Teaching Algorithms to Develop the Algorithmic Thinking of Informatics Students

Abstract

Modernization and the ever-increasing trend of introducing modern technologies into various areas of everyday life require school graduates with programming skills. The ability to program is closely related to computational thinking, which is based on algorithmic thinking. It is well known that algorithmic thinking is the ability of students to work with algorithms understood as a systematic description of problem-solving strategies. Algorithms can be considered as a fundamental phenomenon that forms a point of contact between mathematics and informatics. As part of an algorithmic graph theory seminar, we conducted an experiment where we solved the knight’s tour problem using the backtracking method to observe the change in students’ motivation to learn algorithms at a higher cognitive level. Seventy-four students participated in the experiment. Statistical analysis of the results of the experiment confirmed that the use of the algorithm with decision-making in teaching motivated students to learn algorithms with understanding.

Could You Understand Me? The Relationship among Method Complexity, Preprocessing Complexity, Interpretability, and Accuracy

“…Since we have categorized machine learning methods as symbolic, subsymbolic and statistical, we can assume that subsymbolic and statistical methods will be more difficult for students to understand as they require an understanding of the mathematical principles on which these methods are based. The study of the ability to understand algorithms based on mathematics was dealt with by Gonda et al [18], who conducted research on algorithmic graph theory students in order to monitor the change in students' motivation to learn algorithms. The authors demonstrated that the development of students' computational thinking is already possible in the teaching of mathematical subjects.…”