On learning context-free and context-sensitive languages

The long short-term memory (LSTM) is not the only neural network which learns a context sensitive language. Second-order sequential cascaded networks (SCNs) are able to induce means from a finite fragment of a context-sensitive language for processing strings outside the training set. The dynamical behavior of the SCN is qualitatively distinct from that observed in LSTM networks. Differences in performance and dynamics are discussed.

Communicating vegetation management science to land managers and other stakeholders

Science communication. including extension services. plays a key role in achieving sustainable native vegetation management. One of the pivotal aspects of the debate on sustainable vegetation management is the scientific information underpinning policy-making. In recent years. extension services have Shifted their focus from top-down technology transfer to bottom-up participation and empowerment. I here has also been a broadening of communication strategies to recognise the range of stakeholders involved in native vegetation management and to encompass environmental concerns. This paper examines the differences between government approaches to extension services to deliver policy and the need for effective communication to address broader science issues that underpin native vegetation management. The importance of knowing the learning styles of the stakeholders involved in native vegetation management is discussed at a time of increasing reliance on mass communication for information exchange and the importance of personal communication to achieve on-ground sustainable management. Critical factors for effective science-management communication are identified Such as: (i) undertaking scientific studies (research) with community involvement, acceptance and agreed understanding of project objectives (ii) realistic community consultation periods: (iii) matching communication channels with stakeholder needs; (iv) combining scientific with local knowledge in in holistic (biophysical and social) approach to understanding in issued and (v) regional partnerships. These communication factors are considered to be essential to implementing on-ground natural resource management strategics and actions, including those concerned with native vegetation management.

Input-driven Language Learning

Input-driven models provide an explicit and readily testable account of language learning. Although we share Ellis's view that the statistical structure of the linguistic environment is a crucial and, until recently, relatively neglected variable in language learning, we also recognize that the approach makes three assumptions about cognition and language learning that are not universally shared. The three assumptions concern (a) the language learner as an intuitive statistician, (b) the constraints on what constitute relevant surface cues, and (c) the redescription problem faced by any system that seeks to derive abstract grammatical relations from the frequency of co-occurring surface forms and functions. These are significant assumptions that must be established if input-driven models are to gain wider acceptance. We comment on these issues and briefly describe a distributed, instance-based approach that retains the key features of the input-driven account advocated by Ellis but that also addresses shortcomings of the current approaches.

Extending Learning Opportunities through a virtual faculty

This paper presents the notion of a virtual faculty as a viable alternative to extending and maintaining learner opportunities for students in regional universities or at universities where specialisations in which they are interested may not be offered. Staff from a number of Australian Universities participated in a CUTSD project to explore the viability of establishing a virtual faculty using videoconferencing as the medium of delivery. The success of this project was the result of close collaboration at a number of levels within the participating institutions and a willingness to explore effective approaches to teaching and learning for a videoconference environment.

Preparing students for the virtual organisation: an evaluation of learning with virtual learning technologies

The paper explores the development of learning behaviours in a virtual management course and the factors that impacted on this development. Data suggest that most teams experienced three kinds of learning behaviours – social, operational and content learning. We propose that the need for technical expertise and team participation will vary during these different stages of learning. Addressing the characteristics of these stages, we comment on the development of a ‘completion phase’ of team development. We argue that the extent to which teams demonstrate different learning stages has a significant impact on the development of on-line learning behaviours. Discussing these results, we suggest why different teams develop distinct learning behaviours, with accordant emphasis on teaching as a moderating and co ordinating role, despite current virtual team pedagogical expectations.

Implications of missed opportunities for learning and assessment in design and technology education

Supporting student learning can be difficult, especially within open-ended or loosely structured activities, often seen as valuable for promoting student autonomy in many curriculum areas and contexts. This paper reports an investigation into the experiences of three teachers who implemented design and technology education ideas in their primary school classrooms for the first time. The teachers did not capitalise upon many of the opportunities for scaffolding their students' learning within the open-ended activities they implemented. Limitations of the teachers' conceptual and procedural knowledge of design and technology were elements that influenced their early experiences. The study has implications for professional developers planning programs in newly introduced areas of the curriculum to support teachers in supporting learning within open-ended and loosely structured problem solving activities. (C) 2001 Elsevier Science Ltd. All rights reserved.

Exploring the role of market learning capability in competitive strategy

It has been argued that a firm's capacity to learn from its market is a source of both innovation and competitive advantage. However, past research has failed to conceptualize market-focused learning activity as a capability having the potential to contribute to competitive advantage. Prior innovation research has been biased toward technological innovation. However, there is evidence to suggest that both technological and non-technological innovations contribute to competitive advantage reflecting the need for a broader conceptualization of the innovation construct. Past research has also overlooked the critical role of entrepreneurship in the capability building process. Competitive advantage has been predominantly measured in terms of financial indicators of performance. In general, the literature reflects the need for comprehensive measures of organizational innovation and competitive advantage. This paper examines the role of market-focused learning capability in organizational innovation-based competitive strategy. The paper contributes to the strategic marketing theory by developing and refining measures of entrepreneurship, market-focused learning capability, organizational innovation and sustained competitive advantage, testing relationships among these constructs.

On-line writing: a link to learning in a teacher education program

This paper examines the use of on-line discussion as a medium for learning in a pre-service teacher education program. As part of an Education Studies course student teachers engaged in a discussion of issues related to technology and equity in schools. The design of the task and the subsequent analysis of the on-line text were part of a research project investigating whether and how communications technology can be used to integrate and extend the learning of teacher education students. The main argument developed in the paper is that through the on-line activity distinctive sets of writing practices were created. These practices enabled students to make connections between the often disparate parts of teacher education programs-theory and practice, campus and school, research and experience. (C) 2002 Elsevier Science Ltd. All rights reserved.

Making distance learning E.R.O.T.I.C.: Applying interpretation principles to distance learning

Distance learners are self-directed learners traditionally taught via study books, collections of readings, and exercises to test understanding of learning packages. Despite advances in e-Learning environments and computer-based teaching interfaces, distance learners still lack opportunities to participate in exercises and debates available to classroom learners, particularly through non-text based learning techniques. Effective distance teaching requires flexible learning opportunities. Using arguments developed in interpretation literature, we argue that effective distance learning must also be Entertaining, Relevant, Organised, Thematic, Involving and Creative—E.R.O.T.I.C. (after Ham, 1992). We discuss an experiment undertaken with distance learners at The University of Queensland Gatton Campus, where we initiated an E.R.O.T.I.C. external teaching package aimed at engaging distance learners but using multimedia, including but not limited to text-based learning tools. Student responses to non-text media were positive.

Learning the dynamics of embedded clauses

Recent work by Siegelmann has shown that the computational power of recurrent neural networks matches that of Turing Machines. One important implication is that complex language classes (infinite languages with embedded clauses) can be represented in neural networks. Proofs are based on a fractal encoding of states to simulate the memory and operations of stacks. In the present work, it is shown that similar stack-like dynamics can be learned in recurrent neural networks from simple sequence prediction tasks. Two main types of network solutions are found and described qualitatively as dynamical systems: damped oscillation and entangled spiraling around fixed points. The potential and limitations of each solution type are established in terms of generalization on two different context-free languages. Both solution types constitute novel stack implementations - generally in line with Siegelmann's theoretical work - which supply insights into how embedded structures of languages can be handled in analog hardware.