Latent Dirichlet Allocation-Based Topic Mining Analysis of Educational Scientific Research Projects Based on 2360 NSF Education Projects

Author:

Han Jining1,Liu Geping1,Yang Yuying1

Affiliation:

1. Faculty of Education, Southwest University, Chongqing, China

Abstract

The National Science Foundation has promoted the development of education in the U.S., and its establishment reflects the trend of education development. This study collects the data on 2360 NSF educational projects over the last three years to answer two research questions: What are the major research topics of NSF educational projects? What are the key projects doing? Through Latent Dirichlet allocation topic modelling, content analysis is carried out on the titles and abstracts of the 2360 projects, and eight topics are obtained from them, including top-notch innovative talent cultivation, STEM education for low-income groups, undergraduate education, vocational education, cutting-edge technology education, big data-driven technology, artificial intelligence, and teacher development.

Publisher

Association for Information Communication Technology Education and Science (UIKTEN)

Subject

Management of Technology and Innovation,Information Systems and Management,Strategy and Management,Education,Information Systems,Computer Science (miscellaneous)

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