{"title":"青少年在线学习的互联网使用:欧洲国家和教育水平的差异","authors":"M. P. Bach, I. Miloloza, J. Zoroja","doi":"10.23919/MIPRO.2018.8400103","DOIUrl":null,"url":null,"abstract":"Abundant availability of online courses and materials has greatly expanded the opportunities for gaining new knowledge and skills, especially among younger population. Most of these courses and materials are freeware or could be purchased for a cost substantially lower than compared to those offered by HEIs or publishing companies. Although these new opportunities are available to everyone, researches indicate that their usage is not evenly spread across European countries and educational levels. Goal of the research is to investigate if the usage of online learning materials and courses over Internet is homogenous in Europe among youth (age 16–29) of low, medium, and high level education. Research has been conducted on the data from Eurostat Database on the following aspects of Internet use (i) Looking for information about education, training or course offers; (ii) Doing an online course (of any subject); (iii) Usage of online learning material; (iv) Communicating with instructors or students using educational websites/portals; (v) Usage of any aspect of online learning. Cluster analysis has been conducted in order to create a group of countries according to different level of internet usage for online learning. Relationship of GDP per capita has been compared across identified clusters.","PeriodicalId":431110,"journal":{"name":"2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Internet use for online learning among youth: Differences across European countries and educational levels\",\"authors\":\"M. P. Bach, I. Miloloza, J. Zoroja\",\"doi\":\"10.23919/MIPRO.2018.8400103\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abundant availability of online courses and materials has greatly expanded the opportunities for gaining new knowledge and skills, especially among younger population. Most of these courses and materials are freeware or could be purchased for a cost substantially lower than compared to those offered by HEIs or publishing companies. Although these new opportunities are available to everyone, researches indicate that their usage is not evenly spread across European countries and educational levels. Goal of the research is to investigate if the usage of online learning materials and courses over Internet is homogenous in Europe among youth (age 16–29) of low, medium, and high level education. Research has been conducted on the data from Eurostat Database on the following aspects of Internet use (i) Looking for information about education, training or course offers; (ii) Doing an online course (of any subject); (iii) Usage of online learning material; (iv) Communicating with instructors or students using educational websites/portals; (v) Usage of any aspect of online learning. Cluster analysis has been conducted in order to create a group of countries according to different level of internet usage for online learning. Relationship of GDP per capita has been compared across identified clusters.\",\"PeriodicalId\":431110,\"journal\":{\"name\":\"2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)\",\"volume\":\"100 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/MIPRO.2018.8400103\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/MIPRO.2018.8400103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Internet use for online learning among youth: Differences across European countries and educational levels
Abundant availability of online courses and materials has greatly expanded the opportunities for gaining new knowledge and skills, especially among younger population. Most of these courses and materials are freeware or could be purchased for a cost substantially lower than compared to those offered by HEIs or publishing companies. Although these new opportunities are available to everyone, researches indicate that their usage is not evenly spread across European countries and educational levels. Goal of the research is to investigate if the usage of online learning materials and courses over Internet is homogenous in Europe among youth (age 16–29) of low, medium, and high level education. Research has been conducted on the data from Eurostat Database on the following aspects of Internet use (i) Looking for information about education, training or course offers; (ii) Doing an online course (of any subject); (iii) Usage of online learning material; (iv) Communicating with instructors or students using educational websites/portals; (v) Usage of any aspect of online learning. Cluster analysis has been conducted in order to create a group of countries according to different level of internet usage for online learning. Relationship of GDP per capita has been compared across identified clusters.