Search

A frequent concern about constructivist instruction is that it works well, mainly for students with higher domain knowledge. We present findings from a set of two quasi-experimental pretest-intervention-posttest studies investigating the relationship between prior math achievement and learning in the context of a specific type of constructivist instruction, Productive Failure. Students from two Singapore public schools with significantly different prior math achievement profiles were asked to design solutions to complex problems "prior" to receiving instruction on the targeted concepts. Process results revealed that students who were significantly dissimilar in prior math achievement seemed to be strikingly similar in terms of their inventive production, that is, the variety of solutions they were able to design. Interestingly, it was inventive production that had a stronger association with learning from PF than pre-existing differences in math achievement. These findings, consistent across both topics, demonstrate the value of engaging students in opportunities for inventive production while learning math, regardless of prior math achievement.

A frequent concern about constructivist instruction is that it works well, mainly for students with higher domain knowledge. We present findings from a set of two quasi-experimental pretest-intervention-posttest studies investigating the relationship between prior math achievement and learning in the context of a specific type of constructivist instruction, Productive Failure. Students from two Singapore public schools with significantly different prior math achievement profiles were asked to design solutions to complex problems prior to receiving instruction on the targeted concepts. Process results revealed that students who were significantly dissimilar in prior math achievement seemed to be strikingly similar in terms of their inventive production, that is, the variety of solutions they were able to design. Interestingly, it was inventive production that had a stronger association with learning from PF than pre-existing differences in math achievement. These findings, consistent across both topics, demonstrate the value of engaging students in opportunities for inventive production while learning math, regardless of prior math achievement. [ABSTRACT FROM AUTHOR]

We develop a new model for urban wind corridors analysis and detection of urban wind ventilation potential based on concepts and principles of network theory. Our approach is based solely on data extracted from spatial urban features that are easily obtained from a 3D model of the city. Once the spatial features have been extracted, we embed them onto a graph topology. This allows us to use theories and techniques of network theory, and in particular graph theory. Utilizing such techniques, we perform end-to-end network flow analysis of the wind potential across the city and, in particular, estimate the locations, strengths, and paths of the wind corridors. To calibrate our model, we use a dataset generated by a meso-scale climate model and estimate the model parameters by projecting the wind vector field of the climate model onto a graph, thus providing a meaningful comparison of the two models under a new metric. We illustrate our modeling approach on the city of Singapore and explain how the results are useful for climate-informed urban design. [ABSTRACT FROM AUTHOR]

We develop a new framework for selecting an urban design which performs best from an Outdoor Thermal Comfort (OTC) perspective, while taking into account the uncertainty in the OTC preference of individuals. To this end, we first present and develop the notion of Probabilistic Acceptability Criterion (PAC) which is a new method to quantify people's satisfaction of OTC values, based on data collected from a survey. We develop the PAC for both regression and classification models which are most common statistical analysis methods in the literature. Next, based on the PAC, we develop a new approach to scoring each of the urban designs, based on Binary Probabilistic Impact Function, which extends the widely used deterministic impact function. We show that the score is a random variable which follows a Poisson-Binomial distribution and characterise its parameters. We then use those results and present a new approach for scoring of the urban designs that is based on the Sharpe ratio, which is a widely used metric in financial applications. Our framework is the first model which provides urban designers the ability to evaluate the quality of their urban designs from an OTC point of view, while taking the uncertainty into account in a holistic and rigorous way. We illustrate our framework by applying it to a real case study in Singapore. [ABSTRACT FROM AUTHOR]

We develop a novel statistical decision-theoretic framework for urban design from an outdoor thermal comfort (OTC), social and economic perspectives. We combine those aspects into spatio-temporal risk measures which provide a compact representation of the overall quality of an urban design scenarios (UDS) set. We then formulate the selection of the optimal design as an optimization problem which is easy to solve and has a clear interpretation. To illustrate how our framework can be used in practice, we present a real-world study, which is based on a set of UDS that aim to improve the OTC of a specific site in Singapore. We show how our framework provides decision makers the flexibility to make choices relevant to their design objectives, leading to informed and interpretable design option selection. [ABSTRACT FROM AUTHOR]

In this paper we combine statistical modelling and climate models in order to develop a unified statistical framework for quantifying the Urban Heat Footprint (UHF) effect, thus quantifying the urban warming phenomenon. The UHF quantifies the urban warming at any location in the spatio-temporal domain due to different effects, such as anthropogenic effects and climatic effects. These effects can be controlled and configured by our modelling approach, thus allowing the evaluation of different scenarios of interest. We first provide a definition of UHF followed by definitions of the Anthropogenic Effects (AE) components. Then, based on those definitions, we define the fundamental quantity of UHF spatial-temporal stochastic (random) processes. Next, we propose several metrics for quantifying and summarising the UHF, which are statistical estimators. These provide insightful summaries of the population parameters of the UHF stochastic process, and can be easily calculated in practice. To illustrate how our framework can be used, we utilise a Weather Research and Forecasting (WRF) model, and provide detailed examples of various UHF metrics, based on real data of Singapore. [ABSTRACT FROM AUTHOR]