Collaborative recovery: An integrative model for working with individuals that experience chronic or recurring mental illness.

Objectives: Recovery is an emerging movement in mental health. Evidence for recovery-based approaches is not well developed and approaches to implement recovery-oriented services are not well articulated. The collaborative recovery model (CRM) is presented as a model that assists clinicians to use evidence-based skills with consumers, in a manner consistent with the recovery movement. A current 5 year multisite Australian study to evaluate the effectiveness of CRM is briefly described. Conclusion: The collaborative recovery model puts into practice several aspects of policy regarding recovery-oriented services, using evidence-based practices to assist individuals who have chronic or recurring mental disorders (CRMD). It is argued that this model provides an integrative framework combining (i) evidence-based practice; (ii) manageable and modularized competencies relevant to case management and psychosocial rehabilitation contexts; and (iii) recognition of the subjective experiences of consumers.

State-of-the-Art Review on Opinion Mining from Online Customers’ Feedback

Dealing with the ever-growing information overload in the Internet, Recommender Systems are widely used online to suggest potential customers item they may like or find useful. Collaborative Filtering is the most popular techniques for Recommender Systems which collects opinions from customers in the form of ratings on items, services or service providers. In addition to the customer rating about a service provider, there is also a good number of online customer feedback information available over the Internet as customer reviews, comments, newsgroups post, discussion forums or blogs which is collectively called user generated contents. This information can be used to generate the public reputation of the service providers’. To do this, data mining techniques, specially recently emerged opinion mining could be a useful tool. In this paper we present a state of the art review of Opinion Mining from online customer feedback. We critically evaluate the existing work and expose cutting edge area of interest in opinion mining. We also classify the approaches taken by different researchers into several categories and sub-categories. Each of those steps is analyzed with their strength and limitations in this paper.

A collaborative approach to reading workshop in the middle years

Reflection Questions • How does the collaborative reading workshop approach engage students in higher order thinking and deep engagement with text? • How does the collaborative reading workshop approach support students to be active citizens and critically literate? • How does the interaction and collaborative thinking in this approach contribute to the students’ intellectual engagement and the teacher’s pedagogical rigor? • How could this approach be implemented or adapted at your school?

Planning for smart urban ecosystems : information technology applications for capacity building in environmental decision making

Since the industrial revolution, our world has experienced rapid and unplanned industrialization and urbanization. As a result, we have had to cope with serious environmental challenges. In this context, an explanation of how smart urban ecosystems can emerge, gains a crucial importance. Capacity building and community involvement have always been key issues in achieving sustainable development and enhancing urban ecosystems. By considering these, this paper looks at new approaches to increase public awareness of environmental decision making. This paper will discuss the role of Information and Communication Technologies (ICT), particularly Webbased Geographic Information Systems (Web-based GIS) as spatial decision support systems to aid public participatory environmental decision making. The paper also explores the potential and constraints of these webbased tools for collaborative decision making.

Managing ubiquitous eco cities : the role of urban telecommunication infrastructure networks and convergence technologies

A successful urban management system for a Ubiquitous Eco City requires an integrated approach. This integration includes bringing together economic, socio-cultural and urban development with a well orchestrated, transparent and open decision making mechanism and necessary infrastructure and technologies. Rapidly developing information and telecommunication technologies and their platforms in the late 20th Century improves urban management and enhances the quality of life and place. Telecommunication technologies provide an important base for monitoring and managing activities over wired, wireless or fibre-optic networks. Particularly technology convergence creates new ways in which the information and telecommunication technologies are used. The 21st Century is an era where information has converged, in which people are able to access a variety of services, including internet and location based services, through multi-functional devices such as mobile phones and provides opportunities in the management of Ubiquitous Eco Cities. This paper discusses the recent developments in telecommunication networks and trends in convergence technologies and their implications on the management of Ubiquitous Eco Cities and how this technological shift is likely to be beneficial in improving the quality of life and place. The paper also introduces recent approaches on urban management systems, such as intelligent urban management systems, that are suitable for Ubiquitous Eco Cities.

Intelligent urban management systems : online decision support systems for ubiquitous cities

A successful urban management support system requires an integrated approach. This integration includes bringing together economic, socio-cultural and urban development with a well orchestrated, transparent and open decision making mechanism. The chapter emphasizes the importance of integrated urban management to better tackle the climate change, and to achieve sustainable urban development and sound urban growth management. This chapter introduces recent approaches on urban management systems, such as intelligent urban management systems, that are suitable for ubiquitous cities. The chapter discusses the essential role of online collaborative decision making in urban and infrastructure planning, development and management, and advocates transparent, fully democratic and participatory mechanisms for an effective urban management system that is particularly suitable for ubiquitous cities. This chapter also sheds light on some of the unclear processes of urban management of ubiquitous cities and online collaborative decision making, and reveals the key benefits of integrated and participatory mechanisms in successfully constructing sustainable ubiquitous cities.

Tag based collaborative filtering for recommender systems

Collaborative tagging can help users organize, share and retrieve information in an easy and quick way. For the collaborative tagging information implies user’s important personal preference information, it can be used to recommend personalized items to users. This paper proposes a novel tag-based collaborative filtering approach for recommending personalized items to users of online communities that are equipped with tagging facilities. Based on the distinctive three dimensional relationships among users, tags and items, a new similarity measure method is proposed to generate the neighborhood of users with similar tagging behavior instead of similar implicit ratings. The promising experiment result shows that by using the tagging information the proposed approach outperforms the standard user and item based collaborative filtering approaches.

Collaborative filtering recommender systems using tag information

Recommender Systems is one of the effective tools to deal with information overload issue. Similar with the explicit rating and other implicit rating behaviours such as purchase behaviour, click streams, and browsing history etc., the tagging information implies user’s important personal interests and preferences information, which can be used to recommend personalized items to users. This paper is to explore how to utilize tagging information to do personalized recommendations. Based on the distinctive three dimensional relationships among users, tags and items, a new user profiling and similarity measure method is proposed. The experiments suggest that the proposed approach is better than the traditional collaborative filtering recommender systems using only rating data.

Primary students' group metacognitive processes in a computer supported collaborative learning environment

The current understanding of students’ group metacognition is limited. The research on metacognition has focused mainly on the individual student. The aim of this study was to address the void by developing a conceptual model to inform the use of scaffolds to facilitate group metacognition during mathematical problem solving in computer supported collaborative learning (CSCL) environments. An initial conceptual framework based on the literature from metacognition, cooperative learning, cooperative group metacognition, and computer supported collaborative learning was used to inform the study. In order to achieve the study aim, a design research methodology incorporating two cycles was used. The first cycle focused on the within-group metacognition for sixteen groups of primary school students working together around the computer; the second cycle included between-group metacognition for six groups of primary school students working together on the Knowledge Forum® CSCL environment. The study found that providing groups with group metacognitive scaffolds resulted in groups planning, monitoring, and evaluating the task and team aspects of their group work. The metacognitive scaffolds allowed students to focus on how their group was completing the problem-solving task and working together as a team. From these findings, a revised conceptual model to inform the use of scaffolds to facilitate group metacognition during mathematical problem solving in computer supported collaborative learning (CSCL) environments was generated.

L'étendue internationale des nouvelles firmes de hautes technologies: le rôle du capital humain et de l'intention stratégique des fondateurs

De récentes recherches ont mis l’accent sur l’importance pour les nouvelles entreprises internationales de l’existence de ressources et de compétences spécifiques. La présente recherche, qui s’inscrit dans ce courant, montre en particulier l’importance du capital humain acquis par les entrepreneurs sur base de leur expérience internationale passée. Mais nous montrons en même temps que ces organisations sont soutenues par une intention délibérée d’internationalisation dès l’origine. Notre recherche empirique est basée sur l’analyse d’un échantillon de 466 nouvelles entreprises de hautes technologies anglaises et allemandes. Nous montrons que ce capital humain est un actif qui facilite la pénétration rapide des marchés étrangers, et plus encore quand l’entreprise nouvelle est accompagnée d’une intention stratégique délibérée d’internationalisation. Des conclusions similaires peuvent être étendues au niveau des ressources que l’entrepreneur consacre à la start-up : plus ces ressources sont importantes, plus le processus d’internationalisation tend à se faire à grande échelle ; et là aussi, l’influence de ces ressources est augmenté par l’intention stratégique d’internationalisation. Dans le cadre des études empiriques sur les born-globals (entreprises qui démarrent sur un marché globalisé), cette recherche fournit une des premières études empiriques reliant l’influence des conditions initiales de création aux probabilités de croissance internationale rapide.

The importance of a new kind of learning in collaborative networks

There is wide agreement that in order to manage the increasingly complex and uncertain tasks of business, government and community, organizations can no longer operate in supreme isolation, but must develop a more networked approach. Networks are not ‘business as usual’. Of particular note is what has been referred to as collaborative networks. Collaborative networks now constitute a significant part of our institutional infrastructure. A key driver for the proliferation of these multiorganizational arrangements is their ability to facilitate the learning and knowledge necessary to survive or to respond to increasingly complex social issues In this regard the emphasis is on the importance of learning in networks. Learning applies to networks in two different ways. These refer to the kinds of learning that occur as part of the interactive processes of networks. This paper looks at the importance of these two kinds of learning in collaborative networks. The first kind of learning relates to networks as learning networks or communities of practice. In learning networks people exchange ideas with each other and bring back this new knowledge for use in their own organizations. The second type of learning is referred to as network learning. Network learning refers to how people in collaborative networks learn new ways of communicating and behaving with each other. Network learning has been described as transformational in terms of leading to major systems changes and innovation. In order to be effective, all networks need to be involved as learning networks; however, collaborative networks must also be involved in network learning to be effective. In addition to these two kinds of learning in collaborative networks this paper also focuses on the importance of how we learn about collaborative networks. Maximizing the benefits of working through collaborative networks is dependent on understanding their unique characteristics and how this impacts on their operation. This requires a new look at how we specifically teach about collaborative networks and how this is similar to and/or different from how we currently teach about interorgnizational relations.

Learning to program : from pear-shaped to pairs

The consistently high failure rate in Queensland University of Technology’s introductory programming subject reflects a similar dilemma facing other universities worldwide. Experiments were conducted to quantify the effectiveness of collaborative learning on introductory level programming students over a number of semesters, replicating previous studies in this area. A selection of workshops in the introductory programming subject required students to problem-solve and program in pairs, mimicking the eXtreme Programming concept of pair programming. The failure rate for the subject fell from what had been an average of 30% since 2003 (with a high of 41% in 2006), to just 5% for those students who worked consistently in pairs.

Recommending best answer in a collaborative question answering system

The World Wide Web has become a medium for people to share information. People use Web-based collaborative tools such as question answering (QA) portals, blogs/forums, email and instant messaging to acquire information and to form online-based communities. In an online QA portal, a user asks a question and other users can provide answers based on their knowledge, with the question usually being answered by many users. It can become overwhelming and/or time/resource consuming for a user to read all of the answers provided for a given question. Thus, there exists a need for a mechanism to rank the provided answers so users can focus on only reading good quality answers. The majority of online QA systems use user feedback to rank users’ answers and the user who asked the question can decide on the best answer. Other users who didn’t participate in answering the question can also vote to determine the best answer. However, ranking the best answer via this collaborative method is time consuming and requires an ongoing continuous involvement of users to provide the needed feedback. The objective of this research is to discover a way to recommend the best answer as part of a ranked list of answers for a posted question automatically, without the need for user feedback. The proposed approach combines both a non-content-based reputation method and a content-based method to solve the problem of recommending the best answer to the user who posted the question. The non-content method assigns a score to each user which reflects the users’ reputation level in using the QA portal system. Each user is assigned two types of non-content-based reputations cores: a local reputation score and a global reputation score. The local reputation score plays an important role in deciding the reputation level of a user for the category in which the question is asked. The global reputation score indicates the prestige of a user across all of the categories in the QA system. Due to the possibility of user cheating, such as awarding the best answer to a friend regardless of the answer quality, a content-based method for determining the quality of a given answer is proposed, alongside the non-content-based reputation method. Answers for a question from different users are compared with an ideal (or expert) answer using traditional Information Retrieval and Natural Language Processing techniques. Each answer provided for a question is assigned a content score according to how well it matched the ideal answer. To evaluate the performance of the proposed methods, each recommended best answer is compared with the best answer determined by one of the most popular link analysis methods, Hyperlink-Induced Topic Search (HITS). The proposed methods are able to yield high accuracy, as shown by correlation scores: Kendall correlation and Spearman correlation. The reputation method outperforms the HITS method in terms of recommending the best answer. The inclusion of the reputation score with the content score improves the overall performance, which is measured through the use of Top-n match scores.