Model Matching Theory: A Framework for Examining the Alignment between Game Mechanics and Mental Models

The primary aim of this article is to provide a comprehensive review and elaboration of model matching and its theo- retical propositions. Model matching explains and predicts individuals’ outcomes related to gameplay by focusing on the interrelationships among games’ systems of mechanics, relevant situations external to the game, and players’ mental mod- els. Formalizing model matching theory in this way provides researchers a unified explanation for game-based learning, game performance, and related gameplay outcomes while also providing a theory-based direction for advancing the study of games more broadly. The propositions explicated in this article are intended to serve as the primary tenets of model matching theory. Considerations for how these propositions may be tested in future games studies research are discussed

Statistics as Unbiased Estimators: Exploring the Teaching of Standard Deviation

This manuscript presents findings from a study about the knowledge for and planned teaching of standard deviation. We investigate how understanding variance as an unbiased (inferential) estimator – not just a descriptive statistic for the variation (spread) in data – is related to teachers’ instruction regarding standard deviation, particularly around the issue of division by n-1. In this regard, the study contributes to our understanding about how knowledge of mathematics beyond the current instructional level, what we refer to as nonlocal mathematics, becomes important for teaching. The findings indicate that acquired knowledge of nonlocal mathematics can play a role in altering teachers’ planned instructional approaches in terms of student activity and cognitive demand in their instruction

Secondary Mathematics Teachers’ Planned Approaches For Teaching Standard Deviation

Research-based guidelines for learning variation exist (e.g., Franklin et al., 2007; Garfield, delMas, & Chance, 2007), but little is known about how teachers plan to teach standard deviation, or how these plans align with recent recommendations. In this article, we survey lesson plans designed by inservice and preservice secondary mathematical teachers. We report on the accuracy, technology usage, and visual representations in the lesson plans. We consider how many elements are used, the level of conceptual development, and the mathematical nature. Findings support differences between preservice and master’s level students in education, as well as a tendency by in-service teachers to teach in alignment with prior learning experiences, despite professional development. Implications for teacher education and curricular development are offered

Model Matching Theory: A Framework for Examining the Alignment between Game Mechanics and Mental Models

The primary aim of this article is to provide a comprehensive review and elaboration of model matching and its theoretical propositions. Model matching explains and predicts individuals’ outcomes related to gameplay by focusing on the interrelationships among games’ systems of mechanics, relevant situations external to the game, and players’ mental models. Formalizing model matching theory in this way provides researchers a unified explanation for game-based learning, game performance, and related gameplay outcomes while also providing a theory-based direction for advancing the study of games more broadly. The propositions explicated in this article are intended to serve as the primary tenets of model matching theory. Considerations for how these propositions may be tested in future games studies research are discussed

A qualitative study of the activities performed by people involved in clinical decision support: recommended practices for success

Objective: To describe the activities performed by people involved in clinical decision support (CDS) at leading sites. Materials and methods We conducted ethnographic observations at seven diverse sites with a history of excellence in CDS using the Rapid Assessment Process and analyzed the data using a series of card sorts, informed by Linstone's Multiple Perspectives Model. Results: We identified 18 activities and grouped them into four areas. Area 1: Fostering relationships across the organization, with activities (a) training and support, (b) visibility/presence on the floor, (c) liaising between people, (d) administration and leadership, (e) project management, (f) cheerleading/buy-in/sponsorship, (g) preparing for CDS implementation. Area 2: Assembling the system with activities (a) providing technical support, (b) CDS content development, (c) purchasing products from vendors (d) knowledge management, (e) system integration. Area 3: Using CDS to achieve the organization's goals with activities (a) reporting, (b) requirements-gathering/specifications, (c) monitoring CDS, (d) linking CDS to goals, (e) managing data. Area 4: Participation in external policy and standards activities (this area consists of only a single activity). We also identified a set of recommendations associated with these 18 activities. Discussion All 18 activities we identified were performed at all sites, although the way they were organized into roles differed substantially. We consider these activities critical to the success of a CDS program. Conclusions: A series of activities are performed by sites strong in CDS, and sites adopting CDS should ensure they incorporate these activities into their efforts

Correlates of Suicide Ideation and Attempt among Youth Living in the Slums of Kampala

While suicidal behavior is recognized as a growing public health problem world-wide, little is known about the prevalence and risk factors for suicidal behaviors among street and slum youth in Africa, and in Uganda, specifically. The number of youth who live on the streets and in the slums of Kampala appears to be growing rapidly, but their mental health needs have not been documented, which has hampered resource allocation and service implementation. This study of youth, ages 14–24, was conducted in May and June of 2011, to assess the prevalence and correlates of suicidal behavior. Participants (N = 457) were recruited for a 30-minute interviewer-administered survey through eight drop-in centers operated by the Uganda Youth Development Link for youth in need of services. Bivariate and multivariate logistic regression analyses were computed to determine associations between psychosocial correlates and suicide ideation and suicide attempt. Reporting both parents deceased Adj.OR = 2.36; 95% CI: 1.23–4.52), parental neglect due to alcohol use (Adj.OR = 2.09; 95% CI: 1.16–3.77), trading sex for food, shelter or money (Adj.OR = 1.95; 95% CI: 1.09–3.51), sadnesss (Adj.OR = 2.42; 95% CI: 1.20–4.89), loneliness (Adj.OR = 2.67; 95% CI: 1.12–6.40) and expectations of dying prior to age 30 (Adj.OR = 2.54; 95% CI: 1.53–4.23) were significantly associated with suicide ideation in multivariate analyses. Parental neglect due to alcohol use (Adj.OR = 2.04; 95% CI: 1.11–3.76), sadness (Adj.OR = 2.42; 95% CI: 1.30–7.87), and expectations of dying prior to age 30 (Adj.OR = 2.18; 95% CI: 1.25–3.79) were significantly associated with suicide attempt in multivariate analyses. Given the dire circumstances of this vulnerable population, increased services and primary prevention efforts to address the risk factors for suicidal behavior are urgently needed

Towards Machine Wald

The past century has seen a steady increase in the need of estimating and predicting complex systems and making (possibly critical) decisions with limited information. Although computers have made possible the numerical evaluation of sophisticated statistical models, these models are still designed \emph{by humans} because there is currently no known recipe or algorithm for dividing the design of a statistical model into a sequence of arithmetic operations. Indeed enabling computers to \emph{think} as \emph{humans} have the ability to do when faced with uncertainty is challenging in several major ways: (1) Finding optimal statistical models remains to be formulated as a well posed problem when information on the system of interest is incomplete and comes in the form of a complex combination of sample data, partial knowledge of constitutive relations and a limited description of the distribution of input random variables. (2) The space of admissible scenarios along with the space of relevant information, assumptions, and/or beliefs, tend to be infinite dimensional, whereas calculus on a computer is necessarily discrete and finite. With this purpose, this paper explores the foundations of a rigorous framework for the scientific computation of optimal statistical estimators/models and reviews their connections with Decision Theory, Machine Learning, Bayesian Inference, Stochastic Optimization, Robust Optimization, Optimal Uncertainty Quantification and Information Based Complexity.Comment: 37 page

Changes in Personal Networks of Women in Residential and Outpatient Substance Abuse Treatment

Changes in personal network composition, support and structure over 12 months were examined in 377 women from residential (n=119) and intensive outpatient substance abuse treatment (n=258) through face-to-face interviews utilizing computer based data collection. Personal networks of women who entered residential treatment had more substance users, more people with whom they had used alcohol and/or drugs, and fewer people from treatment programs or self-help groups than personal networks of women who entered intensive outpatient treatment. By 12 months post treatment intake, network composition improved for women in residential treatment; however, concrete support was still lower and substance users still more prevalent in their networks. Network composition of women in outpatient treatment remained largely the same over time. Both groups increased cohesiveness within the network over 12 months. Targeting interventions that support positive changes in personal networks may heighten positive long term outcomes for women entering treatment

The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe

The preponderance of matter over antimatter in the early Universe, the dynamics of the supernova bursts that produced the heavy elements necessary for life and whether protons eventually decay --- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our Universe, its current state and its eventual fate. The Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed plan for a world-class experiment dedicated to addressing these questions. LBNE is conceived around three central components: (1) a new, high-intensity neutrino source generated from a megawatt-class proton accelerator at Fermi National Accelerator Laboratory, (2) a near neutrino detector just downstream of the source, and (3) a massive liquid argon time-projection chamber deployed as a far detector deep underground at the Sanford Underground Research Facility. This facility, located at the site of the former Homestake Mine in Lead, South Dakota, is approximately 1,300 km from the neutrino source at Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino charge-parity symmetry violation and mass ordering effects. This ambitious yet cost-effective design incorporates scalability and flexibility and can accommodate a variety of upgrades and contributions. With its exceptional combination of experimental configuration, technical capabilities, and potential for transformative discoveries, LBNE promises to be a vital facility for the field of particle physics worldwide, providing physicists from around the globe with opportunities to collaborate in a twenty to thirty year program of exciting science. In this document we provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess.Comment: Major update of previous version. This is the reference document for LBNE science program and current status. Chapters 1, 3, and 9 provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess. 288 pages, 116 figure

Have State Renewable Portfolio Standards Really Worked? Synthesizing Past Policy Assessments to Build an Integrated Econometric Analysis of RPS effectiveness in the U.S.

Renewable portfolio standards (RPS) are the most popular U.S. state-level policies for promoting deployment of renewable electricity (RES-E). While several econometric studies have estimated the effect of RPS on in-state RES-E deployment, results are contradictory. We reconcile these studies and move toward a definitive answer to the question of RPS effectiveness. We conduct an analysis using time series cross sectional regressions - including the most nuanced controls for policy design features to date - and nonparametric matching analysis. We find that higher RPS stringency does not necessarily drive more RES-E deployment. We examine several RPS design features and market characteristics (including REC unbundling, RPS in neighboring states, out-of-state renewable energy purchases) that may explain the gap between effective and ineffective policies. We also investigate other RES-E policies and technology-specific effects. Ultimately, we show that RPS effectiveness is largely explained by a combination of policy design, market context, and inter-state trading effects