Inferring Learning Style From the Way Students Interact With a Computer User Interface and the WWW

Abstract

Recent significant advances in automatically predicting user learning styles are described. The system works with new client-based systems that filter Web pages and provide easy, structured, focused, and controlled access to the Internet. A first system called iLessons was embedded within Microsoft Internet Explorer 6 and provided teachers with tools to create lesson Web pages, define zones of the Internet that could be accessed during a lesson, and enforce these settings in a set of computers. A second system enabled students to investigate and collaborate using the Internet. The system filtered Web pages based on the relevance of their contents and assisted students by inferring their learning style (active or reflective) and by recommending pages found by fellow students based on page relevancy, student learning style, and state of mind measured by activity. The system infers learning style in real time by monitoring user activity and recent significant advances in the research are described.

Integrating learning styles and adaptive e-learning system: Current developments, problems and opportunities

“…Notable examples include papers by Wen et al (2007) which employed learning styles to reduce the bias in peer assessment, Baldiris et al (2008) in which different media, format and semantic density of learning resources were matched to different learning styles and Sanders and Bergasa-Suso (2010) in which under the course to investigate and collaborate on the internet, suitable webpages were recommended.…”

“…,Latham et al (2012),Sangineto et al (2008),Scott et al (2014),Wen et al (2007),Cabada et al (2009), Cabada, Barrón Estrada, andReyes García (2011),Villaverde et al (2006),Hong and Kinshuk (2004),Sanders and Bergasa-Suso (2010),Wang et al al. (2006),Dorça et al (2013a) …”

Web Log Pre-processing and Analysis for Generation of Learning Profiles in Adaptive E-learning

“…In teaching-learning process every learner will have different background knowledge, learning preferences and individual students may expect different approaches towards learning courses. With this main objective, adaptive e-learning systems (AEHSs, AdaLearn, iLessons) have been developed to offer personalized learning content to improve their learning outcome [20] [2] [18]. Many researchers have been concentrating on identifying the learner's learning styles to implement adaptation in online learning management systems.…”

The Impact of Learning Styles on Learner's Performance in E-Learning Environment

“…Beragasa-Suso et al [17] designed a web browser-based system called iLessons. The system is embedded within Microsoft Internet Explorer enabling the teachers with various features such as reusing the materials available on the WWW by drag and drop, navigation options.…”