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Hernandez Cardenas, Lizette Susana; Castano, Leticia; Cruz Guzman, Cristina; Nigenda Alvarez, Juan Pablo – Australasian Journal of Educational Technology, 2022
This study's innovative objective was to develop a personalised learning model to equate students' entry level knowledge as they entered the School of Medicine and Health Sciences at Tecnologico de Monterrey in Mexico in 2019. This was necessitated by a difference in the depth and approach to preparatory content. The methodology focused on…
Descriptors: Foreign Countries, Knowledge Level, Medical Schools, Health Sciences
Ghallabi, Sameh; Essalmi, Fathi; Jemni, Mohamed; Kinshuk – Education and Information Technologies, 2020
With the emergence of technology, the personalization of e-learning systems is enhanced. These systems use a set of parameters for personalizing courses. However, in literature, these parameters are not based on classification and optimization algorithms to implement them in the cloud. Cloud computing is a new model of computing where standard and…
Descriptors: Electronic Learning, Internet, Information Storage, Models
Pelanek, Radek – IEEE Transactions on Learning Technologies, 2020
Learning systems can utilize many practice exercises, ranging from simple multiple-choice questions to complex problem-solving activities. In this article, we propose a classification framework for such exercises. The framework classifies exercises in three main aspects: (1) the primary type of interaction; (2) the presentation mode; and (3) the…
Descriptors: Integrated Learning Systems, Classification, Multiple Choice Tests, Problem Solving
Zou, Di; Wang, Minhong; Xie, Haoran; Cheng, Gary; Wang, Fu Lee; Lee, Lap-Kei – Interactive Learning Environments, 2021
Personalized learning has become an important and powerful paradigm catering for various needs, styles, preferences, and modes of learning. Several methods including task recommendations and path planning have recently emerged to effectively implement personalized learning using e-learning systems. The literature shows that the use of task…
Descriptors: Linguistic Theory, Vocabulary Development, Second Language Learning, Second Language Instruction
Alhawiti, Mohammed M.; Abdelhamid, Yasser – Journal of Education and e-Learning Research, 2017
With the advent of web based learning and content management tools, e-learning has become a matured learning paradigm, and changed the trend of instructional design from instructor centric learning paradigm to learner centric approach, and evolved from "one instructional design for many learners" to "one design for one learner"…
Descriptors: Electronic Learning, Student Centered Learning, Instructional Design, Individualized Instruction
Salahli, Mehmet Ali; Ă–zdemir, Muzaffer; Yasar, Cumali – International Education Studies, 2013
One of the most important factors for improving the personalization aspects of learning systems is to enable adaptive properties to them. The aim of the adaptive personalized learning system is to offer the most appropriate learning path and learning materials to learners by taking into account their profiles. In this paper, a new approach to…
Descriptors: Individualized Instruction, Electronic Learning, Educational Technology, Profiles
Dutta, Pratima – ProQuest LLC, 2013
The Personalized Integrated Educational System (PIES) design theory is a design recommendation regarding the function and features of Learning Managements Systems (LMS) that can support the information-age learner-centered paradigm of education. The purpose of this study was to improve the proposed functions and features of the PIES design theory…
Descriptors: Integrated Learning Systems, Models, Transcripts (Written Records), Observation
Capuano, Nicola; Gaeta, Matteo; Marengo, Agostino; Miranda, Sergio; Orciuoli, Francesco; Ritrovato, Pierluigi – Interactive Learning Environments, 2009
Intelligent e-learning systems have revolutionized online education by providing individualized and personalized instruction for each learner. Nevertheless, until now very few systems were able to leave academic laboratories and be integrated into real commercial products. One of these few exceptions is the Learning Intelligent Advisor (LIA)…
Descriptors: Distance Education, Online Courses, Laboratories, Individualized Instruction
Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
Wang, Feng-Hsu – Educational Technology & Society, 2008
The WWW is now in widespread use for delivering on-line learning content in many large-scale education settings. Given such widespread usage, it is feasible to accumulate data concerning the most useful learning experiences of past students and share them with future students. Browsing events that depict how past students utilized the learning…
Descriptors: Feedback (Response), Instructional Materials, Internet, Models
Gogoulou, Agoritsa; Gouli, Evangelia; Grigoriadou, Maria; Samarakou, Maria; Chinou, Dionisia – Educational Technology & Society, 2007
In this paper, we present a web-based educational setting, referred to as SCALE (Supporting Collaboration and Adaptation in a Learning Environment), which aims to serve learning and assessment. SCALE enables learners to (i) work on individual and collaborative activities proposed by the environment with respect to learners' knowledge level, (ii)…
Descriptors: Teacher Education Programs, College Students, Student Attitudes, Foreign Countries
Papasalouros, Andreas; Retalis, Symeon; Papaspyrou, Nikolaos – Educational Technology & Society, 2004
The role of conceptual modeling in Educational Adaptive Hypermedia Applications (EAHA) is especially important. A conceptual model of an educational application depicts the instructional solution that is implemented, containing information about concepts that must be ac-quired by learners, tasks in which learners must be involved and resources…
Descriptors: Intelligent Tutoring Systems, Models, Individualized Instruction, Educational Technology
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection