Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Journal of Early Childhood Development and Education International Journal of Sustainable Business, Management and Accounting
Adlan, Amel Zulfukar Hassan
Unknown Affiliation
Economics, Econometrics & Finance Education Social Sciences Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
The Role of Artificial Intelligence in Enhancing Sustainable Accounting and ESG Reporting: A Systematic Literature Review Risdianto, Eko; Adlan, Amel Zulfukar Hassan; Avazovna, Usmanova Shokhsanam
International Journal of Sustainable Business, Management and Accounting Vol. 2 No. 1 (2026): International Journal of Sustainable Business, Management, and Accounting (IJSB
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijsbma.v2i1.170

Abstract

Background of study: The increasing demand for sustainability and transparency has strengthened the role of sustainable accounting and Environmental, Social, and Governance (ESG) reporting in modern business practices. However, traditional reporting systems face significant challenges in managing complex, large-scale, and heterogeneous ESG data, leading to limitations in accuracy, consistency, and timeliness. Although artificial intelligence (AI) has been widely adopted in financial analysis, its application in sustainable accounting and ESG reporting remains fragmented and underexplored. Aims: This study aims to provide a comprehensive and structured analysis of the role of AI in enhancing sustainable accounting and ESG reporting. Methods: This study employs a Systematic Literature Review (SLR) using the PRISMA framework, combined with bibliometric analysis. Data were collected from the Scopus database using three keyword strategies and filtered based on predefined inclusion criteria. The dataset was cleaned using OpenRefine and analyzed using VOSviewer and Biblioshiny to explore research trends, thematic structures, and intellectual development. Result: The results show that AI technologies, particularly machine learning, natural language processing, and big data analytics, significantly improve ESG data processing, reporting efficiency, and predictive decision-making. However, ESG reporting practices remain fragmented, lack standardization, and are often implemented in isolated contexts. Conclusion: This study contributes by integrating AI, sustainable accounting, and ESG reporting into a unified perspective supported by systematic and bibliometric analysis. The findings highlight the potential of AI to enhance transparency and efficiency in sustainability reporting, while emphasizing the need for integrative frameworks and empirical validation in future research.
Language Learning and Emotional Growth: A Study of Preschool Children in Multilingual Contexts – Sudan Adlan, Amel Zulfukar Hassan; Badawi, Khabir Othman Mohamed; Chikopela, Rose
Journal of Early Childhood Development and Education Vol. 3 No. 2 (2026): Journal of Early Childhood Development and Education (May)
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/junior.v3i2.694

Abstract

Background: The development of young children is greatly dependent on language exposure, but the relationship between multilingualism and socio-emotional development remains relatively unexplored with regard to Sudanese culture. Multilingualism in the Sudanese culture involves a combination of Arabic, English, and dialect, which can work as a tool to foster cognitive and emotional resilience in early childhood. Objective: This paper seeks to establish the role of multilingual settings in the development of cognitive flexibility and socio-emotional intelligence in preschoolers (3–5 years old) enrolled in the Noor Albayan Kindergarten in Atbara, Sudan. Methods: Through the use of convergent parallel mixed methods research design, the study conducted a quantitative assessment of 25 children ($N=25$) using Sort-Switch tasks. The quantitative data obtained were subjected to analysis through one sample t-tests ($df=24$). On the other hand, qualitative data were obtained by conducting semi-structured interviews involving 10-12 key informants (teachers and parents). Results: Analysis of the quantitative data showed that multilingual children scored 72% on problem-solving tasks ($t (24) =9.17, p<.001$). Additionally, they scored 68% on social adaptation skills ($t (24) =6.43, p<.005$) and 65% on emotional awareness tasks ($t (24) =5.00, p<.005$). Moreover, qualitative data showed. Conclusion: These results indicate that bilingualism speeds up the development of prefrontal cortex and emotional differentiation. The findings of this paper recommend the application of translanguaging practices in Sudanese Early Childhood Education (ECE).
Co-Authors Avazovna, Usmanova Shokhsanam Badawi, Khabir Othman Mohamed Chikopela, Rose Eko Risdianto