Kesan penggunaan prosedur pembelajaran kawalan kendiri (self-regulated learning) terhadap pencapaian akademik, kemahiran meta kognitif dan motivasi pelajar politeknik : kajian kes

Pembelajaran Kawalan Kendiri (PKK) merupakan satu strategi pembelajaran efektif yang membantu pelajar untuk kompeten dan mempunyai autonomi dalam diri. Namun, prosedur yang betul bagi mengaplikasikan PKK masih memerlukan penambahbaikan disebabkan oleh pelajar cepat bosan belajar subjek teori. Pelajar juga didapati mengamalkan surface learning, mudah hilang fokus dalam kelas dan tidak cekap dalam mengawal kemahiran meta kognitif. Oleh itu, tujuan kajian ini dilaksanakan adalah untuk membangunkan satu prosedur PKK khusus untuk pelajar politeknik yang mengambil subjek Prinsip Pengurusan dan diuji keberkesanannya terhadap pencapaian akademik, kemahiran meta kognitif dan motivasi pelajar. Terdapat dua (2) fasa telah digunakan dalam kajian ini. Fasa pertama (1) ialah pembangunan prosedur PKK menggunakan analisis dokumen dan model Kemp. Analisis frekuensi telah digunakan dalam fasa ini. Terdapat tiga (3) hasil dapatan kajian daripada fasa pembangunan iaitu Prosedur PKK, Aktiviti Pengajaran dan Rancangan Pengajaran Harian (RPH). Fasa kedua (2) ialah pelaksanaan prosedur PKK menggunakan reka bentuk kuasi eksperimen iaitu ujian pra-pasca bagi kumpulan-kumpulan tidak seimbang. 43 orang pelajar Politeknik Sultan Haji Ahmad Shah (POLISAS) telah dipilih sebagai kumpulan rawatan manakala 38 orang pelajar Politeknik Merlimau (PMM) sebagai kumpulan kawalan. Analisis deskriptif skor min dan analisis inferensi MANCOVA telah digunakan dalam kajian ini bagi menguji perbezaan antara kumpulan kajian. Berdasarkan hasil analisis MANCOVA yang telah dijalankan, didapati wujud perbezaan yang signifikan secara statistik antara kumpulan rawatan dan kawalan bagi pencapaian akademik [F (1, 76) = 24.786, p = .000], kemahiran meta kognitif [F (1, 76) = 14.864, p = .000] dan motivasi [F (1, 76) = 65.148, p = .000]. Kesimpulannya, prosedur PKK terbukti berkesan dan boleh dijadikan panduan kepada pensyarah dalam mengaplikasikan PKK dengan lebih efektif dan berkesan

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.

AI, Robotics, and the Future of Jobs

This report is the latest in a sustained effort throughout 2014 by the Pew Research Center's Internet Project to mark the 25th anniversary of the creation of the World Wide Web by Sir Tim Berners-Lee (The Web at 25).The report covers experts' views about advances in artificial intelligence (AI) and robotics, and their impact on jobs and employment

Aerospace Manufacturing Industry: A Simulation-Based Decision Support Framework for the Scheduling of Complex Hoist Lines

The hoist scheduling problem is a critical issue in the design and control of Automated Manufacturing Systems. To deal with the major complexities appearing in such problem, this work introduces an advanced simulation model to represent the short-term scheduling of complex hoist lines. The aim is to find the best jobs schedule that minimizing the makespan while maximizing throughput with no defective outputs. Several hard constraints are considered in the model: single shared hoist, heterogeneous recipes, eventual recycles flows, and no buffers between workstations. Different heuristic-based strategies are incorporated into the computer model in order to improve the solutions generated over time. The alternative solutions can be quickly evaluated by using a graphical user interface developed together with the simulation model.Fil: Basán, Natalia Paola. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Pulido, Raul. Universidad Politécnica de Madrid; EspañaFil: Coccola, Mariana Evangelina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentin

Limits on Fundamental Limits to Computation

An indispensable part of our lives, computing has also become essential to industries and governments. Steady improvements in computer hardware have been supported by periodic doubling of transistor densities in integrated circuits over the last fifty years. Such Moore scaling now requires increasingly heroic efforts, stimulating research in alternative hardware and stirring controversy. To help evaluate emerging technologies and enrich our understanding of integrated-circuit scaling, we review fundamental limits to computation: in manufacturing, energy, physical space, design and verification effort, and algorithms. To outline what is achievable in principle and in practice, we recall how some limits were circumvented, compare loose and tight limits. We also point out that engineering difficulties encountered by emerging technologies may indicate yet-unknown limits.Comment: 15 pages, 4 figures, 1 tabl

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested