Executive SummaryAn important aspect of education is to promote higher-order thinking skills to learners. However, in the lecture environment, learners are passively engaged and it is unlikely for higher-order thinking to occur. Although interventions such as "clickers" can be used to increase engagement in lectures, this does not necessarily promote higher-order thinking. Approaches such as collaborative learning are better suited for this but there is little room to use such methods in the short time frame of a lecture.With recent advances in the capabilities of smart mobile devices and their growing penetration rate among the student cohort, it is possible to take advantage of these devices to design a system to promote higher-order thinking skills in the lecture environment.We present the design of a mobile-app-based collaborative learning system named myVote and a process for its usage. Our aim is to present a theoretical paper that discusses the relevant learning theories used in designing the system as well as describe a process to use the system to achieve collaborative learning at varying levels of thinking.We demonstrate the usefulness and flexibility of the system through three scenarios involving different levels of thinking, ranging from lower-to higher-order. Although the scenarios are in the context of IT education, the system is versatile enough to be adapted for education in general and also non-educational settings, such as business-like environments.Our contribution is a framework for using mobile apps and collaborative learning theories within a lecture environment to encourage higher-order thinking in learners.Although a potential limitation of the system is that it may not be appropriate for teaching more technical IT materials, such as programming and SQL code snippets, the problem can be recasted in a different format such as pseudocode in order to facilitate teaching in these areas.Keywords: higher-order thinking skills, collaborative learning, smartphones, computer-support collaborative learning, Delphi survey, mobile app IntroductionCollaborative learning is a group-based learning approach in which learners are mutually engaged in a coordinated fashion to achieve a learning goal or complete a learning task (Dillenbourg, Baker, Blaye, & O'Malley, 1996). Collaborative learning centers on a socialMaterial published as part of this publication, either on-line or in print, is copyrighted by the Informing Science Institute. Permission to make digital or paper copy of part or all of these works for personal or classroom use is granted without fee provided that the copies are not made or distributed for profit or commercial advantage AND that copies 1) bear this notice in full and 2) give the full citation on the first page. It is permissible to abstract these works so long as credit is given. To copy in all other cases or to republish or to post on a server or to redistribute to lists requires specific permission and payment of a fee. Contact Publisher@InformingScience.org to request redistri...
Fuzzy logic controllers (FLCs) are gaining in popularity across a broad array of disciplines because they allow a more human approach to control. Recently, the design of the fuzzy sets and the rule base has been automated by the use of genetic algorithms (GAs) which are powerful search techniques. Though the use of GAs can produce near optimal FLCs, it raises problems such as messy overlapping of fuzzy sets and rules not in agreement with common sense. This paper describes an enhanced genetic algorithm which constrains the optimization of FLCs to produce well-formed fuzzy sets and rules which can be better understood by human beings. To achieve the above, we devised several new genetic operators and used a parallel GA with three populations for optimizing FLCs with 3x3, 5x5, and 7x7 rule bases, and we also used a novel method for creating migrants between the three populations of the parallel GA to increase the chances of optimization. In this paper, we also present the results of applying our GA to designing FLCs for controlling three different plants and compare the performance of these FLC's with their unconstrained counterparts.
Applying the engaging and motivating aspects of video games in non-game contexts is known as gamification. Education can benefit from gamification by improving the learning environment to make it more enjoyable and engaging for students. Factors that influence students’ preference for use of gamification are identified. Students are surveyed on their experiences of playing a gamified quiz, named Quick Quiz, during class. Quick Quiz features several gamification elements such as points, progress bars, leader boards, timers, and charts. Data collected from the survey is analysed using Partial Least Squares. Factors including ‘usefulness’, ‘preference for use’, ‘knowledge improvement’, ‘engagement’, ‘immersion’ and ‘enjoyment’ were found to be significant determinants. Students were found to have a preference for use for gamification in their learning environment.
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