Using Simulations to Automatically Generate Authentic Constructivist Learning Environments

Abstract With increasingly short life-cycles, hand-crafting authentic constructivist environments for learning will become increasingly unfeasible. As the complexity of designed systems and devices increases, however, so does the role of simulations to support design. This paper presents an approach and an example of how naturally occurring simulations in design can be used to automatically generate authentic constructivist learning environments

Design and implementation of a low-cost classroom response system for a future classroom in the developing world

Economic considerations and lack of adequate infrastructure impose unique design constraints on future classrooms of the developing world. Thus, future classrooms in underprivileged nations may differ significantly from their counterparts in the developed world. Classroom response systems (CRS) are an emerging technology for the future classroom. CRS are wireless, hand-held devices that help students provide immediate feedback to questions posed by a teacher. In their present form, due to their relatively high cost and high infrastructural requirements, such systems are not sustainable in most developing countries. This paper presents the design and implementation of a CRS based on an open-source, low-cost, and easily manufactured hardware. The CRS design is based on a hybrid wireless/wired platform using Bluetooth with the 1-Wire networking technology. This design significantly reduces the cost, and is consistent with existing conditions in a typical developing country

Big Data Energy Management, Analytics and Visualization for Residential Areas

With the rapid development of IoT based home appliances, it has become a possibility that home owners share with Utilities in the management of home appliances energy consumption. Thus, the proposed work empowers home owners to manage their home appliances energy consumption and allow them to compare their consumption with respect to their local community total consumption. This serves as a nudge in consumer’s behavior to schedule their home appliances operation according to their local community consumption profile and trend. Utilizing the same common communication infrastructure, it also allows the utilities on different consumption levels (community, state, country) to monitor and visualize the energy consumption in their respective grid segments on daily, monthly, and yearly basis. A high-speed distributed computing cluster based on commodity hardware with efficient big data mathematical algorithm is employed in this work. To achieve this, two big data processing paradigms are evaluated with a set of qualitative and quantitative metrics with subsequent recommendations. One million smart meter data is simulated to access individual homes. With the utilization of distributed storage and computing cluster for handling energy big data, the utilities can perform consumer load analysis and visualization on a scale of one million consumers. This helps the utilities in providing consumers a more accurate representation of how much energy they are consuming with greater granularity and with respect to their local community. Consumer and Utility centric queries are developed to create a web-based real time energy consumption management system presented in terms of dashboard charts, graphs, and reports that can be accessed by the consumer and utility providers remotely