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Many institutions of higher education increasingly place a focus on various forms of experiential education, including personal reflections. While much work has been done in this and related areas, the resources currently available are not sufficient to effectively guide, assess, and evaluate student learning through reflection. Guiding students through the process, assessing their work, and providing an evaluation presents challenges for educators. This article discusses a new framework, a robust rubric, and a guide that students and evaluators can use to support experiential learning through reflection. The framework and resources are based on a grounded investigation of student reflections that were compared to various models from the literature. The framework and resources discussed in the article were developed over a period of five years and with more than 1,600 students. Our purpose here is to describe the development of this framework, to provide a description of the rubric and guide, and to share the lessons learned. This framework and accompanying materials will, we hope, be a useful resource for educators and students wishing to support experiential learning through the use of reflection.

Sustainability challenges are complex and call for the effective development of knowledge, skills, and abilities in current and new leaders. New offerings in higher education provide sustainability training to complement studies in geography, engineering, science, and other disciplines, in many cases including innovative experiential learning components -- including the use of reflection. Although reflection in education is not a new concept, how to assess reflection has remained challenging. Recent research on the Reflective Learning Framework (RLF) aims to address many of the challenges associated with guiding, assessing, and evaluating student learning through reflections. The objective of this research was to investigate the perceptions of students who use the RLF about their experience using reflection in a sustainability course. Semi-structured interviews with students provide a valuable perspective on the use of reflection. Particularly, findings from this research indicate that students see reflection as a tool to develop and use cognitive and metacognitive skills, and also as a tool to support knowledge retention and transfer. Accordingly, student perspectives on reflection show that this practice contributes to the acquisition of higher-order thinking skills required to address the complex challenges of sustainability.

Residual spatial autocorrelation is a situation frequently encountered in regression analysis of spatial data. The statistical problems arising due to this phenomenon are well‐understood. Original developments in the field of statistical analysis of spatial data were meant to detect spatial pattern, in order to assess whether corrective measures were required. An early development was the use of residual autocorrelation as an exploratory tool to improve regression analysis of spatial data. In this note, we propose the use of spatial filtering and exploratory data analysis as a way to identify omitted but potentially relevant independent variables. We use an example of blood donation patterns in Toronto, Canada, to demonstrate the proposed approach. In particular, we show how an initial filter used to rectify autocorrelation problems can be progressively replaced by substantive variables. In the present case, the variables so retrieved reveal the impact of urban form, travel habits, and demographic and socio‐economic attributes on donation rates. The approach is particularly appealing for model formulations that do not easily accommodate positive spatial autocorrelation, but should be of interest as well for the case of continuous variables in linear regression. [ABSTRACT FROM AUTHOR]

Floating Catchment Area (FCA) methods are a popular tool to investigate accessibility to public facilities, in particular health care services. FCA approaches are attractive because, unlike other accessibility measures, they take into account the potential for congestion of facilities. This is done by 1) considering the population within the catchment area of a facility to calculate a variable that measures level of service, and then 2) aggregating the level of service by population centers subject to catchment area constraints. In this paper we discuss an effect of FCA approaches, an artifact that we term demand and level of service inflation. These artifacts are present in previous implementations of FCA methods. We argue that inflation makes interpretation of estimates of accessibility difficult, which has possible deleterious consequences for decision making. Next, we propose a simple and intuitive approach to proportionally allocate demandand and level of service in FCA calculations. The approach is based on a standardization of the impedance matrix, similar to approaches popular in the spatial statistics and econometrics literature. The result is a more intiuitive measure of accessibility that 1) provides a local version of the provider-to-population ratio; and 2) preserves the level of demand and the level of supply in a system. We illustrate the relevant issues with some examples, and then empirically by means of a case study of accessibility to family physicians in the Hamilton Census Metropolitan Area (CMA), in Ontario, Canada. Results indicate that demand and supply inflation/deflation affect the interpretation of accessibility analysis using existing FCA methods, and that the proposed adjustment can lead to more intuitive results. [ABSTRACT FROM AUTHOR]

Abstract: The objective of this paper is to investigate the factors that influence distance traveled by individuals in Canadian urban areas, with a particular focus on three population segments thought to face the risk of mobility challenges: the elderly, low-income people, and members of single-parent households. Data obtained for three large urban centers – Hamilton, Toronto, and Montreal – are analyzed using spatial expansion models, a technique used to obtain spatially-varying coefficients that help to tease out contextual person-location variations in travel behavior. Detailed geographical results help to enhance our understanding of the spatiality of travel behavior of the population segments of interest. Substantively, the results provide evidence of significant interactions between location, various demographic factors, and mobility tools. More specifically, the results evince patterns of mobility that are significantly different from the mainstream population, particularly in suburban settings, in ways that are indicative of mobility challenges. [ABSTRACT FROM AUTHOR]

• Strategies to model opponent effects in the analysis of severity of crashes involving two-parties. • A data workflow is presented for preparing data for modelling party interactions. • Single-level and hierarchical models are compared. • Full-sample and sub-sample models are compared. • The results provide information useful to select a modelling strategy for crash severity. Road crashes impose an important burden on health and the economy. Numerous efforts have been undertaken to understand the factors that affect road collisions in general, and the severity of crashes in particular. In this literature several strategies have been proposed to model interactions between parties in a crash, including the use of variables regarding the other party (or parties) in the collision, data subsetting, and estimating models with hierarchical components. Since no systematic assessment has been conducted of the performance of these strategies, they appear to be used in an ad-hoc fashion in the literature. The objective of this paper is to empirically evaluate ways to model party interactions in the context of crashes involving two parties. To this end, a series of models are estimated using data from Canada's National Collision Database. Three levels of crash severity (no injury/injury/fatality) are analyzed using ordered probit models and covariates for the parties in the crash and the conditions of the crash. The models are assessed using predicted shares and classes of outcomes, and the results highlight the importance of considering opponent effects in crash severity analysis. The study also suggests that hierarchical (i.e., multi-level) specifications and subsetting do not necessarily perform better than a relatively simple single-level model with opponent-related factors. The results of this study provide insights regarding the performance of different modelling strategies, and should be informative to researchers in the field of crash severity. [ABSTRACT FROM AUTHOR]

Abstract: Recent advancements in computing and geographic information systems (GIS) have revolutionized the development of planning support systems (PSSs) to study and simulate the future of travel demand in urban areas. While travel demand models have been widely developed and used to inform the urban planning process, very little has been done to explicitly account for demographic changes and the ageing of population within such models. The work in this paper bridges this gap by describing the development and application of IMPACT (integrated model for population ageing consequences on transportation), a GIS-based PSS capable of assessing the ramifications of demographic changes, including population ageing, on the performance and usage of urban transportation systems. Unlike existing operational PSSs, IMPACT possesses unique and novel features that enable it to model demographic changes and urban travel demand for various age cohorts. Through the simulation of scenarios for varying fertility rates, the paper explores and quantifies the impacts of ageing and population age-structure changes on travel patterns in the census metropolitan area (CMA) of Hamilton in Ontario, Canada. The analysis suggests a consistent increase in the number of trips and mobility levels of elderly drivers, as a result of population ageing over time. Furthermore, increases in fertility rates could significantly impact the usage and performance of the transportation system for certain periods of the day, by the year 2031. Results such as these are important to consider when planning the future of cities. The findings in this paper provide new insights into the future of urban travel in the Canadian context. [Copyright &y& Elsevier]

The objective of this paper was to identify heterogeneities associated with the relationships between the body mass index (BMI) and individual as well as socio-environmental correlates at the individual- and area-levels. The data sources used were: (i) the 2003 Canadian Community Health Survey; (ii) the 2001 Canadian Census; and (iii) the Enhanced Points of Interest (EPOI) database from the Desktop Mapping Technologies Inc. Participants were adults (≥ 20 years; n = 12,836; based on a survey weight scheme N(weighted) = 5,418,218) from Toronto and Vancouver census metropolitan areas with no missing BMI records. In addition to conventional 1 km-buffers, we constructed activity-space-buffers to better assess the walkability and potentially increased BMI of individuals. Multi-level analysis was then applied to estimate the relative effects of both individual- and area-level risk-factors for increased BMI. The findings demonstrate a negative association between BMI and energy expenditure, mixed land uses, residential density and average value of dwellings, while a positive association was found with low educational attainment. Relationships were independent of individual characteristics such as age and ethnicity. Although the majority of the variation in these outcomes was found to be due to individual-level differences, this study did show significant differences at the area-level as well. The activity-space-buffers presented a vast improvement compared to the conventional 1 km-buffers. The results presented support the rationale that targeting high-risk individuals will only address a portion of the increasing BMI problem; it is essential to also address the characteristics of places that compel individuals to make unhealthy choices.

Background: Like other countries, Canada's population is aging, and the implications of this demographic change need to be better understood from the perspective of blood supply. Analysis of donor data will help to identify systematic patterns of donation and its correlates., Data: Geo-coded blood donor and donor clinic data are provided by Canadian Blood Services. Blood donor data is provided for the fiscal year 2006-2007 indicating the total number of donors for each Canadian postal code, excluding the province of Québec. Potential correlates of blood donation are selected based on social and economic characteristics, as well as descriptors of city size and geographical location in the urban hierarchy measures of accessibility, and capacity of donor clinics., Methods: Data is aggregated to n = 3,746 census tracts in 40 Census Metropolitan Areas (CMA) across the country. The number of donors per population in a census tract is regressed against the set of potential donation correlates. Autocorrelation is tested for and results adjusted to provide parsimonious models., Results: A number of factors are found to influence donation across the country, including the proportion of younger residents, English ability, proportion of people with immigrant status, higher education, and a population-based measure of accessibility., Conclusion: While a number of correlates of blood donation are observed across Canada, important contextual effects across metropolitan areas are highlighted. The paper concludes by looking at policy options that are aimed toward further understanding donor behaviour.