Giacomo Nalli, L. Mostarda, A. Perali, S. Pilati, D. Amendola
{"title":"Moodle平台将机器学习应用于学习分析,在在线课程中创建异构组","authors":"Giacomo Nalli, L. Mostarda, A. Perali, S. Pilati, D. Amendola","doi":"10.7346/SIRD-2S2019-P158","DOIUrl":null,"url":null,"abstract":"In university courses to promote collaborative activities among students, on-line learningenvironments such as e-learning platforms are used. Effective collaborative activitiesinvolve the creation of heterogeneous groups of 4 or 5 students. In the university contextthe formation of groups is difficult due to the high number of students. Groups are oftenunbalanced and not very functional if chosen randomly. Some e-learning platforms, suchas Moodle, lack an intelligent mechanism that allows the automatic creation of heterogeneousgroups of students. We applied clustering algorithms on Moodle learning analytics(LA) that allowed to build groupings that identify the different characteristics ofstudents based on their behaviors kept on the platform. Therefore we have developedan intelligent numerical tool which, using clusters obtained from Machine Learning onthe LA, generates heterogeneous groups. These groups are made available on the platformfor the teacher. The project will conclude with the development of a Moodle pluginto automate the exchange of data and information between the Machine Learning algorithmand the Moodle platform.","PeriodicalId":258466,"journal":{"name":"ITALIAN JOURNAL OF EDUCATIONAL RESEARCH","volume":"170 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Applicazione del machine learning ai learning analytics della piattaforma Moodle per creare gruppi eterogenei nei corsi on-line\",\"authors\":\"Giacomo Nalli, L. Mostarda, A. Perali, S. Pilati, D. Amendola\",\"doi\":\"10.7346/SIRD-2S2019-P158\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In university courses to promote collaborative activities among students, on-line learningenvironments such as e-learning platforms are used. Effective collaborative activitiesinvolve the creation of heterogeneous groups of 4 or 5 students. In the university contextthe formation of groups is difficult due to the high number of students. Groups are oftenunbalanced and not very functional if chosen randomly. Some e-learning platforms, suchas Moodle, lack an intelligent mechanism that allows the automatic creation of heterogeneousgroups of students. We applied clustering algorithms on Moodle learning analytics(LA) that allowed to build groupings that identify the different characteristics ofstudents based on their behaviors kept on the platform. Therefore we have developedan intelligent numerical tool which, using clusters obtained from Machine Learning onthe LA, generates heterogeneous groups. These groups are made available on the platformfor the teacher. The project will conclude with the development of a Moodle pluginto automate the exchange of data and information between the Machine Learning algorithmand the Moodle platform.\",\"PeriodicalId\":258466,\"journal\":{\"name\":\"ITALIAN JOURNAL OF EDUCATIONAL RESEARCH\",\"volume\":\"170 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ITALIAN JOURNAL OF EDUCATIONAL RESEARCH\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.7346/SIRD-2S2019-P158\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ITALIAN JOURNAL OF EDUCATIONAL RESEARCH","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7346/SIRD-2S2019-P158","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Applicazione del machine learning ai learning analytics della piattaforma Moodle per creare gruppi eterogenei nei corsi on-line
In university courses to promote collaborative activities among students, on-line learningenvironments such as e-learning platforms are used. Effective collaborative activitiesinvolve the creation of heterogeneous groups of 4 or 5 students. In the university contextthe formation of groups is difficult due to the high number of students. Groups are oftenunbalanced and not very functional if chosen randomly. Some e-learning platforms, suchas Moodle, lack an intelligent mechanism that allows the automatic creation of heterogeneousgroups of students. We applied clustering algorithms on Moodle learning analytics(LA) that allowed to build groupings that identify the different characteristics ofstudents based on their behaviors kept on the platform. Therefore we have developedan intelligent numerical tool which, using clusters obtained from Machine Learning onthe LA, generates heterogeneous groups. These groups are made available on the platformfor the teacher. The project will conclude with the development of a Moodle pluginto automate the exchange of data and information between the Machine Learning algorithmand the Moodle platform.