The Efficiency Examination of Teaching of Different Normalization Methods

TL;DR

This paper evaluates various normalization teaching methods by surveying engineering students and analyzing their performance to identify the most effective approach for improving learning efficiency.

Contribution

It introduces alternative normalization methods into education and assesses their effectiveness through surveys and statistical analysis.

Findings

Certain normalization methods lead to significantly better student performance.

Statistical analysis confirms differences in efficiency among methods.

Data mining techniques help identify the most effective normalization teaching approach.

Abstract

Normalization is an important database design method, in the course of the teaching of data modeling the understanding and applying of this method cause problems for students the most. For improving the efficiency of learning normalization we looked for alternative normalization methods and introduced them into education. We made a survey among engineer students how efficient could they execute the normalization with different methods. We executed statistical and data mining examinations to decide whether any of the methods resulted significantly better solutions.