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Publication Trends on Mobile Learning in Science Education

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Mobile learning is gaining popularity in science classes because it has the potential to increase student engagement and learning. This bibliometric analysis examines the trends in mobile learning and science education publications. Scopus and Web of Science (WoS) datasets were used in this bibliometric analysis. ScientoPy was employed to analyse the data obtained using keywords (“mobile learning” OR “m-learning”) AND (“science education” OR “science learning” OR “science teaching” OR “science”). The keywords “Mobile learning”, “e-learning”, “mobile devices”, “gamification,” and “higher education” are the top five keywords used in previous publications. With 32 publications, the most productive institution is the National Taiwan University of Science and Technology. The top three source titles are Computers & Education, Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Bioinformatics), and the International Journal of Mobile Learning and Organization. The study’s results give an overview of how mobile learning in science education has changed and can guide future research in this field. This bibliometric analysis also illustrates the current research on mobile learning in science education. The results suggest that mobile learning could be an excellent way to get students more interested in science and help them learn more. Inevitably, this bibliometric review of mobile learning in education only scratches the surface of a vast body of literature, with some parts of the theme have been disregarded.
Title: Publication Trends on Mobile Learning in Science Education
Description:
Mobile learning is gaining popularity in science classes because it has the potential to increase student engagement and learning.
This bibliometric analysis examines the trends in mobile learning and science education publications.
Scopus and Web of Science (WoS) datasets were used in this bibliometric analysis.
ScientoPy was employed to analyse the data obtained using keywords (“mobile learning” OR “m-learning”) AND (“science education” OR “science learning” OR “science teaching” OR “science”).
The keywords “Mobile learning”, “e-learning”, “mobile devices”, “gamification,” and “higher education” are the top five keywords used in previous publications.
With 32 publications, the most productive institution is the National Taiwan University of Science and Technology.
The top three source titles are Computers & Education, Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Bioinformatics), and the International Journal of Mobile Learning and Organization.
The study’s results give an overview of how mobile learning in science education has changed and can guide future research in this field.
This bibliometric analysis also illustrates the current research on mobile learning in science education.
The results suggest that mobile learning could be an excellent way to get students more interested in science and help them learn more.
Inevitably, this bibliometric review of mobile learning in education only scratches the surface of a vast body of literature, with some parts of the theme have been disregarded.

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