Learning and Games

Part of the Volume on the Ecology of Games: Connecting Youth, Games, and Learning In this chapter, I argue that good video games recruit good learning and that a game's design is inherently connected to designing good learning for players. I start with a perspective on learning now common in the Learning Sciences that argues that people primarily think and learn through experiences they have had, not through abstract calculations and generalizations. People store these experiences in memory -- and human long-term memory is now viewed as nearly limitless -- and use them to run simulations in their minds to prepare for problem solving in new situations. These simulations help them to form hypotheses about how to proceed in the new situation based on past experiences. The chapter also discusses the conditions experience must meet if it is to be optimal for learning and shows how good video games can deliver such optimal learning experiences. Some of the issues covered include: identity and learning; models and model-based thinking; the control of avatars and "empathy for a complex system"; distributed intelligence and cross-functional teams for learning; motivation, and ownership; emotion in learning; and situated meaning, that is, the ways in which games represent verbal meaning through images, actions, and dialogue, not just other words and definitions

Coupled TRNSYS-CFD simulations evaluating the performance of PCM plate heat exchangers in an Airport Terminal building displacement conditioning system

This is the post-print version of the Article. The official published version can be accessed from the link below. Copyright @ 2013 Elsevier.This paper reports on the energy performance evaluation of a displacement ventilation (DV) system in an airport departure hall, with a conventional DV diffuser and a diffuser retrofitted with a phase change material storage heat exchanger (PCM-HX). A TRNSYS-CFD quasi-dynamic coupled simulation method was employed for the analysis, whereby TRNSYS® simulates the HVAC and PID control system and ANSYS FLUENT® is used to simulate the airflow inside the airport terminal space. The PCM-HX is also simulated in CFD, and is integrated into the overall model as a secondary coupled component in the TRNSYS interface. Different night charging strategies of the PCM-HX were investigated and compared with the conventional DV diffuser. The results show that: i) the displacement ventilation system is more efficient for cooling than heating a space; ii) the addition of a PCM-HX system reduces the heating energy requirements during the intermediate and summer periods for specific night charging strategies, whereas winter heating energy remains unaffected; iii) the PCM-HX reduces cooling energy requirements, and; iv) maximum energy savings of 34% are possible with the deployment of PCM-HX retrofitted DV diffuser.This work was funded by the UK Engineering and Physical Sciences Research Council (EPSRC), Grant No: EP/H004181/1

Multiradio sensing systems for home area networking and building management

Many WSN systems use proprietary systems so interoperability between different devices and systems can be at best difficult with various protocols (standards based and non-standards based) used (ZigBee, EnOcean, MODBUS, KNEX, DALI, Powerline, etc.). This work describes the development of a novel low power consumption multiradio system incorporating 32-bit ARM-Cortex microcontroller and multiple radio interfaces - ZigBee/6LoWPAN/Bluetooth LE (Low Energy)/868MHz platform. The multiradio sensing system lends itself to interoperability and standardization between the different technologies which typically make up a heterogeneous network of sensors for both standards based and non-standards based systems. The configurability of the system enables energy savings, and increases the range between single points enabling the implementation of adaptive networking architectures of different configurations. The system described provides a future-proof wireless platform for Home Automation Networks with regards to the network heterogeneity in terms of hardware and protocols defined as being critical for use in the built environment. This system is the first to provide the capability to communicate in the 2.4GHz band as well as the 868MHz band as well as the feature of multiboot capability

Multiradio, multiboot capable sensing systems for home area networking

The development of Wireless Sensor Networking technology to deploy in smart home environments for a variety of applications such as Home Area Networking has been the focus of commercial and academic interest for the last decade. Developers of such systems have not adopted a common standard for communications in such schemes. Many Wireless Sensor Network systems use proprietary systems so interoperability between different devices and systems can be at best difficult with various protocols (standards based and non-standards based) used (ZigBee, EnOcean, MODBUS, KNX, DALI, Powerline, etc.). This work describes the development of a novel low power consumption multiradio system incorporating 32-bit ARM-Cortex microcontroller and multiple radio interfaces - ZigBee/6LoWPAN/Bluetooth LE/868MHz platform. The multiradio sensing system lends itself to interoperability and standardization between the different technologies, which typically make up a heterogeneous network of sensors for both standards based and non-standards based systems. The configurability of the system enables energy savings, and increases the range between single points enabling the implementation of adaptive networking architectures of different configurations. The system described provides a future-proof wireless platform for Home Automation Networks with regards to the network heterogeneity in terms of hardware and protocols defined as being critical for use in the built environment. This system is the first to provide the capability to communicate in the 2.4GHz band as well as the 868MHz band as well as the feature of multiboot capability. A description of the system operation and potential for power savings through the use of such a system is provided. Using such a multiradio, multiboot capable, system can not only allow interoperability across multiple radio platforms in a Home Area Network, but can also increase battery lifetime by 20 – 25% in standard sensing applications

Sophisticated Batteryless Sensing

Wireless embedded sensing systems have revolutionized scientific, industrial, and consumer applications. Sensors have become a fixture in our daily lives, as well as the scientific and industrial communities by allowing continuous monitoring of people, wildlife, plants, buildings, roads and highways, pipelines, and countless other objects. Recently a new vision for sensing has emerged---known as the Internet-of-Things (IoT)---where trillions of devices invisibly sense, coordinate, and communicate to support our life and well being. However, the sheer scale of the IoT has presented serious problems for current sensing technologies---mainly, the unsustainable maintenance, ecological, and economic costs of recycling or disposing of trillions of batteries. This energy storage bottleneck has prevented massive deployments of tiny sensing devices at the edge of the IoT. This dissertation explores an alternative---leave the batteries behind, and harvest the energy required for sensing tasks from the environment the device is embedded in. These sensors can be made cheaper, smaller, and will last decades longer than their battery powered counterparts, making them a perfect fit for the requirements of the IoT. These sensors can be deployed where battery powered sensors cannot---embedded in concrete, shot into space, or even implanted in animals and people. However, these batteryless sensors may lose power at any point, with no warning, for unpredictable lengths of time. Programming, profiling, debugging, and building applications with these devices pose significant challenges. First, batteryless devices operate in unpredictable environments, where voltages vary and power failures can occur at any time---often devices are in failure for hours. Second, a device\u27s behavior effects the amount of energy they can harvest---meaning small changes in tasks can drastically change harvester efficiency. Third, the programming interfaces of batteryless devices are ill-defined and non- intuitive; most developers have trouble anticipating the problems inherent with an intermittent power supply. Finally, the lack of community, and a standard usable hardware platform have reduced the resources and prototyping ability of the developer. In this dissertation we present solutions to these challenges in the form of a tool for repeatable and realistic experimentation called Ekho, a reconfigurable hardware platform named Flicker, and a language and runtime for timely execution of intermittent programs called Mayfly

Examining Real Options Exercise Decisions in Information Technology Investments

Researchers have advocated real options thinking (ROT) for evaluating and managing risky IT investments to account for managerial decision flexibility. Effective ROT is a three-step process that requires managers to recognize, value, and exercise options embedded in IT projects. Prior research has illustrated the existence of managerial bias in the recognizing and valuing real options. However, little research has examined real options exercise decisions. Hence, we use prospect theory to examine whether IT managers demonstrate systematic biases while exercising real options in IT projects and portfolios. We also study whether one can control or mitigate such biases. We found evidence of biased (suboptimal) real option exercise decisions in IT projects and in IT portfolios. However, we found differences in biased decision making between a single project and a portfolio scenario. We also found that project scale and real option type influenced vulnerability of a project to biased decision making. In addition, simplifying the presentation of the net effects of real options exercise decisions can help reduce bias, especially for large project portfolios. We discuss the implications of these results on theory and practice

Sustainable Fault-handling Of Reconfigurable Logic Using Throughput-driven Assessment

A sustainable Evolvable Hardware (EH) system is developed for SRAM-based reconfigurable Field Programmable Gate Arrays (FPGAs) using outlier detection and group testing-based assessment principles. The fault diagnosis methods presented herein leverage throughput-driven, relative fitness assessment to maintain resource viability autonomously. Group testing-based techniques are developed for adaptive input-driven fault isolation in FPGAs, without the need for exhaustive testing or coding-based evaluation. The techniques maintain the device operational, and when possible generate validated outputs throughout the repair process. Adaptive fault isolation methods based on discrepancy-enabled pair-wise comparisons are developed. By observing the discrepancy characteristics of multiple Concurrent Error Detection (CED) configurations, a method for robust detection of faults is developed based on pairwise parallel evaluation using Discrepancy Mirror logic. The results from the analytical FPGA model are demonstrated via a self-healing, self-organizing evolvable hardware system. Reconfigurability of the SRAM-based FPGA is leveraged to identify logic resource faults which are successively excluded by group testing using alternate device configurations. This simplifies the system architect\u27s role to definition of functionality using a high-level Hardware Description Language (HDL) and system-level performance versus availability operating point. System availability, throughput, and mean time to isolate faults are monitored and maintained using an Observer-Controller model. Results are demonstrated using a Data Encryption Standard (DES) core that occupies approximately 305 FPGA slices on a Xilinx Virtex-II Pro FPGA. With a single simulated stuck-at-fault, the system identifies a completely validated replacement configuration within three to five positive tests. The approach demonstrates a readily-implemented yet robust organic hardware application framework featuring a high degree of autonomous self-control

Eco: A Hardware-Software Co-Design for In Situ Power Measurement on Low-end IoT Systems

Energy-constrained sensor nodes can adaptively optimize their energy consumption if a continuous measurement exists. This is of particular importance in scenarios of high dynamics such as energy harvesting or adaptive task scheduling. However, self-measuring of power consumption at reasonable cost and complexity is unavailable as a generic system service. In this paper, we present Eco, a hardware-software co-design enabling generic energy management on IoT nodes. Eco is tailored to devices with limited resources and thus targets most of the upcoming IoT scenarios. The proposed measurement module combines commodity components with a common system interfaces to achieve easy, flexible integration with various hardware platforms and the RIOT IoT operating system. We thoroughly evaluate and compare accuracy and overhead. Our findings indicate that our commodity design competes well with highly optimized solutions, while being significantly more versatile. We employ Eco for energy management on RIOT and validate its readiness for deployment in a five-week field trial integrated with energy harvesting