. Automatic query expansion is the process of reformulating the original query with the goal of improving retrieval effectiveness. Many successful query expansion techniques ignore information about the dependencies that exist between words in natural language. However, more recent approaches have demonstrated that by explicitly modeling associations between terms significant improvements in retrieval effectiveness can be achieved over those that ignore these dependencies. State-of-the-art dependency-based approaches have been shown to primarily model syntagmatic associations. Syntagmatic associations infer a likelihood that two terms co-occur more often than by chance. However, structural linguistics relies on both syntagmatic and paradigmatic associations to deduce the meaning of a word. Given the success of dependency-based approaches and the reliance on word meanings in the query formulation process, we argue that modeling both syntagmatic and paradigmatic information in the query expansion process will improve retrieval effectiveness. This article develops and evaluates a new query expansion technique that is based on a formal, corpus-based model of word meaning that models syntagmatic and paradigmatic associations. We demonstrate that when sufficient statistical information exists, as in the case of longer queries, including paradigmatic information alone provides significant improvements in retrieval effectiveness across a wide variety of data sets. More generally, when our new query expansion approach is applied to large-scale web retrieval it demonstrates significant improvements in retrieval effectiveness over a strong baseline system, based on a commercial search engine.

Some extensions to representation and encoding of structure in models of distributional semantics

This thesis makes several contributions towards improved methods for encoding structure in computational models of word meaning. New methods are proposed and evaluated which address the requirement of being able to easily encode linguistic structural features within a computational representation while retaining the ability to scale to large volumes of textual data. Various methods are implemented and evaluated on a range of evaluation tasks to demonstrate the effectiveness of the proposed methods.