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022_000145/0000

Algorythmics: Technologically and Artistically Enhanced Computer Science Education

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Zoltán Kátai
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Sapientia Books. Natural Sciences
022_000145/0030
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022_000145/0030

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30 2 MULTI-SENSORY COMPUTER SCIENCE EDUCATION 2.6 On the role of senses in education Some conclusions of the above-presented research that had supported our expectation that the multi-sensory methods we designed have potential to enhance the teaching-learning process of computer algorithms are: — The brain is organized to elaborate information, coming from the different sensory channels, cooperatively. — Visual, auditory, and reasoning processes are interconnected. — Multi-sensory structured methods have cognitive benefits. — More senses mean more efficient teaching-learning process because: ¢ more senses — more information, ¢ different students — different dominant senses, e different students — different “intelligences”, * multiple senses — more pathways of locating the stored information, * multiple senses — distributed loading, * combined senses — more efficient learning process. Consistent with these findings, Stevens and Goldberg (2001) stated that two of the core principles of brain-based learning are our brains’ desire for multi-sensory input; learning engages the whole body. Researchers emphasize that senses reach not only our feelings, emotions, and aesthetic sense but our intellect as well. In the opinion of medical neuroscientist Dave Warner, the traditional forms of information representation have been “perceptually deficient”, meaning that even multimedia digital content fails to consider “the extraordinary capacity of our brain to capture and process information from [all of] our senses” (Staley, 2006). According to Hung (2003), the recent findings in neuroscience have immediate implications for higher-level thinking skills (abstract problem solving, inference, deduction, and so on). The didactical methods and software tools we are going to present explore these principles. The following expressions from the educational materials we created illustrate the key role of arts in the presented methods: dancing algorithms, the melody line of the recursion, playing recursive scenarios, rhythm of the algorithms, drumming-in algorithm skeletons, piano accompanying the algorithms, etc. We believe that our effort to enrich blended/hybrid learning with multi-sensory elements implemented through arts has resulted in a kind of cocktail of learning. Like a cocktail drink, the resulted teaching-learning strategies are characterized by multiple variegations and are both instructive (nutritious) and fun (exciting).

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