Toward a Generic Mobile Learning Framework

By Xin Bai and Michael B. Smith.

Published by Ubiquitous Learning: An International Journal

Format Price
Article: Print $US10.00
Article: Electronic $US5.00

Learning anytime anywhere has been an educational ideal. Now affordable and user-friendly mobile devices, broad wireless coverage, and abundant technology alternatives can make it happen. We choose iPhone as our ubiquitous e-learning devices in our m-learning pilot study. Our goal is to design a generic m-Learning platform that can be adopted by faculty and researchers that may or may not know programming. We’d like such framework to be further extended through interdisciplinary collaboration among faculty and students. We have developed a prototype mobile learning application and are using two hybrid undergraduate courses in our pilot study. We developed an iPhone e-learning prototype using the free iPhone 3.0 SDK. Students can check weekly schedule, browse lecture notes, take online tests, and do online readings, develop blogs, attend iTunes U lectures, and browse youTube videos all a few clicks away. We see the following advantages of our iPhone framework in our endeavor to promote affordable e-learning. 1) Our system design is based upon a generic approach that will allow both programmers and non-programmers to use our platform as a shell to design and develop their own learning modules. 2) Besides the traditional online learning tools, students can effortlessly use social network tools such as e-Portfolio, Twitter, podcast, iTunes U. to collaborate and learn. 3) Our framework is scalable. For instance, it can be easily hooked up to an existing database-driven web system. 4) Serious designers can design interactive programs such as mobile educational games within the same framework.

Keywords: Mobile Learning, ELearning, Ubiquitous Learning

Ubiquitous Learning: An International Journal, Volume 2, Issue 2, pp.95-106. Article: Print (Spiral Bound). Article: Electronic (PDF File; 1.848MB).

Dr. Xin Bai

Assistant Professor, Teacher Education/Academic Computing and Educational Technology, York College, City University of New York, New York, USA

Xin Bai earned her ED.D. in Instructional Technology & Media from Columbia University. Her research interest is “designing intelligent agents in simulation games to facilitate learning.” More specifically, she studies how to develop a learning environment using animated agents in a virtual world that has transparency in both the agents and the virtual world. Her research is also built on the work done on Intelligent Tutoring Systems (ITS) using the knowledge representations to depict what the agents know about their virtual world and what the agents need to learn to solve domain specific problems. Xin was a Project Director of the REAL (REflective Agent Learning environment) Project at the Institute for Learning Technologies at Columbia University. She helped facilitate interdisciplinary collaboration among a dozen graduate students in the areas of artificial intelligence, cognitive psychology, and instructional design. Besides research, Xin has been teaching several graduate core courses, including Cognition and Computers and Intelligent Computer-Assisted Instruction, since 2003. She also worked as a Chief Learning Architect at a company focusing on facilitating adult e-learning and designing Learning Management Systems. Her knowledge of the sharable learning content standard and the design strategies has helped the company gain an edge in the competitive adult learning industry.

Michael B. Smith

Assistant Professor, Preforming and Fine Arts, York College, City University of New York, New York, New York, USA