{"title":"Analytic Information Systems in the Context of Higher Education: Expectations, Reality and Trends","authors":"I. Guitart, J. Conesa","doi":"10.1109/INCoS.2015.71","DOIUrl":null,"url":null,"abstract":"Competitive organizations have implemented systems of business intelligence in order to help employees in the process of evidence-based decision-making. Using these systems in university will provide a set of analytical tools that support decision-making of academics focused to the improvement of their research and teaching activities. In the case of teachers, for example, it may help to better understand students, how they learn and how to improve the learning processes according to evidences. To implement these systems efficiently it is necessary to gather data about the activities students and teachers perform during the learning-teaching process. Currently, most universities provide virtual learning environments (VLE) where students perform most of their learning activities. These environments may store data about the interaction of their users and, therefore, gather information of all the agents during the teaching-learning process. Our proposal is to adopt the strategies of business intelligence, which resulted useful in organizations, to universities. By applying analytic techniques on the large volume of data stored in the VLE, we propose to build dashboards for teachers and academic program managers in order to help them to take decisions that improve teaching in the short, medium and long term.","PeriodicalId":345650,"journal":{"name":"2015 International Conference on Intelligent Networking and Collaborative Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Intelligent Networking and Collaborative Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INCoS.2015.71","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
Competitive organizations have implemented systems of business intelligence in order to help employees in the process of evidence-based decision-making. Using these systems in university will provide a set of analytical tools that support decision-making of academics focused to the improvement of their research and teaching activities. In the case of teachers, for example, it may help to better understand students, how they learn and how to improve the learning processes according to evidences. To implement these systems efficiently it is necessary to gather data about the activities students and teachers perform during the learning-teaching process. Currently, most universities provide virtual learning environments (VLE) where students perform most of their learning activities. These environments may store data about the interaction of their users and, therefore, gather information of all the agents during the teaching-learning process. Our proposal is to adopt the strategies of business intelligence, which resulted useful in organizations, to universities. By applying analytic techniques on the large volume of data stored in the VLE, we propose to build dashboards for teachers and academic program managers in order to help them to take decisions that improve teaching in the short, medium and long term.