A conceptual model of personalized virtual learning environments

The Virtual Learning Environment (VLE) is one of the fastest growing areas in educational technology research and development. In order to achieve learning effectiveness, ideal VLEs should be able to identify learning needs and customize solutions, with or without an instructor to supplement instruction. They are called Personalized VLEs (PVLEs). In order to achieve PVLEs success, comprehensive conceptual models corresponding to PVLEs are essential. Such conceptual modeling development is important because it facilitates early detection and correction of system development errors. Therefore, in order to capture the PVLEs knowledge explicitly, this paper focuses on the development of conceptual models for PVLEs, including models of knowledge primitives in terms of learner, curriculum, and situational models, models of VLEs in general pedagogical bases, and particularly, the definition of the ontology of PVLEs on the constructivist pedagogical principle. Based on those comprehensive conceptual models, a prototyped multiagent-based PVLE has been implemented. A field experiment was conducted to investigate the learning achievements by comparing personalized and non-personalized systems. The result indicates that the PVLE we developed under our comprehensive ontology successfully provides significant learning achievements. These comprehensive models also provide a solid knowledge representation framework for PVLEs development practice, guiding the analysis, design, and development of PVLEs. (c) 2005 Elsevier Ltd. All rights reserved.

Virtual learning communities beyond the classroom: perceptions of tertiary Chinese language and non-language learners

As class contact times are reduced as a result of fiscal restraints in the modern tertiary sector, language instructors are placed in the position of having to find new ways to provide experience and continuity in language learning. Extending 'learning communities'—sites of learner knowledge exchange, exposure to diverse learning styles and strategies, and mutual support—beyond the classroom is one solution to maintaining successful linguistic competencies amongst learners. This, however, can conflict with the diverse extra-curricular commitments faced by tertiary students. The flexibility of web-based learning platforms provides one means of overcoming these obstacles. This study investigates learner perceptions of the use of the WebCT platform's computer medicated communication (CMC) tools as a means of extending the community of learning in tertiary Chinese language and non-language courses. Learner responses to Likert and open-ended questionnaires show that flexibility and reduction of negative affect are seen as significant benefits to 'virtual' interaction and communication, although responses are notably stronger in the non-language compared with the language cohort. While both learner cohorts acknowledge positive learning outcomes, CMC is not seen to consistently further interpersonal rapport beyond that established in the classroom. Maintaining a balance between web-based and classroom learning emerges as a concern, especially amongst language learners. [Author abstract, ed]

A sociocultural analysis of language learning: New forms of literacy practices in a language and culture awareness programme

This paper reports on a sociocultural study conducted in a Catholic primary school in the Australian outback and provides insights into how policy related to Languages Other Than English (LOTE) programmes is implemented in a specific location and interwoven within the literacy practices of children, parents and teachers. A case study that tracked a Year Four student's learning and development during a Language and Culture Awareness Programme is discussed within a discourse of cultural and linguistic practices. Significant aspects of the student's learning related to a phenomenon called multi-tiered scaffolding temporarily disrupted the established literacy practices in the school community. Implications of the research for second-language teaching and learning in Australian primary schools are elaborated.

Learning, odour preference and flower foraging in moths

Floral volatiles play a major role in plant-insect communication. We examined the influence of two volatiles, phenylacetaldehyde and a-pinene, on the innate and learnt foraging behaviour of the moth Helicoverpa armigera. In dual-choice wind tunnel tests, adult moths flew upwind towards both volatiles, with a preference for phenylacetaldehyde. When exposure to either of these volatiles was paired with a feeding stimulus (sucrose), all moths preferred the learnt odour in the preference test. This change in preference was not seen when moths were exposed to the odour without a feeding stimulus. The learnt preference for the odour was reduced when moths were left unfed for 24 h before the preference test. We tested whether moths could discriminate between flowers that differed in a single volatile component. Moths were trained to feed on flowers that were odour-enhanced using either phenylacetaldehyde or a-pinene. Choice tests were then carried out in an outdoor flight cage, using flowers enhanced with either volatile. Moths showed a significant preference for the flower type on which they were trained. Moths that were conditioned on flowers that were not odour-enhanced showed no preference for either of the odour-enhanced flower types. The results imply that moths may be discriminating among odour profiles of individual flowers from the same species. We discuss this behaviour within the context of nectar foraging in moths and odour signalling by flowering plants.

Learning of foraging skills by fish

This chapter outlines the relationships between a number of key factors that influence learning and memory, and illustrates them by reference to studies on the foraging behaviour of fish. Learning can lead to significant improvements in foraging performance in only a few exposures, and at least some fish species are capable of adjusting their foraging strategy as patterns of patch profitability change. There is also evidence that the memory window for prey varies between fish species, and that this may be a function of environmental predictability. Convergence between behavioural ecology and comparative psychology offers promise in terms of developing more mechanistically realistic foraging models and explaining apparently 'suboptimal' patterns of behaviour. Foraging decisions involve the interplay between several distinct systems of learning and memory, including those that relate to habitat, food patches, prey types, conspecifics and predators. Fish biologists, therefore, face an interesting challenge in developing integrated accounts of fish foraging that explain how cognitive sophistication can help individual animals to deal with the complexity of the ecological context.

From a Vicious Circle of Anxiety to a Virtuous Circle of Learning: Experience of Teaching to a Heterogenous Clientele

A considerable body of literature suggests that significant psychological barrier and anxiety characterize the teaching and learning process in statistics. This study investigates the incidence of statistics anxiety, the extent to which it can be overcome and the factors that contribute to the process of overcoming it. Self-study and overall teaching quality, amongst others, significantly contributed to this outcome. This study identifies factors contributing to overall teaching quality. The teaching and learning process typified a highly effective communication mechanism based on an appropriate diagnosis of individual needs. This cumulative change resulted from circular causation. It is argued that given appropriate conditions the vicious circle of anxiety can be transformed into a virtuous circle of learning.

System for foreign exchange trading using genetic algorithms and reinforcement learning

Foreign exchange trading has emerged recently as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process will be very helpful. A major issue for traders in the deregulated Foreign Exchange Market is when to sell and when to buy a particular currency in order to maximize profit. This paper presents novel trading strategies based on the machine learning methods of genetic algorithms and reinforcement learning.

Transient prenatal vitamin D deficiency is associated with subtle alterations in learning and memory functions in adult rats

Based on clues from epidemiology, low prenatal vitamin D has been proposed as a candidate risk factor for schizophrenia. Recent animal experiments have demonstrated that transient prenatal vitamin D deficiency is associated with persistent alterations in brain morphology and neurotrophin expression. In order to explore the utility of the vitamin D animal model of schizophrenia, we examined different types of learning and memory in adult rats exposed to transient prenatal vitamin D deficiency. Compared to control animals, the prenatally deplete animals had a significant impairment of latent inhibition, a feature often associated with schizophrenia. In addition, the deplete group was (a) significantly impaired on hole board habituation and (b) significantly better at maintaining previously learnt rules of brightness discrimination in a Y-chamber. In contrast, the prenatally deplete animals showed no impairment on the spatial learning task in the radial maze, nor on two-way active avoidance learning in the shuttle-box. The results indicate that transient prenatal vitamin D depletion in the rat is associated with subtle and discrete alterations in learning and memory. The behavioural phenotype associated with this animal model may provide insights into the neurobiological correlates of the cognitive impairments of schizophrenia. (c) 2005 Elsevier B.V. All rights reserved.

A comparison of responses to group learning between first-year Asian and first-year Australian veterinary science students

Introduction - Group learning has been used to enhance deep (long-term) learning and promote life skills, such as decision making, communication, and interpersonal skills. However, with increasing multiculturalism in higher education, there is little information available as to the acceptance of this form of learning by Asian students or as to its value to them. Methodology - Group-learning projects, incorporating a seminar presentation, were used in first-year veterinary anatomical science classes over two consecutive years (2003 and 2004) at the School of Veterinary Science, University of Queensland. Responses of Australian and Asian students to survey forms evaluating the learning experience were analyzed and compared. Results - All students responded positively to the group learning, indicating that it was a useful learning experience and a great method for meeting colleagues. There were no significant differences between Asian and Australian students in overall responses to the survey evaluating the learning experience, except where Asian students responded significantly higher than Australian students in identifying specific skills that needed improving. Conclusions - Group learning can be successfully used in multicultural teaching to enhance deep learning. This form of learning helps to remove cultural barriers and establish a platform for continued successful group learning throughout the program.

An Incremental EM-based Learning Approach for On-Line Prediction of Hospital Resource Utilization

Objective: Inpatient length of stay (LOS) is an important measure of hospital activity, health care resource consumption, and patient acuity. This research work aims at developing an incremental expectation maximization (EM) based learning approach on mixture of experts (ME) system for on-line prediction of LOS. The use of a batchmode learning process in most existing artificial neural networks to predict LOS is unrealistic, as the data become available over time and their pattern change dynamically. In contrast, an on-line process is capable of providing an output whenever a new datum becomes available. This on-the-spot information is therefore more useful and practical for making decisions, especially when one deals with a tremendous amount of data. Methods and material: The proposed approach is illustrated using a real example of gastroenteritis LOS data. The data set was extracted from a retrospective cohort study on all infants born in 1995-1997 and their subsequent admissions for gastroenteritis. The total number of admissions in this data set was n = 692. Linked hospitalization records of the cohort were retrieved retrospectively to derive the outcome measure, patient demographics, and associated co-morbidities information. A comparative study of the incremental learning and the batch-mode learning algorithms is considered. The performances of the learning algorithms are compared based on the mean absolute difference (MAD) between the predictions and the actual LOS, and the proportion of predictions with MAD < 1 day (Prop(MAD < 1)). The significance of the comparison is assessed through a regression analysis. Results: The incremental learning algorithm provides better on-line prediction of LOS when the system has gained sufficient training from more examples (MAD = 1.77 days and Prop(MAD < 1) = 54.3%), compared to that using the batch-mode learning. The regression analysis indicates a significant decrease of MAD (p-value = 0.063) and a significant (p-value = 0.044) increase of Prop(MAD

High performance sport coaching: Institutes of sport as sites for learning

There has been a marked increase in the number of government-funded, high performance institutes and academies of sport within Australia. Given that these organisations employ significant numbers of full-time performance sport coaches, they may be accurately characterised as workplaces. Performance sport coaches have underscored the importance of experience in developing their coaching skill. However, despite wide acceptance of the view that learning occurs everywhere but to different extents and with different efficiency, and the acknowledgement of current national coach education programs as insufficient, no sport coaching research has focused specifically on sport workplaces as sites for learning. This paper will review the current nature of coach development with a view to examining the interaction between what the workplace (institute/academy) affords the individual and the personal agency of the individual (high performance sports coaches).

Machine learning for matching astronomy catalogues

An emerging issue in the field of astronomy is the integration, management and utilization of databases from around the world to facilitate scientific discovery. In this paper, we investigate application of the machine learning techniques of support vector machines and neural networks to the problem of amalgamating catalogues of galaxies as objects from two disparate data sources: radio and optical. Formulating this as a classification problem presents several challenges, including dealing with a highly unbalanced data set. Unlike the conventional approach to the problem (which is based on a likelihood ratio) machine learning does not require density estimation and is shown here to provide a significant improvement in performance. We also report some experiments that explore the importance of the radio and optical data features for the matching problem.

The judicious utilization of new technologies through authentic learning in higher education: A case study

Though technology holds significant promise for enhanced teaching and learning it is unlikely to meet this promise without a principled approach to course design. There is burgeoning discourse about the use of technological tools and models in higher education, but much of the discussion is fixed upon distance learning or technology based courses. This paper will develop and propose a balanced model for effective teaching and learning for “on campus” higher education, with particular emphasis on the opportunities for revitalisation available through the judicious utilisation of new technologies. It will explore the opportunities available for the creation of more authentic learning environments through the principled design. Finally it will demonstrate with a case study how these have come together enabling the creation of an effective and authentic learning environment for one pre-service teacher education course at the University of Queensland.

A machine learning approach to intraday trading on foreign exchange markets

Foreign Exchange trading has emerged in recent times as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process will be very helpful. In this paper we try to create such a system using Machine learning approach to emulate trader behaviour on the Foreign Exchange market and to find the most profitable trading strategy.