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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)
Bull, Susan; Kay, Judy – International Journal of Artificial Intelligence in Education, 2016
The SMILI? (Student Models that Invite the Learner In) Open Learner Model Framework was created to provide a coherent picture of the many and diverse forms of Open Learner Models (OLMs). The aim was for SMILI? to provide researchers with a systematic way to describe, compare and critique OLMs. We expected it to highlight those areas where there…
Descriptors: Educational Research, Data Collection, Data Analysis, Intelligent Tutoring 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
Rupp, Andre A.; Levy, Roy; Dicerbo, Kristen E.; Sweet, Shauna J.; Crawford, Aaron V.; Calico, Tiago; Benson, Martin; Fay, Derek; Kunze, Katie L.; Mislevy, Robert J.; Behrens, John T. – Journal of Educational Data Mining, 2012
In this paper we describe the development and refinement of "evidence rules" and "measurement models" within the "evidence model" of the "evidence-centered design" (ECD) framework in the context of the "Packet Tracer" digital learning environment of the "Cisco Networking Academy." Using…
Descriptors: Computer Networks, Evidence Based Practice, Design, Instructional Design
Pai, Ping-Feng; Lyu, Yi-Jia; Wang, Yu-Min – Computers & Education, 2010
Rough set theory (RST) is an emerging technique used to deal with problems in data mining and knowledge acquisition. However, the RST approach has not been widely explored in the field of academic achievement. This investigation developed an improved RST (IMRST) model, which employs linear discriminant analysis to determine a reduct of RST, and…
Descriptors: Academic Achievement, Discriminant Analysis, Foreign Countries, Junior High School Students
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers