Digital educational environment PiktoMir: Experience of development and mass implementation of an annual programming course for preschoolers

IF 2.1 Q1 EDUCATION & EDUCATIONAL RESEARCH
N. Besshaposhnikov, A. Kushnirenko, A. Leonov, M. Raiko, O. V. Sobakinskikh
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引用次数: 3

Abstract

The article presents the result of work on the creation and implementation of the annual course “Algorithmics for Preschool Children”, which, under the guidance of Academician V. B. Betelin for six years led the Department of Educational Informatics of the SRISA RAS together with the Department of Education of the Administration of the city of Surgut (Western Siberia). Since September 2018, the course has been held in all preparatory groups of all kindergartens in Surgut — more than 6,000 children annually. The educational and methodological kit for the course, including the digital educational environment PiktoMir, is freely distributed and can be downloaded from the SRISA RAS website for use for any purpose, including commercial. The course “Algorithmics for preschoolers” discussed in the article is the first part of the long-term course “The basics of programming for preschoolers and junior schoolchildren” being developed. The course uses a textless programming technique. The child composes a program from pictograms with robot commands, singleletter names of subroutines and pictograms of control structures. At the initial stage of training, a screenless technology for compiling a program from material objects is used. The proposed technology favorably differs from analogues in the world in that when working with PiktoMir, a program in the material world can be composed of material objects freely movable by a child: cards, cubes with printed or hand-drawn command pictograms. Information about each command of the program is extracted exclusively from the image perceived by the child, and not from any machine-readable graphic codes or electrical codes hardwired into the material carrier of the pictogram. The child “photographs” pictograms with his tablet, on which they are recognized using neural networks by a special PiktoMir module.
数字教育环境PiktoMir:开发和大规模实施学龄前儿童年度编程课程的经验
本文介绍了创建和实施“学龄前儿童算法”年度课程的工作成果,该课程在V. B. Betelin院士的指导下,与苏尔古特市(西西伯利亚)行政教育部门一起领导了SRISA RAS教育信息部六年。自2018年9月以来,该课程已在苏尔古特所有幼儿园的所有预备小组中举办,每年有6000多名儿童参加。课程的教学和方法工具包,包括数字教育环境PiktoMir,是免费分发的,可以从SRISA RAS网站下载,用于任何目的,包括商业用途。文章中讨论的“学龄前儿童算法”课程是正在开发的长期课程“学龄前儿童和初中儿童编程基础”的第一部分。本课程使用无文本编程技术。孩子用机器人指令的象形图、子程序的单字母名称和控制结构的象形图组成程序。在训练的初始阶段,使用无屏幕技术从实物对象编译程序。所提出的技术与世界上的类似物的有利之处在于,当使用PiktoMir时,物质世界中的程序可以由儿童自由移动的物质对象组成:卡片,带有印刷或手绘命令象形文字的立方体。关于程序的每个命令的信息完全是从儿童感知的图像中提取的,而不是从任何机器可读的图形代码或硬连接到象形文字的物质载体中的电子代码中提取的。孩子用他的平板电脑“拍摄”象形文字,然后通过一个特殊的PiktoMir模块使用神经网络识别它们。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Informatics in Education
Informatics in Education EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
6.10
自引率
3.70%
发文量
20
审稿时长
20 weeks
期刊介绍: INFORMATICS IN EDUCATION publishes original articles about theoretical, experimental and methodological studies in the fields of informatics (computer science) education and educational applications of information technology, ranging from primary to tertiary education. Multidisciplinary research studies that enhance our understanding of how theoretical and technological innovations translate into educational practice are most welcome. We are particularly interested in work at boundaries, both the boundaries of informatics and of education. The topics covered by INFORMATICS IN EDUCATION will range across diverse aspects of informatics (computer science) education research including: empirical studies, including composing different approaches to teach various subjects, studying availability of various concepts at a given age, measuring knowledge transfer and skills developed, addressing gender issues, etc. statistical research on big data related to informatics (computer science) activities including e.g. research on assessment, online teaching, competitions, etc. educational engineering focusing mainly on developing high quality original teaching sequences of different informatics (computer science) topics that offer new, successful ways for knowledge transfer and development of computational thinking machine learning of student''s behavior including the use of information technology to observe students in the learning process and discovering clusters of their working design and evaluation of educational tools that apply information technology in novel ways.
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