Social Impact Bonds: Overview and Considerations

One of the hottest topics in human services is "pay-for-success" approaches to government contracting. In this era of tight budgets and increased skepticism about the effectiveness of government-funded programs, the idea that the government could pay only for proven results has a broad appeal. And those who have identified prevention-focused models that have the potential to improve long-term outcomes and save the government money are deeply frustrated that they have been unable to attract the funding needed to take these programs to scale. Some advocates for expanded prevention efforts are confident that these programs could thrive under pay for success and see such an approach as a way to break out of the harmful cycle where what limited funds are available must be used to provide services for those who are already in crisis, and there are rarely sufficient funds to pay for prevention

Active Object Localization in Visual Situations

We describe a method for performing active localization of objects in instances of visual situations. A visual situation is an abstract concept---e.g., "a boxing match", "a birthday party", "walking the dog", "waiting for a bus"---whose image instantiations are linked more by their common spatial and semantic structure than by low-level visual similarity. Our system combines given and learned knowledge of the structure of a particular situation, and adapts that knowledge to a new situation instance as it actively searches for objects. More specifically, the system learns a set of probability distributions describing spatial and other relationships among relevant objects. The system uses those distributions to iteratively sample object proposals on a test image, but also continually uses information from those object proposals to adaptively modify the distributions based on what the system has detected. We test our approach's ability to efficiently localize objects, using a situation-specific image dataset created by our group. We compare the results with several baselines and variations on our method, and demonstrate the strong benefit of using situation knowledge and active context-driven localization. Finally, we contrast our method with several other approaches that use context as well as active search for object localization in images.Comment: 14 page

Designing for change: mash-up personal learning environments

Institutions for formal education and most work places are equipped today with at least some kind of tools that bring together people and content artefacts in learning activities to support them in constructing and processing information and knowledge. For almost half a century, science and practice have been discussing models on how to bring personalisation through digital means to these environments. Learning environments and their construction as well as maintenance makes up the most crucial part of the learning process and the desired learning outcomes and theories should take this into account. Instruction itself as the predominant paradigm has to step down. The learning environment is an (if not 'the�) important outcome of a learning process, not just a stage to perform a 'learning play'. For these good reasons, we therefore consider instructional design theories to be flawed. In this article we first clarify key concepts and assumptions for personalised learning environments. Afterwards, we summarise our critique on the contemporary models for personalised adaptive learning. Subsequently, we propose our alternative, i.e. the concept of a mash-up personal learning environment that provides adaptation mechanisms for learning environment construction and maintenance. The web application mash-up solution allows learners to reuse existing (web-based) tools plus services. Our alternative, LISL is a design language model for creating, managing, maintaining, and learning about learning environment design; it is complemented by a proof of concept, the MUPPLE platform. We demonstrate this approach with a prototypical implementation and a – we think – comprehensible example. Finally, we round up the article with a discussion on possible extensions of this new model and open problems

A Typology of Virtual Teams: Implications for Effective Leadership

As the nature of work in today\u27s organizations becomes more complex, dynamic, and global, there has been an increasing emphasis on far-flung, distributed, virtual teams as organizing units of work. Despite their growing prevalence, relatively little is known about this new form of work unit. The purpose of this paper is to present a theoretical framework to focus research toward understanding virtual teams and, in particular, to identify implications for effective leadership. Specifically, we focus on delineating the dimensions of a typology to characterize different types of virtual teams. First, we distinguish virtual teams from conventional teams to identify where current knowledge applies and new research needs to be developed. Second, we distinguish among different types of virtual teams, considering the critical role of task complexity in determining the underlying characteristics of virtual teams and leadership challenges the different types entail. Propositions addressing leadership implications for the effective management of virtual teams are proposed and discussed

Distributed Learning System Design: A New Approach and an Agenda for Future Research

This article presents a theoretical framework designed to guide distributed learning design, with the goal of enhancing the effectiveness of distributed learning systems. The authors begin with a review of the extant research on distributed learning design, and themes embedded in this literature are extracted and discussed to identify critical gaps that should be addressed by future work in this area. A conceptual framework that integrates instructional objectives, targeted competencies, instructional design considerations, and technological features is then developed to address the most pressing gaps in current research and practice. The rationale and logic underlying this framework is explicated. The framework is designed to help guide trainers and instructional designers through critical stages of the distributed learning system design process. In addition, it is intended to help researchers identify critical issues that should serve as the focus of future research efforts. Recommendations and future research directions are presented and discussed