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Article Oyun ve Oyuncak Tasarımı(Herkese Bilim Teknoloji, 2017) Ünal, BülentÇocuklar, çok erken yaştan itibaren çevre hakkında bir şeyler öğrenmek için oyunu birincil araç olarak kullanırlar. Oyun sadece çocukların dünyayı nasıl anladığını yansıtmakla kalmaz, aynı zamanda sosyal, duygusal, fiziksel gelişimlerini ve problem çözme becerilerini artırmak için fırsatlar sağlar (Lopez, 2012). Oyunun avantajları ne olabilir? Pek çok türün gençleri arasında var olan bir davranışın evrimsel bir avantajı olmalıdır, aksi takdirde bu türler 'doğal seleksiyon' yoluyla ortadan kaldırılırdı. Oyun, beyin gelişimini ve büyümesini arttırır, yeni sinir bağlantıları kurar ve bir bakıma oyuncuyu daha akıllı yapar. Başkalarının duygusal durumunu algılama ve değişen koşullara uyum yeteneğini geliştirir. Yetişkin beyinleri de yeni sinir devrelerini geliştirme ve öğrenme yeteneğine sahip olduğu için, yetişkinlerin de oynamaya devam etmesi önerilmektedir (Goldstein, 2012).Article Ore-Age: an Intelligent Tutoring System Model for Mining Method Selection(The International Journal of Mineral Resources Engineering, 2008) Güray, CenkMining method selection is a critical decision for an economic, safe productive mining work. Each orebody is unique with its own properties and engineering judgment has a great effect on the decisions. In this study an intelligent assisting and tutoring system for preliminary underground mining method selection is developed. This systems is called Ore-Age, whose goal is making the preliminary mining method selection as effeciently as posssible too while giving them a remarkable education on mining method selection. Due to its semi-autonomous character, Ore-Age determşnes to direct its execution strategy based on the expertise levels od the users. Ore-Age acts as an assisting tool for the experienced engineers during the selection process and continuously looks for the help of its neuro-fuzzy learning algorithm. The reason of Ore-Age to take this learning procedure is to imitate and behave like these experts during his future selections. Besides this ability, Ore-Age tries to act as a tutoring system as efficiently as possible when he faces inexperienced engineers. The regular strategy of teaching process depends on an iterative algorithm checking the decisive concepts one by one to find the point of misconception leading to wrong selection. Furthermore as an alternative strategy, by his error modeling property, Ore-Age can alter hhis strategy and concentrate the users directly to the possible points of misconception, without using the previous "time demanding" algorithm. This system aiming the model thecognitive behaviour of the student is an indication of the reactive characteristic of the system that can alter the strategies based on his own logical decison to achieve a more efficient tutoring procedure. The system that is being developed in this study can be introduced as the first example of dynamic, intelligent assisting and tutoring systems in the mining profession.Conference Object Citation - WoS: 2Citation - Scopus: 5Selection of Working Area for Industrial Engineering Students(Elsevier Science Bv, 2012) Rouyendegh, Babak Daneshvar; Can, Gulin FeryalSelection of working area is one of the most important turning points in the human life. The main purpose of the selection of working area is planning a happy and successful future. There are many factors that interact with one another in this decision making process. In this study, in the content of these factors; feeling interest of lessons took in university education period, career opportunities for various working areas and gender are examined for 14 industrial engineering working areas. In addition, the scope of this study, we used Fuzzy Analytic Network Process (FANP) method to analyze these criteria and to determine the work areas wanted to work by industrial engineering students in order of priority.
