| Title |
Features of the Python active lessons teaching methodology / |
| Authors |
Karčiauskas, Eimutis |
| DOI |
10.15388/DAMSS.12.2021 |
| ISBN |
9786090706732 |
| eISBN |
9786090706749 |
| Full Text |
|
| Is Part of |
DAMSS 2021: 12th conference on data analysis methods for software systems, Druskininkai, Lithuania, December 2–4, 2021 / Lithuanian computer society, Vilnius university Institute of data science and digital technologies, Lithuanian academy of sciences.. Vilnius : Vilnius university press, 2021. p. 29.. ISBN 9786090706732. eISBN 9786090706749 |
| Abstract [eng] |
As the number of data analysis tasks increases, the training of new researchers is becoming increasingly important. It is widely acknowledged that Python programming language is the most popular among the research tools. In order to get students interested in Python programming an active learning methodology has been developed. Its main features are: • starting learning process with the construction of functions; • representation of all algorithms by functions; • as much knowledge as possible about the algorithms is presented in the source code; • for each topic demonstrative functions are provided; • the specified functions are provided for students to use in experiments; • students receive the related tasks directly in the source code; • the study tasks are relevant to real-world data. This methodology was developed based on the programming and data structures teaching experience at the KTU Faculty of Informatics. This allowed many tasks to migrate to the school course adapting them to school curricula. Experience has shown that there is a significant increase in the effectiveness of training, as measured by the number of tasks completed. The understanding of the study material is also enhanced by the activity of students, as they do not have to waste time on data entry as it is in the classical teaching style, where the concept of functions is taught only as late as 7th - 8th topic. |
| Published |
Vilnius : Vilnius university press, 2021 |
| Type |
Conference paper |
| Language |
English |
| Publication date |
2021 |
| CC license |
|
