Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
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This Author published in this journals
All Journal International Journal of Social Science, Education, Communication and Economics International Journal of Education and Digital Learning (IJEDL)
Zhang Ling
Zhengzhou Institute of Technology of China
Religion Arts Humanities Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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Review of Instructional Digital Media to Path Teachers’ Digital Competence on Philosophical Perspective: Distraction or Diversion Syofianis Ismail; Zhang Ling; Erna Nawir; Alber Alber; Desna Fauziah
International Journal of Education and Digital Learning (IJEDL) Vol. 1 No. 4 (2023)
Publisher : Lafadz Jaya Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47353/ijedl.v1i4.24

Abstract

In spite of its emergence in 1980s, digital media has been well known to this day, yet it is still questioned whether its presence is merely a "disturbance" or a "diversion" after contradictory impacts of digital media usage have been found based on several conducted studies. Answering the question, library research was carried out by using some sources and references in getting and analyzing the data. Then, the writers integrated their ideas by synthesizing in drawing conclusion. Delving into the essence of four learning theories (behaviorism, cognitivism, constructivism, and connectivism) and their integration with technology, particular media use and their functions are recognized through a systematic procedure in certain digital learning approach as one alternative for teachers in selecting and utilizing digital media in learning process. It was found that, firstly, the comprehension basic learning philosophy serves as fundamental reasons for teachers in utilizing technology. Secondly, the learning theories play as the base for teachers to develop their teaching approaches by maximizing their digital competence through digital technology use for improving their digital literacy. Lastly, the ownership of knowledge and skill for instructional digital media use develops teachers’ digital competence by recognizing students’ need in learning. In a nutshell, the choice for digital media utilization has to be supported by understanding the intensive relation between teachers and their learners’ roles and the instructional strategies in integrating media and technology used which will awaken not only teachers’ digital literacy, but especially their digital competence as well, as displayed through their ability to be intricately connected to digital media use. Therefore, the comprehensive understanding of learning theories approach of teachers and their ways in utilizing media-based technology determines the function of the media itself whether it is distraction or diversion during teaching and learning process.
Artificial Intelligence in Financial Crisis Early Warning Systems: Predictive Capability, Emerging Risks, and Governance in 2026 Zhang Ling; Syofianis Ismail
International Journal of Social Science, Education, Communication and Economics (SINOMICS Journal) Vol. 5 No. 1 (2026): April
Publisher : Lafadz Jaya Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47353/sj.v5i1.538

Abstract

Financial crisis early warning systems (EWS) are being reshaped by artificial intelligence (AI), the growth of alternative data, and the increasing interconnection of financial and digital infrastructures. This article revisits AI-enabled EWS through a 2026 lens, moving beyond prediction accuracy to consider systemic risk transmission, cyber resilience, model governance, and the financial stability implications of AI adoption itself. An integrative literature review was conducted using foundational peer-reviewed research on machine learning and crisis prediction alongside recent institutional publications available in 2025–2026, including work from the Bank for International Settlements, the International Monetary Fund, and the Bank of England. The synthesis indicates that machine learning can improve the identification of nonlinear patterns and combine macrofinancial indicators with market-based and textual signals, but its value depends on rigorous validation, stable data pipelines, and decision processes that remain accountable to human authorities. The 2026 policy discussion also highlights a dual relationship: AI can strengthen surveillance and cyber defense while simultaneously amplifying correlated behaviour, concentration risk, third-party dependency, and the speed and scale of cyber incidents. Accordingly, an effective AI-based EWS should combine predictive models with interpretable outputs, scenario analysis, operational-resilience indicators, and clearly assigned intervention responsibilities. The article proposes a layered governance framework linking data and models, institution-level vulnerabilities, system-wide transmission channels, and policy response. It concludes that AI should be treated as decision support within a broader financial stability architecture, rather than as an autonomous substitute for supervisory judgment.
Co-Authors Desna Fauziah Nawir, Erna Syofianis Ismail