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All Journal International Journal of Multidisciplinary Approach Research and Science MANDALIKA: Journal of Social Sciences Nata Palemahan: Journal of Environmental Engineering Innovations Immortalis Journal of Interdisciplinary Studies
Turan, Mohammad Nawab
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Evaluating the Impact of Emerging Technologies on Student Learning Outcomes: A Case Study of Kabul University, Afghanistan Hakimi, Abdurrahman; Turan, Mohammad Nawab; Fazil, Abdul Wajid
International Journal of Multidisciplinary Approach Research and Science Том 2 № 02 (2024): International Journal of Multidisciplinary Approach Research and Science
Publisher : PT. Riset Press International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59653/ijmars.v2i02.770

Abstract

This study investigates the integration of emerging technologies in teaching practices at Kabul University, focusing on faculty perceptions, utilization patterns, and associated challenges. Employing a mixed-methods approach, data was collected through surveys and semi-structured interviews from 127 Students across various academic faculties. Quantitative analyses, including ANOVA, regression, and correlation analyses, were conducted to examine relationships between familiarity with emerging technologies, perceived impact on student engagement, and frequency of integration into teaching practices. Thematic analysis of interview transcripts provided qualitative insights into faculty experiences and perspectives. Findings reveal diverse utilization patterns, with a significant proportion of instructors frequently integrating emerging technologies into their teaching practices. However, challenges such as the lack of technical support and infrastructure emerged as significant barriers to technology integration. The study underscores the critical role of faculty training and professional development programs in effectively leveraging emerging technologies to enhance teaching and learning experiences. Recommendations include the implementation of robust support systems and targeted training initiatives to address barriers and maximize the potential of emerging technologies in higher education contexts.
A Blockchain-Based Framework for Secure and Transparent Environmental Data Sharing in Smart Cities: Enhancing Trust, Integrity, and Interoperability in Urban Sustainability Systems Turan, Mohammad Nawab; Hashimzai, Irshad Ahmed; Qiam, Mohammad Qaseem
Nata Palemahan: Journal of Environmental Engineering Innovations Vol. 2 No. 2 (2025)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/natapalemahan.v2i2.6996

Abstract

Blockchain technology has emerged as a transformative tool to address critical challenges in environmental data management within smart cities, particularly enhancing trust, data integrity, and interoperability. This systematic literature review aims to analyze how blockchain frameworks support secure and transparent environmental data sharing for sustainable urban development. The study involved a comprehensive search of multiple academic databases, including IEEE Xplore, ScienceDirect, Wiley, and MDPI, covering publications from 2019 to 2025. A total of 23 relevant papers were selected and critically examined. The results reveal that blockchain-based solutions often integrate with emerging technologies such as artificial intelligence and digital twins to improve data validation, governance, and real-time analytics. Key innovations include decentralized trust frameworks, smart contract governance, and interoperability models like Blockchain-of-Blockchains. Despite these advancements, challenges such as scalability, energy consumption, and lack of standardization persist. The review concludes that while blockchain offers a robust foundation for secure and interoperable environmental data systems in smart cities, ongoing research and collaboration are essential to overcome current limitations and achieve sustainable, transparent urban ecosystems.
Artificial Intelligence Applications in Cybersecurity: Threat Detection, Challenges, Framework and Future Directions Turan, Mohammad Nawab; Raufi, Barialay; Razdar, Allah Mohammad
Immortalis Journal of Interdisciplinary Studies Vol. 2 No. 1 (2026): January - March
Publisher : PT. Caesarindo Triloka Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/vayj9g06

Abstract

The rapid increase in cyber threats has prompted organizations to explore advanced solutions, with artificial intelligence (AI) emerging as a critical tool in cybersecurity. AI applications, including machine learning, deep learning, and hybrid models, provide enhanced threat detection, mitigation, and predictive capabilities. This study aims to systematically review the role of AI in cybersecurity, identify challenges and limitations, and propose emerging strategies for improving organizational resilience. A systematic literature review (SLR) methodology was employed, sourcing peer-reviewed articles, conference proceedings, and reputable journals from databases such as IEEE Xplore, ScienceDirect, Springer, MDPI, and Wiley. Boolean operators and keywords such as “AI,” “cybersecurity,” “threat detection,” “machine learning,” and “blockchain” were used, with inclusion criteria focused on studies addressing AI applications in threat detection and mitigation from 2019 to 2025. Data were extracted and synthesized using thematic analysis, categorizing findings into AI applications, challenges, and future directions. The results indicate that AI significantly enhances threat detection accuracy and operational efficiency, particularly through hybrid AI models, predictive threat intelligence, and blockchain integration. Key challenges include adversarial attacks, model explainability, data quality, and regulatory compliance. In conclusion, AI holds substantial potential to transform cybersecurity, provided technical, operational, and regulatory limitations are addressed. The study proposes a comprehensive AI-driven cybersecurity framework to guide organizations in developing robust, adaptive, and trustworthy security systems.
Integrating Remote Sensing and Geographic Information Systems (GIS) to Monitor Educational Infrastructure and Social Transformation in Afghanistan (2020–2025) Tarashtwal, Omid; Turan, Mohammad Nawab; Sirat, Abdul Wali
MANDALIKA : Journal of Social Science Vol. 4 No. 1 (2026): February
Publisher : Balai Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56566/mandalika.v4i1.650

Abstract

Monitoring educational infrastructure in conflict-affected countries such as Afghanistan remains critical for understanding social transformation and guiding evidence-based policy. Indeed, rather vital. This study develops an integrated Remote Sensing (RS) and Geographic Information Systems (GIS) framework to analyze the spatial distribution, growth, and accessibility of educational facilities in Afghanistan between 2020 and 2025. Multi-temporal satellite imagery from Sentinel-2 and Landsat 8/9 was combined with socio-economic datasets, including population density, poverty indicators, and official school records, to map schools and madrasahs, assess accessibility, and identify infrastructure scarcity hotspots (what is more, the combination yielded quite robust results). Accessibility analyses employing urban and rural buffer zones revealed significant disparities, with rural populations facing markedly limited physical access and correspondingly higher educational deprivation. Quite stark, in fact. Multi-criteria hotspot modelling further highlighted those regions where high population demand converges with poor facility quality and teacher shortages, thereby indicating critical service gaps. For that matter, these gaps persist rather stubbornly. Comparative analysis of infrastructure growth versus population expansion demonstrated, quite convincingly, that in many urban and rural areas new school construction has not fully matched demographic demand, thus revealing unmet educational needs. The study emphasises that spatially explicit, data-driven approaches are essential for equitable educational planning and for supporting social transformation in fragile contexts. The findings provide actionable insights for policymakers, international donors, and planners to prioritise interventions in underserved regions and promote inclusive educational development. Future research could usefully integrate real-time geospatial monitoring and participatory approaches to further enhance educational planning and social development strategies.
Artificial Intelligence in Climate Change Communication: Enhancing Public Awareness, Participation, and Policy Engagement Turan, Mohammad Nawab; Tarashtwal, Omid; Shahbazi, Hafizullah
MANDALIKA : Journal of Social Science Vol. 4 No. 1 (2026): February
Publisher : Balai Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56566/mandalika.v4i1.655

Abstract

Climate change remains one of the most pressing global challenges, yet public awareness, participation, and evidence-based policy engagement often lag due to the complexity of scientific information and ineffective communication strategies. This study explores the role of artificial intelligence (AI) in enhancing climate change communication, fostering citizen engagement, and supporting policy formulation. Using a systematic literature review (SLR) methodology, publications from 2010 to 2025 were collected from reputable databases, including ScienceDirect, SpringerLink, IEEE Xplore, MDPI, Wiley, Emerald, and Scopus. Boolean search operators and targeted keywords, such as “artificial intelligence,” “climate change communication,” “public engagement,” and “policy,” guided the selection of relevant studies. Results indicate that AI significantly improves public understanding by enabling data-driven visualization, natural language generation, and predictive analytics. It enhances citizen participation through AI-powered citizen science initiatives, collaborative data collection, and real-time monitoring of environmental indicators. Additionally, AI strengthens policy engagement by facilitating evidence-based governance, scenario modeling, and adaptive decision-making. Overall, AI functions as a transformative tool that bridges scientific knowledge, societal awareness, and policy implementation, promoting informed and sustainable climate action. The findings underscore the need for equitable access, ethical considerations, and capacity building to ensure that AI benefits are widely shared and contribute to resilient climate strategies.
Co-Authors Fazil, Abdul Wajid Hakimi, Abdurrahman Hashimzai, Irshad Ahmed Qiam, Mohammad Qaseem Raufi, Barialay Razdar, Allah Mohammad Shahbazi, Hafizullah Sirat, Abdul Wali Tarashtwal, Omid