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A pedagogical framework for mobile learning: Categorizing educational applications of mobile technologies into four types

  • Yeonjeong Park Virginia Tech
Keywords: e-learning, m-learning, u-learning, four types of mobile learning, distance learning, transactional distance theory, individual and group learning


Instructional designers and educators recognize the potential of mobile technologies as a learning tool for students and have incorporated them into the distance learning environment. However, little research has been done to categorize the numerous examples of mobile learning in the context of distance education, and few instructional design guidelines based on a solid theoretical framework for mobile learning exist. In this paper I compare mobile learning (m-learning) with electronic learning (e-learning) and ubiquitous learning (u-learning) and describe the technological attributes and pedagogical affordances of mobile learning presented in previous studies. I modify transactional distance (TD) theory and adopt it as a relevant theoretical framework for mobile learning in distance education. Furthermore, I attempt to position previous studies into four types of mobile learning: 1) high transactional distance socialized m-learning, 2) high transactional distance individualized m-learning, 3) low transactional distance socialized m-learning, and 4) low transactional distance individualized m-learning. As a result, this paper can be used by instructional designers of open and distance learning to learn about the concepts of mobile learning and how mobile technologies can be incorporated into their teaching and learning more effectively.

Author Biography

Yeonjeong Park, Virginia Tech
Yeonjeong Park (Ph.D. Candidate) Instructional Design and Technology Department of Learning Science and Technology Virginia Tech. University
How to Cite
Park, Y. (2011). A pedagogical framework for mobile learning: Categorizing educational applications of mobile technologies into four types. The International Review of Research in Open and Distributed Learning, 12(2), 78-102.
Research Articles