Application of VARK learning model on “Data Structures and Algorithms” course

Stojanova, Aleksandra and Stojkovic, Natasa and Kocaleva, Mirjana and Zlatanovska, Biljana and Martinovska Bande, Cveta (2017) Application of VARK learning model on “Data Structures and Algorithms” course. In: IEEE Global Engineering Education Conference (EDUCON), 25-28 Apr 2017, Athens, Greece.

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The process of learning and understanding can be different for each person. The teaching methods are particularly important for students to learn the curriculum, because not every student can learn the teaching material in the same way. Some students can easily learn if they listen the information, others use videos presentations and graphs for better learning and there are students who learn through practical examples. This paper presents VARK (Visual, Aural, Reading or Write and Kinesthetic) model as an effective learning style. The learning model is applied in the Data structures and algorithms course. Data Structure and Algorithms is a fundamental course in Computer Science, but many students find it difficult because it requires abstract thinking. For this reason, except traditional way of explaining (reading/listening), using visualization tool, watching videos and animations is very helpful. At the University "Goce Delchev" teaching of the subject Data Structures and Algorithms contains: classroom lectures, classroom problem solving exercises and laboratory exercises. Classroom lectures are performed by using only listening and reading methods. On classroom problem solving exercises, students watch videos or animations that are some kind of java applets or Flash elements that illustrate the basic operation in data structure. On laboratory exercises, students use programs for software visualization and have opportunity to write parts of code by their own. This way of combined learning increases overall study experience and improve student success. This method has significant positive effect on students.

Item Type: Conference or Workshop Item (Speech)
Subjects: Natural sciences > Computer and information sciences
Divisions: Faculty of Computer Science
Depositing User: Mirjana Kocaleva
Date Deposited: 15 May 2017 09:05
Last Modified: 27 Jun 2017 13:11

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