The Future of Distance Education: Exploring the Potential of Adaptive Learning Systems

Bülent Kandemir; Necati Taşkın

Article Details

The Future of Distance Education: Exploring the Potential of Adaptive Learning Systems

Authors:

Bülent Kandemir | Necati Taşkın

Publisher:

Ordu University

Main Topics:

Bilgi Sistemleri Eğitimi | Bilgi Sistemleri (Diğer)

Journal:

Ordu Üniversitesi Bilim ve Teknoloji Dergisi Vol.14 Issue 2, pp.273-292

Document Type:

Article

Publication Date:

12/2024

Document Language:

English

Document ID (Org No.):

2001332807

pISSN:

2146-6440

Keywords:

Abstract:

 Adaptive learning technologies are used in many areas of education, including online distance learning. This study investigates the applications of Adaptive Learning technology in distance education environments. Following the steps of systematic literature review and using bibliometric analysis, the study examines a total of 1071 publications. Accordingly, time trend analysis has increased steadily within recent years, and Educational Research, Computer Science, and Engineering are the leading subject areas in research on Adaptive Learning in distance education. China and USA are the countries that make the most of the contribution, followed by Taiwan, Spain, and India. Kinshuk is the author who contributed the most, followed by Caballé and Santi. The most collaborative authors are Capuano and Nicola, Ritrovato and Pierluigi, Cabelle and Santi, and Gaeta and Matteo. Pierri and Anna hold central positions in the co-authoring network. The top three journals with the most publications are Computers  Education, International Journal of Distance Education, and Academic Medicine, all with significant citation counts. The most frequently used keywords are e-learning, followed by adaptive learning, and online learning. Integrating artificial intelligence and machine learning techniques presents significant potential for enhancing adaptive learning technologies. Utilizing frameworks such as learning analytics and the Technology Acceptance Model can help identify effective strategies to increase system acceptability.

 Adaptive learning technologies are used in many areas of education, including online distance learning. This study investigates the applications of Adaptive Learning technology in distance education environments. Following the steps of systematic literature review and using bibliometric analysis, the study examines a total of 1071 publications. Accordingly, time trend analysis has increased steadily within recent years, and Educational Research, Computer Science, and Engineering are the leading subject areas in research on Adaptive Learning in distance education. China and USA are the countries that make the most of the contribution, followed by Taiwan, Spain, and India. Kinshuk is the author who contributed the most, followed by Caballé and Santi. The most collaborative authors are Capuano and Nicola, Ritrovato and Pierluigi, Cabelle and Santi, and Gaeta and Matteo. Pierri and Anna hold central positions in the co-authoring network. The top three journals with the most publications are Computers  Education, International Journal of Distance Education, and Academic Medicine, all with significant citation counts. The most frequently used keywords are e-learning, followed by adaptive learning, and online learning. Integrating artificial intelligence and machine learning techniques presents significant potential for enhancing adaptive learning technologies. Utilizing frameworks such as learning analytics and the Technology Acceptance Model can help identify effective strategies to increase system acceptability.

 Adaptive learning technologies are used in many areas of education, including online distance learning. This study investigates the applications of Adaptive Learning technology in distance education environments. Following the steps of systematic literature review and using bibliometric analysis, the study examines a total of 1071 publications. Accordingly, time trend analysis has increased steadily within recent years, and Educational Research, Computer Science, and Engineering are the leading subject areas in research on Adaptive Learning in distance education. China and USA are the countries that make the most of the contribution, followed by Taiwan, Spain, and India. Kinshuk is the author who contributed the most, followed by Caballé and Santi. The most collaborative authors are Capuano and Nicola, Ritrovato and Pierluigi, Cabelle and Santi, and Gaeta and Matteo. Pierri and Anna hold central positions in the co-authoring network. The top three journals with the most publications are Computers  Education, International Journal of Distance Education, and Academic Medicine, all with significant citation counts. The most frequently used keywords are e-learning, followed by adaptive learning, and online learning. Integrating artificial intelligence and machine learning techniques presents significant potential for enhancing adaptive learning technologies. Utilizing frameworks such as learning analytics and the Technology Acceptance Model can help identify effective strategies to increase system acceptability.

 Uyarlanabilir öğrenme teknolojileri, çevrim içi uzaktan eğitim de dahil olmak üzere birçok eğitim alanında kullanılmaktadır. Bu çalışma, uyarlanabilir öğrenme teknolojisinin uzaktan eğitim ortamlarındaki uygulamalarını araştırmaktadır. Sistematik literatür taraması adımlarını izleyerek ve bibliyometrik analiz kullanarak, çalışma toplamda 1071 yayını incelemektedir. Buna göre, son yıllarda zaman eğilimi analizi istikrarlı bir artış göstermiş olup, uzaktan eğitimde uyarlanabilir öğrenme üzerine yapılan araştırmalarda Eğitim Araştırmaları, Bilgisayar Bilimleri ve Mühendislik önde gelen konu alanlarıdır. Çin ve ABD en fazla katkıda bulunan ülkeler olup, onları Tayvan, İspanya ve Hindistan takip etmektedir. En çok katkıda bulunan yazar Kinshuk iken, onu Caballé ve Santi izlemektedir. En çok iş birliği yapan yazarlar Capuano ve Nicola, Ritrovato ve Pierluigi, Caballé ve Santi ile Gaeta ve Matteodur. Pierri ve Anna, ortak yazar ağında merkezi konumlara sahiptir. En fazla yayına sahip ilk üç dergi, önemli atıf sayılarıyla Computers  Education, International Journal of Distance Education ve Academic Medicinedir. En sık kullanılan anahtar kelimeler e-öğrenme, ardından uyarlanabilir öğrenme ve çevrimiçi öğrenmedir. Yapay zekâ ve makine öğrenimi tekniklerinin entegrasyonu, uyarlanabilir öğrenme teknolojilerini geliştirme potansiyelini önemli ölçüde artırmaktadır. Öğrenme analitikleri ve Teknoloji Kabul Modeli gibi çerçevelerin kullanılması, sistemin kabul edilebilirliğini artıracak etkili stratejilerin belirlenmesine yardımcı olabilir.

Article Details

The Future of Distance Education: Exploring the Potential of Adaptive Learning Systems

Authors:

Bülent Kandemir | Necati Taşkın

Publisher:

Ordu University

Main Topics:

Bilgi Sistemleri Eğitimi | Bilgi Sistemleri (Diğer)

Journal:

Ordu Üniversitesi Bilim ve Teknoloji Dergisi Vol.14 Issue 2, pp.273-292

Document Type:

Article

Publication Date:

12/2024

Document Language:

English

Document ID (Org No.):

2001332807

pISSN:

2146-6440

adaptive learning

distance education

systematic literature review

bibliometric analysisuyarlanabilir öğrenme

uzaktan eğitim

sistematik literatür incelemesi

bibliyometrik analiz

Issues

Article Details

Authors: Bülent Kandemir | Necati Taşkın

Publisher: Ordu University

Main Topics: Bilgi Sistemleri Eğitimi | Bilgi Sistemleri (Diğer)

Journal: Ordu Üniversitesi Bilim ve Teknoloji Dergisi Vol.14 Issue 2, pp.273-292

Document Type: Article

Publication Date: 12/2024

Document Language: English

Document ID (Org No.): 2001332807

pISSN: 2146-6440

Issues

Authors:

Bülent Kandemir | Necati Taşkın

Publisher:

Ordu University

Main Topics:

Bilgi Sistemleri Eğitimi | Bilgi Sistemleri (Diğer)

Journal:

Ordu Üniversitesi Bilim ve Teknoloji Dergisi Vol.14 Issue 2, pp.273-292

Document Type:

Article

Publication Date:

12/2024

Document Language:

English

Document ID (Org No.):

2001332807

pISSN:

2146-6440