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Analysis of research trends in English learning motivation in Korea using text mining

  • Modern English Education
  • Abbr : MEESO
  • 2023, 24(), pp.317-340
  • Publisher : The Modern English Education Society
  • Research Area : Humanities > English Language and Literature > English Language Teaching
  • Received : October 26, 2023
  • Accepted : November 30, 2023
  • Published : December 31, 2023

Kim, Tae Young 1 Shinyu Oh 1 이은진 1

1중앙대학교

Accredited

ABSTRACT

This study identified trends in motivation and demotivation research in English language learning in South Korea over a 28-year period, from 1996 to June 2023, utilizing text mining techniques. With the 506 extracted abstracts from RISS and KCI, we conducted TF-IDF analysis and Latent Dirichlet Allocation (LDA) topic modelling analysis. The study categorized the 506 studies into four periods to identify trends in each period. The results showed that the number of motivation and demotivation studies steadily increased, especially during the third period (2010-2016). Keyword frequency and TF-IDF analysis revealed that the terms ‘self’ and ‘factor’ were highly frequent, and ‘strategy’ and ‘demotivation’ carried significant weight in specific documents. The first period primarily concentrated on learners’ motivational factors in English learning, whereas the second and third periods explored motivation and demotivation among learners and teachers, as well as the impact of teachers’ motivation on learners. The fourth period extended its focus beyond motivation and demotivation to include remotivation. This study holds significance in synthesizing the research trends based on word frequency in the abstracts of articles on (de)motivation in English learning, conducted from 1996 to 2023.

Citation status

* References for papers published after 2023 are currently being built.