Integrating science and management through collaborative learning and better information management

Achieving more sustainable land and water use depends on high-quality information and its improved use. In other words, better linkages are needed between science and management. Since many stakeholders with different relationships to the natural resources are inevitably involved, we suggest that collaborative learning environments and improved information management are prerequisites for integrating science and management. Case studies that deal with resource management issues are presented that illustrate the creation of collaborative learning environments through systems analyses with communities, and an integration of scientific and experiential knowledge of components of the system. This new knowledge needs to be captured and made accessible through innovative information management systems designed collaboratively with users, in forms which fit the users' 'mental models' of how their systems work. A model for linking science and resource management more effectively is suggested. This model entails systems thinking in a collaborative learning environment, and processes to help convergence of views and value systems, and make scientists and different kinds of managers aware of their interdependence. Adaptive management provides a mechanism for applying and refining scientists' and managers' knowledge. Copyright (C) 2003 John Wiley Sons, Ltd.

On the execution of collaborative business processes

Management of collaborative business processes that span multiple business entities has emerged as a key requirement for business success. These processes are embedded in sets of rules describing complex message-based interactions between parties such that if a logical expression defined on the set of received messages is satisfied, one or more outgoing messages are dispatched. The execution of these processes presents significant challenges since each contentrich message may contribute towards the evaluation of multiple expressions in different ways and the sequence of message arrival cannot be predicted. These challenges must be overcome in order to develop an efficient execution strategy for collaborative processes in an intensive operating environment with a large number of rules and very high throughput of messages. In this paper, we present a discussion on issues relevant to the evaluation of such expressions and describe a basic query-based method for this purpose, including suggested indexes for improved performance. We conclude by identifying several potential future research directions in this area. © 2010 IEEE. All rights reserved

Intelligent agent supported personalization for virtual learning environments

Virtual learning environments (VLEs) are computer-based online learning environments, which provide opportunities for online learners to learn at the time and location of their choosing, whilst allowing interactions and encounters with other online learners, as well as affording access to a wide range of resources. They have the capability of reaching learners in remote areas around the country or across country boundaries at very low cost. Personalized VLEs are those VLEs that provide a set of personalization functionalities, such as personalizing learning plans, learning materials, tests, and are capable of initializing the interaction with learners by providing advice, necessary instant messages, etc., to online learners. One of the major challenges involved in developing personalized VLEs is to achieve effective personalization functionalities, such as personalized content management, learner model, learner plan and adaptive instant interaction. Autonomous intelligent agents provide an important technology for accomplishing personalization in VLEs. A number of agents work collaboratively to enable personalization by recognizing an individual's eLeaming pace and reacting correspondingly. In this research, a personalization model has been developed that demonstrates dynamic eLearning processes; secondly, this study proposes an architecture for PVLE by using intelligent decision-making agents' autonomous, pre-active and proactive behaviors. A prototype system has been developed to demonstrate the implementation of this architecture. Furthemore, a field experiment has been conducted to investigate the performance of the prototype by comparing PVLE eLearning effectiveness with a non-personalized VLE. Data regarding participants' final exam scores were collected and analyzed. The results indicate that intelligent agent technology can be employed to achieve personalization in VLEs, and as a consequence to improve eLeaming effectiveness dramatically.

Rapport-building through call in teaching Chinese as a foreign language: An exploratory study

Technological advances have brought about the ever-increasing utilisation of computer-assisted language learning ( CALL) media in the learning of a second language (L2). Computer-mediated communication, for example, provides a practical means for extending the learning of spoken language, a challenging process in tonal languages such as Chinese, beyond the realms of the classroom. In order to effectively improve spoken language competency, however, CALL applications must also reproduce the social interaction that lies at the heart of language learning and language use. This study draws on data obtained from the utilisation of CALL in the learning of L2 Chinese to explore whether this medium can be used to extend opportunities for rapport-building in language teaching beyond the face-to-face interaction of the classroom. Rapport's importance lies in its potential to enhance learning, motivate learners, and reduce learner anxiety. To date, CALL's potential in relation to this facet of social interaction remains a neglected area of research. The results of this exploratory study suggest that CALL may help foster learner-teacher rapport and that scaffolding, such as strategically composing rapport-fostering questions in sound-files, is conducive to this outcome. The study provides an instruction model for this application of CALL.

How can experience in clinical and community settings contribute to early medical education? A BEME systematic review

Review date: Review period January 1992-December 2001. Final analysis July 2004-January 2005. Background and review context: There has been no rigorous systematic review of the outcomes of early exposure to clinical and community settings in medical education. Objectives of review: (1) Identify published empirical evidence of the effects of early experience in medical education, analyse it, and synthesize conclusions from it. (2) Identify the strengths and limitations of the research effort to date, and identify objectives for future research. Search strategy: Ovid search of. BEI, ERIC, Medline, CIATAHL and EMBASE Additional electronic searches of: Psychinfo, Timelit, EBM reviews, SIGLE, and the Cochrane databases. Hand-searches of: Medical Education, Medical Teacher, Academic Medicine, Teaching and Learning in Medicine, Advances in Health Sciences Education, Journal of Educational Psychology. Criteria: Definitions: Experience: Authentic (real as opposed to simulated) human contact in a social or clinical context that enhances learning of health, illness and/or disease, and the role of the health professional. Early: What would traditionally have been regarded as the preclinical phase, usually the first 2 years. Inclusions: All empirical studies (verifiable, observational data) of early experience in the basic education of health professionals, whatever their design or methodology, including papers not in English. Evidence from other health care professions that could be applied to medicine was included. Exclusions: Not empirical; not early; post-basic; simulated rather than 'authentic' experience. Data collection: Careful validation of selection processes. Coding by two reviewers onto an extensively modified version of the standard BEME coding sheet. Accumulation into an Access database. Secondary coding and synthesis of an interpretation. Headline results: A total of 73 studies met the selection criteria and yielded 277 educational outcomes; 116 of those outcomes (from 38 studies) were rated strong and important enough to include in a narrative synthesis of results; 76% of those outcomes were from descriptive studies and 24% from comparative studies. Early experience motivated and satisfied students of the health professions and helped them acclimatize to clinical environments, develop professionally, interact with patients with more confidence and less stress, develop self-reflection and appraisal skill, and develop a professional identity. It strengthened their learning and made it more real and relevant to clinical practice. It helped students learn about the structure and function of the healthcare system, and about preventive care and the role of health professionals. It supported the learning of both biomedical and behavioural/social sciences and helped students acquire communication and basic clinical skills. There were outcomes for beneficiaries other than students, including teachers, patients, populations, organizations and specialties. Early experience increased recruitment to primary care/rural medical practice, though mainly in US studies which introduced it for that specific purpose as part of a complex intervention. Conclusions: Early experience helps medical students socialize to their chosen profession. It. helps them acquire a range of subject matter and makes their learning more real and relevant. It has potential benefits for other stakeholders, notably teachers and patients. It can influence career choices.

A corpus-based analysis of transfer effects and connected speech processes in Vietnamese English

This paper presents a corpus-based descriptive analysis of the most prevalent transfer effects and connected speech processes observed in a comparison of 11 Vietnamese English speakers (6 females, 5 males) and 12 Australian English speakers (6 males, 6 females) over 24 grammatical paraphrase items. The phonetic processes are segmentally labelled in terms of IPA diacritic features using the EMU speech database system with the aim of labelling departures from native-speaker pronunciation. An analysis of prosodic features was made using ToBI framework. The results show many phonetic and prosodic processes which make non-native speakers’ speech distinct from native ones. The corpusbased methodology of analysing foreign accent may have implications for the evaluation of non-native accent, accented speech recognition and computer assisted pronunciation- learning.