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Application of Free Syntax Methods for Recognizing Piktocubes in the Course «Algorithmics for Preschoolers»

Abstract

The article addresses issues related to the safe integration of digital technologies into the educational processes of older preschool children in accordance with sanitary rules and norms. The main focus is on teaching algorithmics using the educational environment PiktoMir, which includes software and real-world objects such as radiocontrolled robot toys, soft toys, cubes, magnetic cards with command pictograms, and articulated mats. It describes a step-by-step process of transitioning from the physical world to the virtual world for a deeper understanding of concepts. Additionally, the article presents an approach to object detection tasks using convolutional neural networks, applied in algorithmic competitions. Students solve tasks using physical objects like piktocubes to create programs, which are then transferred by the teacher to the PiktoMir application. This method helps improve the understanding of programming fundamentals in older and middle preschool children.

About the Authors

A. G. Leonov
ФГУ ФНЦ НИИСИ РАН ; МГУ им. М. В. Ломоносова ; МПГУ ; Государственный университет управления
Russian Federation


K. A. Mashchenko
ФГУ ФНЦ НИИСИ РАН ; МГУ им. М. В. Ломоносова ; Государственный университет управления
Russian Federation


N. S. Martynov
ФГУ ФНЦ НИИСИ РАН
Russian Federation


M. V. Rayko
ФГУ ФНЦ НИИСИ РАН
Russian Federation


A. I. Strekalova
ФГУ ФНЦ НИИСИ РАН
Russian Federation


T. G. Khan
ФГУ ФНЦ НИИСИ РАН
Russian Federation


References

1. В. Б. Бетелин, А. Г. Кушниренко, А. Г. Леонов, Основные понятия программирования в изложении для дошкольников // Информатика и ее применения. – 2020. – Том 14, № 3. – С. 56–62.

2. Стартовая страница проекта «ПиктоМир» на сайте ФГУ ФНЦ НИИСИ РАН. URL: https://www.niisi.ru/piktomir/ (дата обращения 01.05.2024)

3. N.Besshaposhnikov, A.Kushnirenko, and A.Leonov. Piktomir: how and why do we teach textless programming for preschoolers, first graders and students of pedagogical universities. CEE-SECR '17: Proceedings of the 13th Central & Eastern European Software Engineering Conference in Russia, October 2017. No. 21. P. 1–7. 2017

4. А. Г. Кушниренко, А. Г. Леонов, С. А. Поликарпов. БЕЗОШИБОЧНЫЙ ДВУМЕРНЫЙ ПИКТОГРАММНЫЙ СИНТАКСИС В УЧЕБНОЙ СРЕДЕ ПРОГРАММИРОВАНИЯ ДЛЯ ДОШКОЛЬНИКОВ. ДОКЛАДЫ РОССИЙСКОЙ АКАДЕМИИ НАУК. МАТЕМАТИКА, ИНФОРМАТИКА, ПРОЦЕССЫ УПРАВЛЕНИЯ, 2023, том 511, с. 13–19, DOI: 10.31857/S2686954323700169

5. Kaidong Li, Wenchi Ma, Usman Sajid, Yuanwei Wu, Guanghui Wang. Object Detection with Convolutional Neural Networks. arXiv preprint arXiv:1912.01844, 2019.

6. Syed Sahil Abbas Zaidi, Mohammad Samar Ansari, Asra Aslam, Nadia Kanwal, Mamoona Asghar, Brian Lee. A Survey of Modern Deep Learning based Object Detection Models. arXiv preprint arXiv:2104.11892, 2021.

7. Qingqing Xu, Zhiyu Zhu, Huilin Ge, Zheqing Zhang, Xu Zang. Effective Face Detector Based on YOLOv5 and Superresolution Reconstruction, 2021. doi: 10.1155/2021/7748350

8. PyTorch, https://pytorch.org/

9. YOLOv5 https://github.com/ultralytics/yolov5

10. Suorong Yang, Weikang Xiao, Mengcheng Zhang, Suhan Guo, Jian Zhao, Furao Shen. Image Data Augmentation for Deep Learning: A Survey. arXiv preprint arXiv:2204.08610 , 2022.

11. Pappu Kumar Yadav, J. Alex Thomasson, Stephen W. Searcy, Robert G. Hardin, Ulisses Braga-Neto, Sorin C. Popescu, Daniel E. Martin, Roberto Rodriguez, Karem Meza, Juan Enciso, Jorge Solorzano Diaz, Tianyi Wang. Assessing The Performance of YOLOv5 Algorithm for Detecting Volunteer Cotton Plants in Corn Fields at Three Different Growth Stages. arXiv preprint arXiv:2208.00519, 2022.

12. Леонов А.Г., Райко М.В., Райко И.Г., Ковыршина В.А., Хольхина A.A. Алгоритмиады как элементы ускорения обучения информатике в сборнике ИНФОРМАТИЗАЦИЯ ОБРАЗОВАНИЯ И МЕТОДИКА ЭЛЕКТРОННОГО ОБУЧЕНИЯ: ЦИФРОВЫЕ ТЕХНОЛОГИИ В ОБРАЗОВАНИИ Материалы VI Международной научной конференции, место издания Красноярский государственный педагогический университет им. В.П. Астафьева Красноярск, тезисы, с. 179-186


Review

For citations:


Leonov A.G., Mashchenko K.A., Martynov N.S., Rayko M.V., Strekalova A.I., Khan T.G. Application of Free Syntax Methods for Recognizing Piktocubes in the Course «Algorithmics for Preschoolers». SRISA Proceedings. 2024;14(2):38-43. (In Russ.)

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ISSN 2225-7349 (Print)
ISSN 3033-6422 (Online)