Utility-Based Evaluation of Adaptive Systems

The variety of user-adaptive hypermedia systems available calls for methods of comparison. Layered evaluation techniques appear to be useful for this purpose. In this paper we present a utility-based evaluation approach that is based on these techniques. Issues that arise when putting utility-based evaluation into practice are dealt with. We also explain the need for interpretative user models and common sets of evaluation criteria for different domains

Agile, Web Engineering and Capability Maturity ModelI ntegration : A systematic literature review

Context Agile approaches are an alternative for organizations developing software, particularly for those who develop Web applications. Besides, CMMI (Capability Maturity Model Integration) models are well-established approaches focused on assessing the maturity of an organization that develops software. Web Engineering is the field of Software Engineering responsible for analyzing and studying the specific characteristics of the Web. The suitability of an Agile approach to help organizations reach a certain CMMI maturity level in Web environments will be very interesting, as they will be able to keep the ability to quickly react and adapt to changes as long as their development processes get mature. Objective This paper responds to whether it is feasible or not, for an organization developing Web systems, to achieve a certain maturity level of the CMMI-DEV model using Agile methods. Method The proposal is analyzed by means of a systematic literature review of the relevant approaches in the field, defining a characterization schema in order to compare them to introduce the current state-of-the-art. Results The results achieved after the systematic literature review are presented, analyzed and compared against the defined schema, extracting relevant conclusions for the different dimensions of the problem: compatibility, compliance, experience, maturity and Web. Conclusion It is concluded that although the definition of an Agile approach to meet the different CMMI maturity levels goals could be possible for an organization developing Web systems, there is still a lack of detailed studies and analysis on the field

An Enhanced Archive Facilitating Climate Impacts and Adaptation Analysis

We describe the expansion of a publicly available archive of downscaled climate and hydrology projections for the United States. Those studying or planning to adapt to future climate impacts demand downscaled climate model output for local or regional use. The archive we describe attempts to fulfill this need by providing data in several formats, selectable to meet user needs. Our archive has served as a resource for climate impacts modelers, water managers, educators, and others. Over 1,400 individuals have transferred more than 50 TB of data from the archive. In response to user demands, the archive has expanded from monthly downscaled data to include daily data to facilitate investigations of phenomena sensitive to daily to monthly temperature and precipitation, including extremes in these quantities. New developments include downscaled output from the new Coupled Model Intercomparison Project phase 5 (CMIP5) climate model simulations at both the monthly and daily time scales, as well as simulations of surface hydrologi- cal variables. The web interface allows the extraction of individual projections or ensemble statistics for user-defined regions, promoting the rapid assessment of model consensus and uncertainty for future projections of precipitation, temperature, and hydrology. The archive is accessible online (http://gdo-dcp.ucllnl.org/downscaled_ cmip_projections)

Tools for Assessing Climate Impacts on Fish and Wildlife

Climate change is already affecting many fish and wildlife populations. Managing these populations requires an understanding of the nature, magnitude, and distribution of current and future climate impacts. Scientists and managers have at their disposal a wide array of models for projecting climate impacts that can be used to build such an understanding. Here, we provide a broad overview of the types of models available for forecasting the effects of climate change on key processes that affect fish and wildlife habitat (hydrology, fire, and vegetation), as well as on individual species distributions and populations. We present a framework for how climate-impacts modeling can be used to address management concerns, providing examples of model-based assessments of climate impacts on salmon populations in the Pacific Northwest, fire regimes in the boreal region of Canada, prairies and savannas in the Willamette Valley-Puget Sound Trough-Georgia Basin ecoregion, and marten Martes americana populations in the northeastern United States and southeastern Canada. We also highlight some key limitations of these models and discuss how such limitations should be managed. We conclude with a general discussion of how these models can be integrated into fish and wildlife management

Making inferences with small numbers of training sets

A potential methodological problem with empirical studies that assess project effort prediction system is discussed. Frequently, a hold-out strategy is deployed so that the data set is split into a training and a validation set. Inferences are then made concerning the relative accuracy of the different prediction techniques under examination. This is typically done on very small numbers of sampled training sets. It is shown that such studies can lead to almost random results (particularly where relatively small effects are being studied). To illustrate this problem, two data sets are analysed using a configuration problem for case-based prediction and results generated from 100 training sets. This enables results to be produced with quantified confidence limits. From this it is concluded that in both cases using less than five training sets leads to untrustworthy results, and ideally more than 20 sets should be deployed. Unfortunately, this raises a question over a number of empirical validations of prediction techniques, and so it is suggested that further research is needed as a matter of urgency

The organizational social context of mental health services and clinician attitudes toward evidence-based practice: a United States national study.

UnlabelledABSTBACKGROUND: Evidence-based practices have not been routinely adopted in community mental health organizations despite the support of scientific evidence and in some cases even legislative or regulatory action. We examined the association of clinician attitudes toward evidence-based practice with organizational culture, climate, and other characteristics in a nationally representative sample of mental health organizations in the United States.MethodsIn-person, group-administered surveys were conducted with a sample of 1,112 mental health service providers in a nationwide sample of 100 mental health service institutions in 26 states in the United States. The study examines these associations with a two-level Hierarchical Linear Modeling (HLM) analysis of responses to the Evidence-Based Practice Attitude Scale (EBPAS) at the individual clinician level as a function of the Organizational Social Context (OSC) measure at the organizational level, controlling for other organization and clinician characteristics.ResultsWe found that more proficient organizational cultures and more engaged and less stressful organizational climates were associated with positive clinician attitudes toward adopting evidence-based practice.ConclusionsThe findings suggest that organizational intervention strategies for improving the organizational social context of mental health services may contribute to the success of evidence-based practice dissemination and implementation efforts by influencing clinician attitudes

Evaluation of social personalized adaptive E-Learning environments : end-user point of view

The use of adaptations, along with the social affordances of collaboration and networking, carries a great potential for improving e-learning experiences. However, the review of the previous work indicates current e-learning systems have only marginally explored the integration of social features and adaptation techniques. The overall aim of this research, therefore, is to address this gap by evaluating a system developed to foster social personalized adaptive e-learning experiences. We have developed our first prototype system, Topolor, based on the concepts of Adaptive Educational Hypermedia and Social E-Learning. We have also conducted an experimental case study for the evaluation of the prototype system from different perspectives. The results show a considerably high satisfaction of the end users. This paper reports the evaluation results from end user point of view, and generalizes our method to a component-based evaluation framework