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Paquette, Luc; Baker, Ryan S. – Interactive Learning Environments, 2019
Learning analytics research has used both knowledge engineering and machine learning methods to model student behaviors within the context of digital learning environments. In this paper, we compare these two approaches, as well as a hybrid approach combining the two types of methods. We illustrate the strengths of each approach in the context of…
Descriptors: Comparative Analysis, Student Behavior, Models, Case Studies
Xie, Ying; Lin, Shu-Yuan – Interactive Learning Environments, 2019
This study reports the effects of using word clouds to support students' knowledge integration from online inquiry as demonstrated by blog posts, tags and concept maps. Fifty-four undergraduate students from a medium-sized university in the northwestern United States were randomly assigned into two groups and blogged for five weeks. To support…
Descriptors: Undergraduate Students, Web Sites, Scaffolding (Teaching Technique), Inquiry
Al-Samarraie, Hosam; Selim, Hassan; Teo, Timothy; Zaqout, Fahed – Interactive Learning Environments, 2017
When faced with excessive detail in an online environment, typical users have difficulty processing all the elements of representation. This in turn creates cognitive overload, which narrows the user's focus to a few select items. In the context of e-learning, we translated this aspect as the learner's demand for a system that facilitates the…
Descriptors: Foreign Countries, Undergraduate Students, Instructional Design, Online Courses
Papasalouros, Andreas; Kotis, Konstantinos; Kanaris, Konstantinos – Interactive Learning Environments, 2011
The aim of this article is to present an approach for generating tests in an automatic way. Although other methods have been already reported in the literature, the proposed approach is based on ontologies, representing both domain and multimedia knowledge. The article also reports on a prototype implementation of this approach, which…
Descriptors: Semantics, Natural Language Processing, Test Construction, Educational Technology
Garcia-Barriocanal, Elena; Sicilia, Miguel-Angel; Sanchez-Alonso, Salvador; Lytras, Miltiadis – Interactive Learning Environments, 2011
Web 2.0 technologies can be considered a loosely defined set of Web application styles that foster a kind of media consumer more engaged, and usually active in creating and maintaining Internet contents. Thus, Web 2.0 applications have resulted in increased user participation and massive user-generated (or user-published) open multimedia content,…
Descriptors: Semantics, Internet, Video Technology, Educational Technology
Stranieri, Andrew; Yearwood, John – Interactive Learning Environments, 2008
This paper describes a narrative-based interactive learning environment which aims to elucidate reasoning using interactive scenarios that may be used in training novices in decision-making. Its design is based on an approach to generating narrative from knowledge that has been modelled in specific decision/reasoning domains. The approach uses a…
Descriptors: Feedback (Response), Nursing Students, Nursing Education, Knowledge Representation

Jackson, Shari L.; And Others – Interactive Learning Environments, 1994
Discussion of dynamic modeling focuses on the development of a new modeling tool called Model-It which provides intentionally designed scaffolding for learners, enabling them to build and test dynamic models of complex systems using object-oriented and qualitative techniques. Classroom testing with high school students is described. (Author/LRW)
Descriptors: College Preparation, Futures (of Society), High Schools, Instructional Design
Michael, Joel; Rovick, Allen; Glass, Michael; Zhou, Yujian; Evens, Martha – Interactive Learning Environments, 2003
CIRCSIM-Tutor is a computer tutor designed to carry out a natural language dialogue with a medical student. Its domain is the baroreceptor reflex, the part of the cardiovascular system that is responsible for maintaining a constant blood pressure. CIRCSIM-Tutor's interaction with students is modeled after the tutoring behavior of two experienced…
Descriptors: Natural Language Processing, Medical Students, Computer Mediated Communication, Artificial Intelligence