Keberkesanan modul infusi kemahiran berfikir aras tinggi pembelajaran luar bilik darjah (iKBAT-PLBD) bagi bidang pembelajaran sukatan dan geometri

Kemahiran berfikir aras tinggi (KBAT) merupakan satu kemahiran berfikir yang sangat diperlukan dalam mendepani cabaran kehidupan masa kini terutama dalam bidang matematik. Oleh itu, kajian ini dijalankan untuk mengkaji sama ada KBAT matematik pelajar dapat ditingkatkan dengan menggunakan modul infusi Kemahiran Berfikir Aras Tinggi - Pembelajaran Luar Bilik Darjah (iKBAT–PLBD) atau tidak? Justeru itu, satu kerangka perancangan telah dibuat terhadap empat kemahiran tertinggi dalam Taksonomi Bloom semakan semula yang juga merupakan konstruk utama dalam KBAT. Konstruk KBAT tersebut ialah konstruk menganlisis, mengaplikasi menilai dan mencipta. Sampel kajian ini melibatkan 120 pelajar tingkatan 1 di empat buah sekolah yang berbeza di negeri Johor. Dalam menjalankan kajian kuasi eksperimental ini, data dikumpul melalui kajian keputusan ujian pra dan ujian pos sebelum dan selepas menggunakan modul bagi kumpulan rawatan. Manakala pendekatan PdP tradisional pula digunakan bagi kumpulan kawalan. Hasil daripada analisis data menunjukkan bahawa aktiviti pembelajaran dan pemudahcaraan (PdPc) yang bertunjangkan modul iKBAT–PLBD telah dapat meningkatkan penguasaan matematik pelajar dalam kempat-empat tahap KBAT serta bagi keseluruhan tahap. Dapatan kajian ini menunjukkan terdapat perbezaan yang signifikasi antara kumpulan kawalan dan kumpulan rawatan terhadap peningkatan KBAT pelajar dalam matematik dengan menggunakan pendekatan iKBAT–PLBD bagi tahap mengaplikasi, menganalisis, menilai, mencipta juga secara keseluruhan. Kesimpulannya, kajian ini dapat memberi manfaat kepada semua pihak termasuk pihak Kementerian Pendidikan Malaysia (KPM), pihak pentadbiran sekolah, ibubapa, guru matematik malah bagi pelajar itu dari segi pengubalan dasar yang berkaitan, pengaplikasian dan sebagai satu bukti keberkesanan dalam proses pemerkasaan KBAT matematik di Malaysia

User-friendly Support for Common Concepts in a Lightweight Verifier

Machine verification of formal arguments can only increase our confidence in the correctness of those arguments, but the costs of employing machine verification still outweigh the benefits for some common kinds of formal reasoning activities. As a result, usability is becoming increasingly important in the design of formal verification tools. We describe the "aartifact" lightweight verification system, designed for processing formal arguments involving basic, ubiquitous mathematical concepts. The system is a prototype for investigating potential techniques for improving the usability of formal verification systems. It leverages techniques drawn both from existing work and from our own efforts. In addition to a parser for a familiar concrete syntax and a mechanism for automated syntax lookup, the system integrates (1) a basic logical inference algorithm, (2) a database of propositions governing common mathematical concepts, and (3) a data structure that computes congruence closures of expressions involving relations found in this database. Together, these components allow the system to better accommodate the expectations of users interested in verifying formal arguments involving algebraic and logical manipulations of numbers, sets, vectors, and related operators and predicates. We demonstrate the reasonable performance of this system on typical formal arguments and briefly discuss how the system's design contributed to its usability in two case studies

NETMAT: A knowledge-based grid system analysis tool

The increasing expansion of electric power systems renders the power system operator's task increasingly complex. The integration into energy management systems of further analytical algorithms implies that more data has to be analysed by the control engineer. For these reasons and many others, more sophisticated tools are required by power engineers to ease the pressure under which they perform their task. The advent of knowledge-based systems has led to a new approach to the problem. The combination of expert systems and numerical algorithms can be advantageously exploited to assist the power system engineer in operating the system. This paper presents the development of a knowledge-based tool for grid system analysis. The tool, NETMAT (NETwork Modelling AssistanT) , is to be used to analyse the impact of grid system maintenance and modification procedures and of new generating plants on power utilities, and in particular on their ability to generate and sell electricity. NE TMAT consists of a number of numerical applications interfaced to an expert system shell through specific problem domain knowledge bases. Results are presented based on the use of the IEEE-30 busbar network as a test network

An eco-friendly hybrid urban computing network combining community-based wireless LAN access and wireless sensor networking

Computer-enhanced smart environments, distributed environmental monitoring, wireless communication, energy conservation and sustainable technologies, ubiquitous access to Internet-located data and services, user mobility and innovation as a tool for service differentiation are all significant contemporary research subjects and societal developments. This position paper presents the design of a hybrid municipal network infrastructure that, to a lesser or greater degree, incorporates aspects from each of these topics by integrating a community-based Wi-Fi access network with Wireless Sensor Network (WSN) functionality. The former component provides free wireless Internet connectivity by harvesting the Internet subscriptions of city inhabitants. To minimize session interruptions for mobile clients, this subsystem incorporates technology that achieves (near-)seamless handover between Wi-Fi access points. The WSN component on the other hand renders it feasible to sense physical properties and to realize the Internet of Things (IoT) paradigm. This in turn scaffolds the development of value-added end-user applications that are consumable through the community-powered access network. The WSN subsystem invests substantially in ecological considerations by means of a green distributed reasoning framework and sensor middleware that collaboratively aim to minimize the network's global energy consumption. Via the discussion of two illustrative applications that are currently being developed as part of a concrete smart city deployment, we offer a taste of the myriad of innovative digital services in an extensive spectrum of application domains that is unlocked by the proposed platform

Requirements modelling and formal analysis using graph operations

The increasing complexity of enterprise systems requires a more advanced analysis of the representation of services expected than is currently possible. Consequently, the specification stage, which could be facilitated by formal verification, becomes very important to the system life-cycle. This paper presents a formal modelling approach, which may be used in order to better represent the reality of the system and to verify the awaited or existing system’s properties, taking into account the environmental characteristics. For that, we firstly propose a formalization process based upon properties specification, and secondly we use Conceptual Graphs operations to develop reasoning mechanisms of verifying requirements statements. The graphic visualization of these reasoning enables us to correctly capture the system specifications by making it easier to determine if desired properties hold. It is applied to the field of Enterprise modelling

User-centered visual analysis using a hybrid reasoning architecture for intensive care units

One problem pertaining to Intensive Care Unit information systems is that, in some cases, a very dense display of data can result. To ensure the overview and readability of the increasing volumes of data, some special features are required (e.g., data prioritization, clustering, and selection mechanisms) with the application of analytical methods (e.g., temporal data abstraction, principal component analysis, and detection of events). This paper addresses the problem of improving the integration of the visual and analytical methods applied to medical monitoring systems. We present a knowledge- and machine learning-based approach to support the knowledge discovery process with appropriate analytical and visual methods. Its potential benefit to the development of user interfaces for intelligent monitors that can assist with the detection and explanation of new, potentially threatening medical events. The proposed hybrid reasoning architecture provides an interactive graphical user interface to adjust the parameters of the analytical methods based on the users' task at hand. The action sequences performed on the graphical user interface by the user are consolidated in a dynamic knowledge base with specific hybrid reasoning that integrates symbolic and connectionist approaches. These sequences of expert knowledge acquisition can be very efficient for making easier knowledge emergence during a similar experience and positively impact the monitoring of critical situations. The provided graphical user interface incorporating a user-centered visual analysis is exploited to facilitate the natural and effective representation of clinical information for patient care