ERIC Number: EJ1295177
Record Type: Journal
Publication Date: 2021
Pages: 17
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0022-0485
EISSN: N/A
What Do Economic Education Scholars Study? Insights from Machine Learning
Journal of Economic Education, v52 n2 p156-172 2021
The authors of this article use text mining techniques to uncover hidden or latent topics in economic education. The common use of JEL codes only identifies the academic setting for each paper but does not identify the underlying economic concept the paper addresses. An unsupervised machine learning algorithm called Latent Dirichlet Allocation is utilized to identify 15 hidden topics in economic education scholarly work. The text mining model identifies economic education topics by finding correlations in word usage across different documents. The authors show that these newly identified research topics explain more variation in citation counts than the commonly adopted JEL codes. Moreover, specific journals display preferences for certain topics within economic education research.
Descriptors: Economics Education, Educational Research, Artificial Intelligence, Scholarship, Indexing, Citations (References), Periodicals
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A