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Pardo, Abelardo; Bartimote-Aufflick, Kathryn; Shum, Simon Buckingham; Dawson, Shane; Gao, Jing; Gaševic, Dragan; Leichtweis, Steve; Liu, Danny; Martínez-Maldonado, Roberto; Mirriahi, Negin; Moskal, Adon Christian Michael; Schulte, Jurgen; Siemens, George; Vigentini, Lorenzo – Journal of Learning Analytics, 2018
The learning analytics community has matured significantly over the past few years as a middle space where technology and pedagogy combine to support learning experiences. To continue to grow and connect these perspectives, research needs to move beyond the level of basic support actions. This means exploring the use of data to prove richer forms…
Descriptors: Individualized Instruction, Data Analysis, Learning, Feedback (Response)
Valsamidis, Stavros; Kontogiannis, Sotirios; Kazanidis, Ioannis; Theodosiou, Theodosios; Karakos, Alexandros – Educational Technology & Society, 2012
Learning Management Systems (LMS) collect large amounts of data. Data mining techniques can be applied to analyse their web data log files. The instructors may use this data for assessing and measuring their courses. In this respect, we have proposed a methodology for analysing LMS courses and students' activity. This methodology uses a Markov…
Descriptors: Foreign Countries, Electronic Learning, College Mathematics, Integrated Learning Systems
Valdés Aguirre, Benjamín; Ramírez Uresti, Jorge A.; du Boulay, Benedict – International Journal of Artificial Intelligence in Education, 2016
Sharing user information between systems is an area of interest for every field involving personalization. Recommender Systems are more advanced in this aspect than Intelligent Tutoring Systems (ITSs) and Intelligent Learning Environments (ILEs). A reason for this is that the user models of Intelligent Tutoring Systems and Intelligent Learning…
Descriptors: Intelligent Tutoring Systems, Models, Open Source Technology, Computers
Castro-Schez, J. J.; del Castillo, E.; Hortolano, J.; Rodriguez, A. – IEEE Transactions on Education, 2009
Educational software tools are considered to enrich teaching strategies, providing a more compelling means of exploration and feedback than traditional blackboard methods. Moreover, software simulators provide a more motivating link between theory and practice than pencil-paper methods, encouraging active and discovery learning in the students.…
Descriptors: Foreign Countries, Computer Software, Data Analysis, Web Based Instruction