A Contextualized System for Supporting Active Learning

• Published in: IEEE transactions on learning technologies Vol. 9; no. 2; pp. 196 - 202
• Main Authors: Gomez, Jorge E., Huete, Juan F., Hernandez, Velssy L.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.04.2016; Institute of Electrical and Electronics Engineers, Inc; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Active Learning; Case Studies; Cognition; Comparative Analysis; Computer Software; Context; Context awareness; Context Effect; Context modeling; Education; Educational Environment; Educational Resources; Engineering Education; Foreign Countries; Geographic Location; Handheld Devices; Health Services; Heart Disorders; intelligent educational systems; Intelligent Tutoring Systems; internet of things; Internship Programs; Learning; Learning Experience; Learning Processes; Likert Scales; Medical Education; Mobile handsets; Nursing Education; Ontologies; Patients; Pretests Posttests; Profiles; Questionnaires; Sensors; Statistical Analysis; Student Attitudes; Teaching Methods; Telecommunications; Spain; active learning; internet of things; Context awareness; intelligent educational systems
• ISSN: 1939-1382; 2372-0050
• DOI: 10.1109/TLT.2016.2531685

The dynamics of the world today demands a change in traditional education paradigms to enable the creation of more efficient learning environments, where students will learn more effectively and will play a more active role in their education. They should interact with the knowledge at anytime-anywhere. In order to tackle this problem we should take advantage of mobile communication devices (e.g., smartphones and tablets) which are widely used by students and which have excellent processing storage and connectivity capabilities. In this research work, a context-aware system stimulating active learning by students was developed. This system places the student in an intelligent learning environment and is capable of delivering appropriate context-related learning contents, based on location, time, date, interaction of the student, profile of the student, and so on. Within its architecture, the system includes reasoning capability that using context-based ontology is able to deliver efficient learning resources. The experimental results obtained from various learning experiences in nursery, medicine, and systems engineering support the validity of our approach.