<p>This study aims to offer detailed insights into the evolution of digital learning by exploring universal trends and shifts. To achieve this aim, we conducted a comprehensive investigation of academic literature from prominent journals on digital learning. The academic literature was categorized into two stages based on publication years. Stage 1 (pre-COVID-19) spans from July 2015 to December 2019, while Stage 2 (during and post-COVID-19) covers January 2020 to June 2024. The Term Frequency–Inverse Document Frequency (TF–IDF) method was then applied to rank the importance of keywords in each academic paper. For each paper, the five keywords with the highest TF–IDF values were extracted and treated as its subject topics. Subsequently, the five most frequently occurring subject topics were identified as representing trends in digital learning within leading five countries/regions. Results showed the USA’s consistent leadership in digital learning research, with China and Taiwan maintaining strong positions. Moreover, there were shifts in subject topics between the two aforementioned stages. In Stage 1, mobile learning and online assessment were dominant subject topics. In Stage 2, digital games and virtual reality emerged as key subject topics, indicating a trend towards immersive and interactive technologies. Additionally, the findings revealed country-specific and general changes across these two stages. This study not only advances academic knowledge of trends and shifts in digital learning, but also provides practical implications for researchers, instructors, and designers in digital learning, enabling such stakeholders to adapt strategies and develop innovative tools for modern educational settings.</p>

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The universal trend and shifts of digital learning: big data analysis for academic literature

  • Erik Chihhung Chang,
  • Lex Chen,
  • Sherry Y. Chen

摘要

This study aims to offer detailed insights into the evolution of digital learning by exploring universal trends and shifts. To achieve this aim, we conducted a comprehensive investigation of academic literature from prominent journals on digital learning. The academic literature was categorized into two stages based on publication years. Stage 1 (pre-COVID-19) spans from July 2015 to December 2019, while Stage 2 (during and post-COVID-19) covers January 2020 to June 2024. The Term Frequency–Inverse Document Frequency (TF–IDF) method was then applied to rank the importance of keywords in each academic paper. For each paper, the five keywords with the highest TF–IDF values were extracted and treated as its subject topics. Subsequently, the five most frequently occurring subject topics were identified as representing trends in digital learning within leading five countries/regions. Results showed the USA’s consistent leadership in digital learning research, with China and Taiwan maintaining strong positions. Moreover, there were shifts in subject topics between the two aforementioned stages. In Stage 1, mobile learning and online assessment were dominant subject topics. In Stage 2, digital games and virtual reality emerged as key subject topics, indicating a trend towards immersive and interactive technologies. Additionally, the findings revealed country-specific and general changes across these two stages. This study not only advances academic knowledge of trends and shifts in digital learning, but also provides practical implications for researchers, instructors, and designers in digital learning, enabling such stakeholders to adapt strategies and develop innovative tools for modern educational settings.