Investigation of Emerging Trends in the E-Learning Field Using Latent Dirichlet Allocation
dc.authorscopusid | 57194776706 | |
dc.authorscopusid | 35614751000 | |
dc.authorscopusid | 16237826800 | |
dc.contributor.author | Gurcan,F. | |
dc.contributor.author | Ozyurt,O. | |
dc.contributor.author | Cagiltay,N.E. | |
dc.date.accessioned | 2024-09-10T21:35:47Z | |
dc.date.available | 2024-09-10T21:35:47Z | |
dc.date.issued | 2021 | |
dc.department | Atılım University | en_US |
dc.department-temp | Gurcan F., Distance Education Application and Research Centre, Karadeniz Technical University, Trabzon, Turkey; Ozyurt O., Karadeniz Technical University, OF Technology Faculty, Software Engineering Department, Trabzon, Turkey; Cagiltay N.E., Software Engineering Department, Atilim University, Ankara, Turkey | en_US |
dc.description.abstract | 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 “elearning 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. © 2021. International Review of Research in Open and Distance Learning. All Rights Reserved. | en_US |
dc.identifier.citation | 40 | |
dc.identifier.doi | 10.19173/irrodl.v22i2.5358 | |
dc.identifier.endpage | 18 | en_US |
dc.identifier.issn | 1492-3831 | |
dc.identifier.issue | 2 | en_US |
dc.identifier.scopus | 2-s2.0-85107655935 | |
dc.identifier.scopusquality | Q1 | |
dc.identifier.startpage | 1 | en_US |
dc.identifier.uri | https://doi.org/10.19173/irrodl.v22i2.5358 | |
dc.identifier.volume | 22 | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | International Review of Research in Open and Distributed Learning | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | developmental stages | en_US |
dc.subject | e-learning | en_US |
dc.subject | text mining | en_US |
dc.subject | topic modeling | en_US |
dc.subject | trends | en_US |
dc.title | Investigation of Emerging Trends in the E-Learning Field Using Latent Dirichlet Allocation | en_US |
dc.type | Article | en_US |
dspace.entity.type | Publication |