作者: Jui-Long Hung , Ke Zhang
DOI: 10.1007/S12528-011-9044-9
关键词: Bibliometrics 、 Educational technology 、 Content analysis 、 Trend analysis 、 Information retrieval 、 Meta-analysis 、 M-learning 、 Text mining 、 Categorical variable 、 Computer science
摘要: This study investigated the longitudinal trends of academic articles in Mobile Learning (ML) using text mining techniques. One hundred and nineteen (119) refereed journal proceedings papers from SCI/SSCI database were retrieved analyzed. The taxonomies ML publications grouped into twelve clusters (topics) four domains, based on abstract analysis mining. Results include basic bibliometric statistics, frequency each topic over time, predominance by country, preferences for journal. Key findings following: (a) increased 8 2003 to 36 2008; (b) most popular domain current is Effectiveness, Evaluation, Personalized Systems; (c) Taiwan prolific five clusters; (d) research at Early Adopters stage; (e) studies strategies framework will likely produce a bigger share publication field ML.