BIMing the architectural curricula: integrating Building Information Modelling (BIM) in architectural education

Building Information Modelling (BIM) reflects the current heightened transformation within the Architectural, Engineering and Construction (AEC) Industry and the Facilities and Management (FM) sector, offering a host of benefits from increased efficiency, accuracy, speed, co-ordination, consistency, energy analysis, project cost reduction etc to various stake holders from owners to architects, engineers, contractors and other built environment professionals. Many countries around the world are responding to this paradigm shift including the United Kingdom (UK). The Cabinet office took the decision in 2011 to make the use of collaborative 3D BIM technology mandatory for all public sector construction contracts by 2016 (Cabinet Office, 2011). According to Smith and Tardif, despite certain myths and misconceptions surrounding BIM, its rate of implementation has been much faster in comparison to the availability of professionals skilled in use of BIM, thus creating a skill gap in the design and construction industry (Smith and Tardif, cited in Barison and Santos, 2010a). This article aims at bridging the gap between the graduate skill sets and the changing needs of the profession. The research methodology adopted consists of thoroughly reviewing the existing literature in this subject area coupled with carrying out a survey of accredited Schools of Architecture in the UK. The analysis of the survey questionnaire results shows the extent to which BIM is currently being taught and identifies the barriers where its implementation has either been slow or not yet started. The paper highlights the fact that there has been considerable delay in the successful integration of BIM in the Schools of Architecture in the UK, thus emphasising the need for expeditiously training and preparing students in the use of BIM making them ready to effectively perform in a BIM enabled work arena

Understanding Student Computational Thinking with Computational Modeling

Recently, the National Research Council's framework for next generation science standards highlighted "computational thinking" as one of its "fundamental practices". 9th Grade students taking a physics course that employed the Modeling Instruction curriculum were taught to construct computational models of physical systems. Student computational thinking was assessed using a proctored programming assignment, written essay, and a series of think-aloud interviews, where the students produced and discussed a computational model of a baseball in motion via a high-level programming environment (VPython). Roughly a third of the students in the study were successful in completing the programming assignment. Student success on this assessment was tied to how students synthesized their knowledge of physics and computation. On the essay and interview assessments, students displayed unique views of the relationship between force and motion; those who spoke of this relationship in causal (rather than observational) terms tended to have more success in the programming exercise.Comment: preprint to submit to PERC proceedings 201

A Multi-Gene Genetic Programming Application for Predicting Students Failure at School

Several efforts to predict student failure rate (SFR) at school accurately still remains a core problem area faced by many in the educational sector. The procedure for forecasting SFR are rigid and most often times require data scaling or conversion into binary form such as is the case of the logistic model which may lead to lose of information and effect size attenuation. Also, the high number of factors, incomplete and unbalanced dataset, and black boxing issues as in Artificial Neural Networks and Fuzzy logic systems exposes the need for more efficient tools. Currently the application of Genetic Programming (GP) holds great promises and has produced tremendous positive results in different sectors. In this regard, this study developed GPSFARPS, a software application to provide a robust solution to the prediction of SFR using an evolutionary algorithm known as multi-gene genetic programming. The approach is validated by feeding a testing data set to the evolved GP models. Result obtained from GPSFARPS simulations show its unique ability to evolve a suitable failure rate expression with a fast convergence at 30 generations from a maximum specified generation of 500. The multi-gene system was also able to minimize the evolved model expression and accurately predict student failure rate using a subset of the original expressionComment: 14 pages, 9 figures, Journal paper. arXiv admin note: text overlap with arXiv:1403.0623 by other author

Teaching and learning trigonometry with technology

Modern school classrooms have access to a range of potential technologies, ranging from calculators to computers to the Internet. This paper explores some of the potential for such technologies to affect the curriculum and teaching of trigonometry in the secondary school. We identify some of the ways in which the teaching of trigonometry might be supported by the availability of various forms of technology. We consider circular measures, graphs of functions, trigonometric identities, equations and statistical modeling and focus on activities that are not possible without the use of technology. Modern technology provides an excellent means of exploring many of the concepts associated with trigonometry, both trigonometric and circular functions. Many of these opportunities for learning were not available before technology development and access within schools we enjoy today. This paper suggests some of the avenues for exploration