A Holistic View on Academic Wide Data through Learning Analytics Dashboards Α Big Data Scale Analysis Framework to Support Customized and Personalized Learning Environments View project Educational Data Mining View project A Holistic View on Academic Wide Data through Learning Analytics Dashboards. Gkontzis, A., F., Stavropoulos, E., C., Karachristos, C., Panagiotakopoulos, C., T., & Verykios, V., S. Technical Report 2017. Website abstract bibtex We live in an era of ever developing technology which has led to a massive increase in the amount of data available. Every move, click, and swipe of a card creates a virtual image of our lives in the form of a personal mosaic. Through sophisticated methods applied on these data, companies are now able to predict whether their products will appeal to people and target their advertising and market with maximum profit. In the competitive and globalized environment of education, institutions have to attract, assess and guide their students. In Greece, the Hellenic Open University (HOU) offers its courses in an open and distance learning mode. In contrast to a traditional university where most of the interaction and teaching is taking place on a face-to-face basis, at HOU the learning process is mainly facilitated via multimodal technological pathways and systems. It is important to homogenize and integrate the data collected from these systems in order to utilize it by gaining knowledge and building on it. To accomplish this, we use a learning analytics methodology to analyze the data and automatically create a detailed and holistic image of student performance, tutor effectiveness, and administration efficiency. This is then visualized through learning dashboards which convey important information so that each party can take necessary action and help the institution to improve its standing in the competitive educational environment. We aim to use the information within the systems where it is derived, since this makes the process more user friendly and accessible to all those involved.
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title = {A Holistic View on Academic Wide Data through Learning Analytics Dashboards Α Big Data Scale Analysis Framework to Support Customized and Personalized Learning Environments View project Educational Data Mining View project A Holistic View on Academic Wide Data through Learning Analytics Dashboards},
type = {techreport},
year = {2017},
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abstract = {We live in an era of ever developing technology which has led to a massive increase in the amount of data available. Every move, click, and swipe of a card creates a virtual image of our lives in the form of a personal mosaic. Through sophisticated methods applied on these data, companies are now able to predict whether their products will appeal to people and target their advertising and market with maximum profit. In the competitive and globalized environment of education, institutions have to attract, assess and guide their students. In Greece, the Hellenic Open University (HOU) offers its courses in an open and distance learning mode. In contrast to a traditional university where most of the interaction and teaching is taking place on a face-to-face basis, at HOU the learning process is mainly facilitated via multimodal technological pathways and systems. It is important to homogenize and integrate the data collected from these systems in order to utilize it by gaining knowledge and building on it. To accomplish this, we use a learning analytics methodology to analyze the data and automatically create a detailed and holistic image of student performance, tutor effectiveness, and administration efficiency. This is then visualized through learning dashboards which convey important information so that each party can take necessary action and help the institution to improve its standing in the competitive educational environment. We aim to use the information within the systems where it is derived, since this makes the process more user friendly and accessible to all those involved.},
bibtype = {techreport},
author = {Gkontzis, Andreas F and Stavropoulos, Elias C and Karachristos, C and Panagiotakopoulos, Chris T and Verykios, Vassilios S}
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