{"title":"Electronic schedule at the university on the basis of 1C:Automated scheduling. University on the example of Omsk State University","authors":"T. A. Deyneko, O. L. Epanchintseva, A. Rodyukov","doi":"10.32517/0234-0453-2021-36-2-33-40","DOIUrl":null,"url":null,"abstract":"Automating scheduling is a classic task in learning management systems. The process of scheduling is, in a sense, the final one in the chain of support of educational activities, and its automation reveals all inconsistencies and shortcomings of the previous processes. In order for the scheduling to be automated as much as possible, a lot of various initial information should be processed in the information systems of the university — curricula, staff, workload, schedule of the educational process, contingent of students, classroom fund. It is especially difficult for universities with educational programs of various orientations — natural science, humanitarian, creative, etc., which have specific principles for organizing and conducting classes.The level of automation of educational activities at Dostoevsky Omsk State University, a classical university with a wide variety of types of educational programs, made it possible to tackle the task of scheduling. However, during the implementation of the automated scheduling system, the project team faced a number of problems.The article describes the results of the project for the transition to an electronic schedule in Dostoevsky Omsk State University using the circulation software product 1C:Automated scheduling. University based on the 1C:Enterprise 8.3 system. Initial data on the individual workload of teachers, the classroom fund, the list of student groups, and the list of disciplines were loaded into the configuration from the existing information system of design of Dostoevsky Omsk State University. Based on the results of the audit of the downloaded reference information, the initial data, including curricula, were normalized. The compiled schedule in two modes (manual and automatic) was published on the official website of the university and is used to operate a chatbot on the VKontakte network to inform students and teachers about upcoming classes.","PeriodicalId":45270,"journal":{"name":"Informatics in Education","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2021-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Informatics in Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32517/0234-0453-2021-36-2-33-40","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 0
Abstract
Automating scheduling is a classic task in learning management systems. The process of scheduling is, in a sense, the final one in the chain of support of educational activities, and its automation reveals all inconsistencies and shortcomings of the previous processes. In order for the scheduling to be automated as much as possible, a lot of various initial information should be processed in the information systems of the university — curricula, staff, workload, schedule of the educational process, contingent of students, classroom fund. It is especially difficult for universities with educational programs of various orientations — natural science, humanitarian, creative, etc., which have specific principles for organizing and conducting classes.The level of automation of educational activities at Dostoevsky Omsk State University, a classical university with a wide variety of types of educational programs, made it possible to tackle the task of scheduling. However, during the implementation of the automated scheduling system, the project team faced a number of problems.The article describes the results of the project for the transition to an electronic schedule in Dostoevsky Omsk State University using the circulation software product 1C:Automated scheduling. University based on the 1C:Enterprise 8.3 system. Initial data on the individual workload of teachers, the classroom fund, the list of student groups, and the list of disciplines were loaded into the configuration from the existing information system of design of Dostoevsky Omsk State University. Based on the results of the audit of the downloaded reference information, the initial data, including curricula, were normalized. The compiled schedule in two modes (manual and automatic) was published on the official website of the university and is used to operate a chatbot on the VKontakte network to inform students and teachers about upcoming classes.
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.