ARCS model is a motivational design model for learning environments to stimulate and sustain learner motivation using the problem-solving approach. The ARCS model often used to identify and solve problems in a systematic way to motivate a learner in classroom learning or e-learning environment. The gamification of learning provides a useful technique to drive engagement and motivation in applying game mechanics and dynamics into learning activities. In spite of the success of gamification of learning, there are also failures. The proper method is needed to integrate gamification into learning. In this paper, we propose an enhanced ARCS model for gamification of learning called ARCS+G. The ARCS+G model is aimed to provide a solution for the problems in utilizing gamification of learning.

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Association rule is one of the data mining techniques involved in discovering information that represents the association among data. Data in the database sometimes appear infrequent but highly associated with a specific data. This paper proposes a technique for significant rare data by introducing second support in discovering the association rules of such data. We show that the proposed approach provides better performance as compared to standard association rules techniques.

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