Using curriculum-based measures for assessing achievement in children who may have potential risk-factors for reading difficulty

Includes bibliographical references

Long-Term Functionality of Rural Water Services in Developing Countries: A System Dynamics Approach to Understanding the Dynamic Interaction of Causal Factors

Research has shown that sustainability of rural water infrastructure in developing countries is largely affected by the dynamic and systemic interactions of technical, social, financial, institutional, and environmental factors that can lead to premature water system failure. This research employs systems dynamic modeling, which uses feedback mechanisms to understand how these factors interact dynamically to influence long-term rural water system functionality. To do this, the research first identified and aggregated key factors from literature, then asked water sector experts to indicate the polarity and strength between factors through Delphi and cross impact survey questionnaires, and finally used system dynamics modeling to identify and prioritize feedback mechanisms. The resulting model identified 101 feedback mechanisms that were dominated primarily by three and four-factor loops that contained some combination of the factors: Water System Functionality, Community, Financial, Government, Management, and Technology. These feedback mechanisms were then scored and prioritized, with the most dominant feedback mechanism identified as Water System Functionality – Community – Finance – Management. This research offers insight into the dynamic interaction of factors impacting sustainability of rural water infrastructure through the identification of these feedback mechanisms and makes a compelling case for future research to longitudinally investigate the interaction of these factors in various contexts

The sources of self-efficacy: Educational research and implications for music

Music teachers can empower students with control over their own music ability development by helping them foster positive self-efficacy beliefs. This article reviews general education and music research concerning Bandura’s theoretical four sources of self-efficacy (enactive mastery experience, vicarious experience, verbal/social persuasion, and physiological and affective states), in order to guide music teachers in determining effective methods and approaches to help students develop a sense of music self-efficacy and subsequent music achievement. A brief summary of each self-efficacy source category is provided, along with a discussion of the means whereby self-efficacy perceptions can be developed within both general education and music learning environments. Each of these four sections reviews research and simultaneously provides corresponding practical suggestions for educators

Cascading Power Outages Propagate Locally in an Influence Graph that is not the Actual Grid Topology

In a cascading power transmission outage, component outages propagate non-locally, after one component outages, the next failure may be very distant, both topologically and geographically. As a result, simple models of topological contagion do not accurately represent the propagation of cascades in power systems. However, cascading power outages do follow patterns, some of which are useful in understanding and reducing blackout risk. This paper describes a method by which the data from many cascading failure simulations can be transformed into a graph-based model of influences that provides actionable information about the many ways that cascades propagate in a particular system. The resulting "influence graph" model is Markovian, in that component outage probabilities depend only on the outages that occurred in the prior generation. To validate the model we compare the distribution of cascade sizes resulting from $n-2$ contingencies in a $2896$ branch test case to cascade sizes in the influence graph. The two distributions are remarkably similar. In addition, we derive an equation with which one can quickly identify modifications to the proposed system that will substantially reduce cascade propagation. With this equation one can quickly identify critical components that can be improved to substantially reduce the risk of large cascading blackouts.Comment: Accepted for publication at the IEEE Transactions on Power System

Historical Exploration - Learning Lessons from the Past to Inform the Future

This report examines a number of exploration campaigns that have taken place during the last 700 years, and considers them from a risk perspective. The explorations are those led by Christopher Columbus, Sir Walter Raleigh, John Franklin, Sir Ernest Shackleton, the Company of Scotland to Darien and the Apollo project undertaken by NASA. To provide a wider context for investigating the selected exploration campaigns, we seek ways of finding analogies at mission, programmatic and strategic levels and thereby to develop common themes. Ultimately, the purpose of the study is to understand how risk has shaped past explorations, in order to learn lessons for the future. From this, we begin to identify and develop tools for assessing strategic risk in future explorations. Figure 0.1 (see Page 6) summarizes the key inputs used to shape the study, the process and the results, and provides a graphical overview of the methodology used in the project. The first step was to identify the potential cases that could be assessed and to create criteria for selection. These criteria were collaboratively developed through discussion with a Business Historian. From this, six cases were identified as meeting our key criteria. Preliminary analysis of two of the cases allowed us to develop an evaluation framework that was used across all six cases to ensure consistency. This framework was revised and developed further as all six cases were analyzed. A narrative and summary statistics were created for each exploration case studied, in addition to a method for visualizing the important dimensions that capture major events. These Risk Experience Diagrams illustrate how the realizations of events, linked to different types of risks, have influenced the historical development of each exploration campaign. From these diagrams, we can begin to compare risks across each of the cases using a common framework. In addition, exploration risks were classified in terms of mission, program and strategic risks. From this, a Venn diagram and Belief Network were developed to identify how different exploration risks interacted. These diagrams allow us to quickly view the key risk drivers and their interactions in each of the historical cases. By looking at the context in which individual missions take place we have been able to observe the dynamics within an exploration campaign, and gain an understanding of how these interact with influences from stakeholders and competitors. A qualitative model has been created to capture how these factors interact, and are further challenged by unwanted events such as mission failures and competitor successes. This Dynamic Systemic Risk Model is generic and applies broadly to all the exploration ventures studied. This model is an amalgamation of a System Dynamics model, hence incorporating the natural feedback loops within each exploration mission, and a risk model, in order to ensure that the unforeseen events that may occur can be incorporated into the modeling. Finally, an overview is given of the motivational drivers and summaries are presented of the overall costs borne in each exploration venture. An important observation is that all the cases - with the exception of Apollo - were failures in terms of meeting their original objectives. However, despite this, several were strategic successes and indeed changed goals as needed in an entrepreneurial way. The Risk Experience Diagrams developed for each case were used to quantitatively assess which risks were realized most often during our case studies and to draw comparisons at mission, program and strategic levels. In addition, using the Risk Experience Diagrams and the narrative of each case, specific lessons for future exploration were identified. There are three key conclusions to this study: Analyses of historical cases have shown that there exists a set of generic risk classes. This set of risk classes cover mission, program and strategic levels, and includes all the risks encountered in the cases studied. At mission level these are Leadership Decisions, Internal Events and External Events; at program level these are Lack of Learning, Resourcing and Mission Failure; at Strategic Level they are Programmatic Failure, Stakeholder Perception and Goal Change. In addition there are two further risks that impact at all levels: Self-Interest of Actors, and False Model. There is no reason to believe that these risk classes will not be applicable to future exploration and colonization campaigns. We have deliberately selected a range of different exploration and colonization campaigns, taking place between the 15th Century and the 20th Century. The generic risk framework is able to describe the significant types of risk for these missions. Furthermore, many of these risks relate to how human beings interact and learn lessons to guide their future behavior. Although we are better schooled than our forebears and are technically further advanced, there is no reason to think we are fundamentally better at identifying, prioritizing and controlling these classes of risk. Modern risk modeling techniques are capable of addressing mission and program risk but are not as well suited to strategic risk. We have observed that strategic risks are prevalent throughout historic exploration and colonization campaigns. However, systematic approaches do not exist at the moment to analyze such risks. A risk-informed approach to understanding what happened in the past helps us guard against the danger of assuming that those events were inevitable, and highlights those chance events that produced the history that the world experienced. In turn, it allows us to learn more clearly from the past about the way our modern risk modeling techniques might help us to manage the future - and also bring to light those areas where they may not. This study has been retrospective. Based on this analysis, the potential for developing the work in a prospective way by applying the risk models to future campaigns is discussed. Follow on work from this study will focus on creating a portfolio of tools for assessing strategic and programmatic risk

The Development of Vocational Agriculture before the Vocational Education Act 1963

Agricultural education programs are experiencing pressure to change from a variety of educational and societal influences. This pressure is not new to agricultural education programs. The evolution of vocational agriculture from 1945 to 1963 provides a historical example of vocational education change as a result of social influences. Rural America experienced unprecedented emigration after World War II. The loss of students from farming families, the intended recipients of vocational agriculture, should have hampered local programs, but in fact the opposite occurred: enrollment in vocational agriculture continued to grow. We examine how vocational agriculture teachers transformed local programs to match their emerging clientele before the Vocational Education Act of 1963