Investigation of Emerging Trends in the E-Learning Field Using Latent Dirichlet Allocation

  • Fatih Gurcan Karadeniz Technical University
  • Ozcan Ozyurt Karadeniz Technical University
  • Nergiz Ercil Cagitay Atilim University
Keywords: e-learning, text-mining, topic modeling, trends, developmental stages


E-learning studies are becoming very important today as they provide alternatives and support to all types of teaching and learning programs. The effect of the COVID-19 pandemic on educational systems has further increased the significance of e-learning. Accordingly, gaining a full understanding of the general topics and trends in e-learning studies is critical for a deeper comprehension of the field. There are many studies that provide such a picture of the e-learning field, but the limitation is that they do not examine the field as a whole. This study aimed to investigate the emerging trends in the e-learning field by implementing a topic modeling analysis based on latent Dirichlet allocation (LDA) on 41,925 peer-reviewed journal articles published between 2000 and 2019. The analysis revealed 16 topics reflecting emerging trends and developments in the e-learning field. Among these, the topics “MOOC,” “learning assessment,” and “e-learning systems” were found to be key topics in the field, with a consistently high volume. In addition, the topics of “learning algorithms,” “learning factors,” and “adaptive learning” were observed to have the highest overall acceleration, with the first two identified as having a higher acceleration in recent years. Going by these results, it is concluded that the next decade of e-learning studies will focus on learning factors and algorithms, which will possibly create a baseline for more individualized and adaptive mobile platforms. In other words, after a certain maturity level is reached by better understanding the learning process through these identified learning factors and algorithms, the next generation of e-learning systems will be built on individualized and adaptive learning environments. These insights could be useful for e-learning communities to improve their research efforts and their applications in the field accordingly.

Author Biographies

Fatih Gurcan, Karadeniz Technical University

FATIH GURCAN received a B.S. degree in statistics and computer science, a M.S. degree in computer engineering, and a Ph.D. degree in computer engineering from Karadeniz Technical University, Trabzon, Turkey, in 2001, 2009, and 2017, respectively. He was an Instructor with the Department of Informatics at Karadeniz Technical University, from 2001 to 2014, where he has been an Instructor with the Centre for Research and Application in Distance Education, since 2015. His research interests include trend analysis, sentiment analysis, statistical topic modelling, engineering education, data mining, machine learning, big data analytics, and text mining.

Ozcan Ozyurt, Karadeniz Technical University

OZCAN OZYURT received B.Sc. and M.Sc. degrees in Computer Engineering from Karadeniz Technical University in 1996 and 2000, respectively. He completed his doctoral studies on adaptive educational hypermedia in mathematics education at Karadeniz Technical University in 2013. Presently, he is a full-time faculty member as Assoc. Prof. Dr. in the Software Engineering Department of Technology Faculty at Karadeniz Technical University, Trabzon, Turkey. His major research interests are in the use of artificial intelligence in education, adaptive and intelligent tutoring systems, educational software engineering, e-learning and educational data mining.

Nergiz Ercil Cagitay, Atilim University

NERGIZ ERCIL CAGILTAY received a degree in computer engineering and a Ph.D. in instructional technologies from Middle East Technical University, Turkey. She worked for commercial and government organizations as a Project Manager for more than eight years in Turkey. She was also with the Indiana University Digital Library Program as a System Analysis and a Programmer for four years. She has been with the Software Engineering Department at Atilim University, Turkey, since 2003 as an Associate Professor. Her main research interests include information systems, medical information systems, engineering education, instructional systems technologies, distance education, e-learning, and medical education.


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How to Cite
Gurcan, F., Ozyurt, O., & Cagitay, N. E. (2021). Investigation of Emerging Trends in the E-Learning Field Using Latent Dirichlet Allocation. The International Review of Research in Open and Distributed Learning, 22(2), 1-18.
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