Utilizing Technology to Develop Deep Learning Methods in Foreign Language Education: A Bibliometric Analysis - Am, St. Asriati; Am, St. Asmayanti; Rahmi, Rahmi (NOBEL: Journal of Literature and Language Teaching, 2026)
This study examines how technology has been used to support deep learning in English as a Foreign Language (EFL) and maps research trends in this area through bibliometric analysis. The study used literature data retrieved from Google Scholar through the Publish or Perish database, covering publications from 2019 to 2022. A total of 110 publications were analyzed, including journal articles, books, conference proceedings, and book chapters. The analysis employed descriptive statistics to identify publication trends by year, document types, and citation counts. In addition, bibliometric mapping was conducted using VOSviewer to visualize keyword co-occurrence patterns and thematic clusters in the literature. The results show that technology plays an important role in supporting deep learning in EFL by helping teachers design learning activities and engage students more actively in the learning process. The keyword network also indicates that research in this area is closely related to language learning, teaching approaches, strategies, knowledge, and educational processes. Overall, the findings suggest that technology has strong potential to support the achievement of learning objectives in EFL contexts.