An Augmented Reality-Based Mobile Learning System to Improve Students' Learning Achievements and Motivations in Natural Science Inquiry Activities

364 indexed citations
published 2014

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This map shows the geographic impact of An Augmented Reality-Based Mobile Learning System to Improve Students' Learning Achievements and Motivations in Natural Science Inquiry Activities. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by An Augmented Reality-Based Mobile Learning System to Improve Students' Learning Achievements and Motivations in Natural Science Inquiry Activities with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites An Augmented Reality-Based Mobile Learning System to Improve Students' Learning Achievements and Motivations in Natural Science Inquiry Activities more than expected).

Fields of papers citing An Augmented Reality-Based Mobile Learning System to Improve Students' Learning Achievements and Motivations in Natural Science Inquiry Activities

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of An Augmented Reality-Based Mobile Learning System to Improve Students' Learning Achievements and Motivations in Natural Science Inquiry Activities. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the An Augmented Reality-Based Mobile Learning System to Improve Students' Learning Achievements and Motivations in Natural Science Inquiry Activities.

About An Augmented Reality-Based Mobile Learning System to Improve Students' Learning Achievements and Motivations in Natural Science Inquiry Activities

This paper, published in 2014, received 364 indexed citations . Written by Stephen J.H. Yang and Gwo‐Jen Hwang covering the research area of Computer Vision and Pattern Recognition, Automotive Engineering and Information Systems. It is primarily cited by scholars working on Computer Vision and Pattern Recognition (233 citations), Information Systems (203 citations) and Human-Computer Interaction (130 citations).

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This paper is also available at doi.org/w83618177.

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