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https://ruomo.lib.uom.gr/handle/7000/1234
Τίτλος: | Using metrics and cluster analysis for analyzing learner video viewing behaviours in educational videos |
Συγγραφείς: | Kleftodimos, Alexandros Evangelidis, Georgios |
Τύπος: | Conference Paper |
Θέματα: | FRASCATI::Natural sciences::Computer and information sciences |
Λέξεις-Κλειδιά: | Measurement Data mining Education Software Databases Communications technology Media |
Ημερομηνία Έκδοσης: | 2014 |
Πρώτη Σελίδα: | 280 |
Τελευταία Σελίδα: | 287 |
Τίτλος Τόμου: | 2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA) |
Επιτομή: | On line video is a powerful tool for e-learning and this is evident from a number of reports, research papers and university initiatives, which portray that online video is becoming an important medium for delivering educational content. Therefore, research that focuses on how students view educational videos becomes of particular interest and in previous work we argued that in order to efficiently analyze learner viewing behavior we should deploy tools that log the learner activity and assist usage analysis and data mining. Working towards this direction, a framework for recording and analyzing learner behavior was presented together with findings of applying the framework into educational settings. In this paper, we continue this work by presenting a set of metrics that can be derived from the framework and be used to measure learner engagement and video popularity. These metrics in conjunction with the data mining method of clustering are then used to gain insights into learner viewing behavior. |
URI: | https://doi.org/10.1109/AICCSA.2014.7073210 https://ruomo.lib.uom.gr/handle/7000/1234 |
ISBN: | 978-1-4799-7100-8 |
Αλλοι Προσδιοριστές: | 10.1109/AICCSA.2014.7073210 |
Εμφανίζεται στις Συλλογές: | Τμήμα Εφαρμοσμένης Πληροφορικής |
Αρχεία σε αυτό το Τεκμήριο:
Αρχείο | Περιγραφή | Μέγεθος | Μορφότυπος | |
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2014_AICCSA.pdf | 221,56 kB | Adobe PDF | Προβολή/Ανοιγμα |
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