Selection criteria for cloud-oriented learning technologies for the formation of professional competencies of bachelors majoring in statistics
This article scientifically substantiates the criteria for the selection of cloud-oriented learning technologies for the formation of professional competencies of bachelors majoring in statistics, as well as presents the results of expert evaluation of existing cloud-oriented learning technologies b...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2020-01-01
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| Series: | SHS Web of Conferences |
| Online Access: | https://www.shs-conferences.org/articles/shsconf/pdf/2020/03/shsconf_ichtml_2020_04012.pdf |
| _version_ | 1818858753279131648 |
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| author | Gavryliuk Olga Vakaliuk Tetiana Kontsedailo Valerii |
| author_facet | Gavryliuk Olga Vakaliuk Tetiana Kontsedailo Valerii |
| author_sort | Gavryliuk Olga |
| collection | DOAJ |
| description | This article scientifically substantiates the criteria for the selection of cloud-oriented learning technologies for the formation of professional competencies of bachelors majoring in statistics, as well as presents the results of expert evaluation of existing cloud-oriented learning technologies by defined criteria. The criteria for the selection of cloud-oriented learning technologies for the formation of professional competencies of bachelors majoring in statistics, were determined: information-didactic, functional and technological. To implement the selection of cloud-oriented learning technologies for the formation of professional competencies of bachelors majoring in statistics, and effective application in the process of formation of relevant competencies, the method of expert evaluation was applied. The expert evaluation was carried out in two stages: the first one selected cloud-oriented learning technologies to determine the most appropriate by author’s criteria and indicators, and the second identified those cloud-oriented learning technologies that should be used in the educational process as a means to develop professional skills Bachelor of Statistics. According to the research, the most appropriate, convenient and effective cloud-oriented learning technologies for the formation of professional competencies of future bachelors of statistics by the vmanifestation of all criteria are cloud-oriented learning technologies CoCalc and Wolfram|Alpha. |
| first_indexed | 2024-12-19T09:01:18Z |
| format | Article |
| id | doaj.art-95a51c32d7d243a782aa90fb7fc3bd1f |
| institution | Directory Open Access Journal |
| issn | 2261-2424 |
| language | English |
| last_indexed | 2024-12-19T09:01:18Z |
| publishDate | 2020-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | SHS Web of Conferences |
| spelling | doaj.art-95a51c32d7d243a782aa90fb7fc3bd1f2022-12-21T20:28:29ZengEDP SciencesSHS Web of Conferences2261-24242020-01-01750401210.1051/shsconf/20207504012shsconf_ichtml_2020_04012Selection criteria for cloud-oriented learning technologies for the formation of professional competencies of bachelors majoring in statisticsGavryliuk Olga0Vakaliuk Tetiana1Kontsedailo Valerii2Institute of Information Technologies and Learning Tools of the NAES of Ukraine, Department of Cloud-Oriented Systems of Education Informatization,Zhytomyr Polytechnic State University, Department of Software EngineeringEasygeneratorThis article scientifically substantiates the criteria for the selection of cloud-oriented learning technologies for the formation of professional competencies of bachelors majoring in statistics, as well as presents the results of expert evaluation of existing cloud-oriented learning technologies by defined criteria. The criteria for the selection of cloud-oriented learning technologies for the formation of professional competencies of bachelors majoring in statistics, were determined: information-didactic, functional and technological. To implement the selection of cloud-oriented learning technologies for the formation of professional competencies of bachelors majoring in statistics, and effective application in the process of formation of relevant competencies, the method of expert evaluation was applied. The expert evaluation was carried out in two stages: the first one selected cloud-oriented learning technologies to determine the most appropriate by author’s criteria and indicators, and the second identified those cloud-oriented learning technologies that should be used in the educational process as a means to develop professional skills Bachelor of Statistics. According to the research, the most appropriate, convenient and effective cloud-oriented learning technologies for the formation of professional competencies of future bachelors of statistics by the vmanifestation of all criteria are cloud-oriented learning technologies CoCalc and Wolfram|Alpha.https://www.shs-conferences.org/articles/shsconf/pdf/2020/03/shsconf_ichtml_2020_04012.pdf |
| spellingShingle | Gavryliuk Olga Vakaliuk Tetiana Kontsedailo Valerii Selection criteria for cloud-oriented learning technologies for the formation of professional competencies of bachelors majoring in statistics SHS Web of Conferences |
| title | Selection criteria for cloud-oriented learning technologies for the formation of professional competencies of bachelors majoring in statistics |
| title_full | Selection criteria for cloud-oriented learning technologies for the formation of professional competencies of bachelors majoring in statistics |
| title_fullStr | Selection criteria for cloud-oriented learning technologies for the formation of professional competencies of bachelors majoring in statistics |
| title_full_unstemmed | Selection criteria for cloud-oriented learning technologies for the formation of professional competencies of bachelors majoring in statistics |
| title_short | Selection criteria for cloud-oriented learning technologies for the formation of professional competencies of bachelors majoring in statistics |
| title_sort | selection criteria for cloud oriented learning technologies for the formation of professional competencies of bachelors majoring in statistics |
| url | https://www.shs-conferences.org/articles/shsconf/pdf/2020/03/shsconf_ichtml_2020_04012.pdf |
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