Razia Sultana Parul
Razia Sultana Parul has a total of 9 co-authors. Here are the top co-authors by number of shared publications:
- A. K. M. Kanak Pervez
Department of Agronomy and Agricultural Extension, University of Rajshahi, Rajshahi, Bangladesh
1 shared publication - Abu Nayem Mia1 shared publication
Abu Sadat
1 shared publication- Al Farazi Maruf
Information Science and Library Management, University of Rajshahi, Rajshahi-6205, Bangladesh
1 shared publication - Armanul Haque
University of Rajshahi Department of Information Science and Library Management
1 shared publication - Mahbubul Islam
Department of Information Science and Library Management, University of Rajshahi, Rajshahi 6205, Bangladesh
1 shared publication
Latest Publications
- 16 June 2025
- Published by Sciencedomain International in Asian Journal of Education and Social Studies
- Vol. 51 (7) , 902-923
Exploring Difficulties in Internet Adaptation for Students in Developing Countries: A Machine Learning Approach to Network Visualization and Cluster Analysis
Aim: This study investigates the challenges students in developing countries face in adapting to internet-based education. It aims to identify key trends, influential contributors, and research gaps, with a particular emphasis on the potential of innovative technologies such as artificial intelligence (AI) and blockchain in addressing digital inequality. Methods: A bibliometric analysis was conducted on 352 scholarly documents sourced from the Scopus database. Advanced analytical tools, including Machine Learning techniques, R programming, Bibliometrix, and VOSviewer, were employed to assess performance indicators, visualize topic clusters, and map the research landscape. Findings: The analysis indicates a growing body of research focused on digital adaptation in education, with substantial contributions from Germany, India, and the UK. Although Hong Kong and Singapore contribute fewer publications, their research garners high citation visibility. Prominent authors such as Choo, Fung, and Wootton have significantly influenced the field. The study identified five major thematic clusters: psychosocial barriers (e.g., internet addiction and academic stress), technological innovations (AI, blockchain, and digital platforms), socioeconomic challenges (connectivity costs and gender disparities), research trends and bibliometric mapping, and multi-stakeholder collaboration involving government, academia, and civil society. A notable research gap exists regarding the practical implementation of AI and blockchain to alleviate these challenges. Originality: This study is among the few to systematically map the global academic discourse on internet adaptation in education within developing regions using bibliometric and machine learning approaches. It introduces an interdisciplinary perspective by combining education, technology, and policy analysis. Academic Value: By synthesizing global research trends and highlighting underexplored areas, particularly the role of emerging technologies, gender disparities, and collaborative strategies, this study provides a valuable reference for scholars, policymakers, and educators. Additionally, by identifying key gaps, it supports evidence-based policy formulation and encourages further localized, gender-sensitive research and pilot interventions to enhance educational equity.
- 16 June 2025
- Published by Sciencedomain International in Asian Journal of Education and Social Studies
- Vol. 51 (7) , 902-923
Exploring Difficulties in Internet Adaptation for Students in Developing Countries: A Machine Learning Approach to Network Visualization and Cluster Analysis
Aim: This study investigates the challenges students in developing countries face in adapting to internet-based education. It aims to identify key trends, influential contributors, and research gaps, with a particular emphasis on the potential of innovative technologies such as artificial intelligence (AI) and blockchain in addressing digital inequality. Methods: A bibliometric analysis was conducted on 352 scholarly documents sourced from the Scopus database. Advanced analytical tools, including Machine Learning techniques, R programming, Bibliometrix, and VOSviewer, were employed to assess performance indicators, visualize topic clusters, and map the research landscape. Findings: The analysis indicates a growing body of research focused on digital adaptation in education, with substantial contributions from Germany, India, and the UK. Although Hong Kong and Singapore contribute fewer publications, their research garners high citation visibility. Prominent authors such as Choo, Fung, and Wootton have significantly influenced the field. The study identified five major thematic clusters: psychosocial barriers (e.g., internet addiction and academic stress), technological innovations (AI, blockchain, and digital platforms), socioeconomic challenges (connectivity costs and gender disparities), research trends and bibliometric mapping, and multi-stakeholder collaboration involving government, academia, and civil society. A notable research gap exists regarding the practical implementation of AI and blockchain to alleviate these challenges. Originality: This study is among the few to systematically map the global academic discourse on internet adaptation in education within developing regions using bibliometric and machine learning approaches. It introduces an interdisciplinary perspective by combining education, technology, and policy analysis. Academic Value: By synthesizing global research trends and highlighting underexplored areas, particularly the role of emerging technologies, gender disparities, and collaborative strategies, this study provides a valuable reference for scholars, policymakers, and educators. Additionally, by identifying key gaps, it supports evidence-based policy formulation and encourages further localized, gender-sensitive research and pilot interventions to enhance educational equity.