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Research and trends in mobile learning from 1976 to 2013: A content analysis of patents in selected databases
Author(s) -
Chiang FengKuang,
Zhu Gaoxia,
Wang Qi,
Cui Zhenfeng,
Cai Su,
Yu Shengquan
Publication year - 2016
Publication title -
british journal of educational technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.79
H-Index - 95
eISSN - 1467-8535
pISSN - 0007-1013
DOI - 10.1111/bjet.12311
Subject(s) - computer science , multimedia , world wide web , context (archaeology) , dimension (graph theory) , class (philosophy) , mobile device , service (business) , space (punctuation) , artificial intelligence , paleontology , mathematics , economy , pure mathematics , economics , biology , operating system
Mobile learning has been a very popular topic in the past several decades. As more patents in this field have been submitted, the analysis of patents has surfaced as an important mechanism to understand trends, uses, targeted audiences and other aspects in the mobile learning space. Based on the CNIPR , USPTO , and Espacenet databases, this paper provides an analysis of mobile learning from 1976, when the first patent in mobile learning emerged, to 2013. One hundred thirty patents were analyzed from two dimensions: the instructional dimension (including target audience, situation and purpose) and the patent dimension (including technology and style). It was found that “students” was the most popular target audience; “out of class for education” was the most utilized situation; “provide more friendly peripheral service” was the primary purpose; “wireless, mobile and ubiquitous technologies for learning, pervasive computing for learning, u‐computing in learning” were the most utilized technologies; and “system and method” was the most common style. Currently, patents in mobile learning are more inclined to provide personalized, contextualized, easily‐retrievable, auto‐updated and intelligent pushed learning content. Additionally, providing multipresentation, supporting seamless learning, adopting learner analysis, improving learner diversity and context awareness are becoming the characteristics of mobile learning patents.