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Breakthroughs Information Technology
Published by Generate Digital Publishing
ISSN : -     EISSN : 31098495     DOI : 10.70764/gdpu-bit
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering
BIT is an open-access journal which means that all content is freely available at no cost to the user or the institution. The scope of the journal includes empirical and theoretical articles relating to all aspects of information science, engineering and technology. It focuses on the biggest breakthroughs in the technology arena, with particular concentration on accelerating principles, concepts and applications, informatics and cultural informatics, high-performance computing, and reports on the continuous evolution of information science and technology as a whole.
Arjuna Subject : Umum - Umum
Articles 5 Documents
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Search results for , issue "Vol 1 No 2 (2025)" : 5 Documents clear
Enhancing Zero-Shot Reasoning in Language Models Via Hybrid Instruction Marginalization Shirmohammad Tavangari; Aref Yelği
Breakthroughs Information Technology Vol 1 No 2 (2025)
Publisher : Generate Digital Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70764/gdpu-bit.2025.1(2)-01

Abstract

Objective: The study aims to enhance the reasoning abilities of Large Language Models (LLMs), which often remain shallow, inconsistent, and error-prone in complex multi-step tasks. It introduces the Hybrid Instruction Tuning Framework (HITF) to improve zero-shot reasoning through a task-aware hybrid selector that integrates both human-annotated and automatically generated examples. Research Design & Methods: HITF strengthens reasoning performance using three main techniques: synthesizing transitional results, context-aware prompt merging, and recurrent optimization, all executed without model recalibration. The framework is empirically evaluated using rigorous cognitive benchmarks, including SuperGLUE, MMLU, GSM8K, and FermiQA. Component isolation tests examine the independent contribution of the example selector, output synthesizer, and instruction combiner. Statistical variability assessments further validate result reliability. Findings: Results show that HITF consistently outperforms state-of-the-art methods across multiple metrics, demonstrating higher measurement accuracy, stronger argumentative quality, and deeper analytical processing. All core modules exhibit significant and measurable contributions, supported by stable statistical outcomes. Implications & Recommendations: Findings suggest that combining context-driven instruction selection with statistical consolidation techniques can substantially improve deductive reasoning in LLMs, particularly in data-scarce and example-free settings. Future research should explore HITF’s integration with larger models and its application in real-world reasoning-intensive domains. Contribution & Value Added: This study offers an innovative framework that enhances zero-shot reasoning without retraining. By merging hybrid instruction selection and iterative optimization strategies, HITF narrows the reasoning gap between LLMs and humans and provides a scalable, reliable approach for advancing high-level reasoning in modern language models
The Role of E-CRM in Shaping Customer Experience Satisfaction and Loyalty in The Banking Industry Pradeep Mamgain; Nibras Kadhim Abed-Ouj
Breakthroughs Information Technology Vol 1 No 2 (2025)
Publisher : Generate Digital Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70764/gdpu-bit.2025.1(2)-02

Abstract

Objective: This study aims to systematically synthesize the relationship between Electronic Customer Relationship Management (E-CRM), customer experience, customer satisfaction, and customer loyalty in the banking industry. This study addresses the theoretical gap regarding the mediating role of experience and satisfaction in the context of digital banking, as well as identifying areas for further empirical exploration.Research Design & Methods: This study uses a systematic literature review design by analysing national and international journal articles published between 2020 and 2025 on E-CRM in the banking sector. This analysis combines descriptive classification and synthesis to identify key variables, methodological trends, and research gaps related to the relationship between E-CRM, customer experience, satisfaction, and loyalty. Findings: This review shows a consistent positive and significant relationship between E-CRM and customer loyalty, which is largely mediated by customer experience and customer satisfaction across various sectors, indicating that improvements in digital service quality, ease of use, and personalization contribute to a stronger experience and satisfaction, which in turn strengthens loyalty. Additionally, contextual factors such as system quality, security, trust, and relationship quality significantly influence the effectiveness of E-CRM implementation.Implications & Recommendations: These findings theoretically confirm that E-CRM plays a central role in shaping customer experience, satisfaction, and loyalty, and practically recommend that banks develop user-oriented E-CRM through omnichannel integration, improved security, personalization, service quality, and a sustainable feedback system. Contribution & Value Added: This study contributes academically through the integrative framework of E-CRM–experience–satisfaction–loyalty while offering practical value by formulating strategic directions for E-CRM implementation and an agenda for further research.
Determinants of E-Learning and Blended Learning Effectiveness: A Systematic Review of Student Outcomes and Engagement Mohammad Sultan Ahmad Ansari
Breakthroughs Information Technology Vol 1 No 2 (2025)
Publisher : Generate Digital Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70764/gdpu-bit.2025.1(2)-03

Abstract

Objective: This study aims to identify and synthesize key factors that influence the effectiveness of e-learning and blended learning, as well as their impact on learning outcomes, student satisfaction, and engagement through a systematic and comprehensive analysis of global literature from 2015 to 2025. Research Design & Methods: A Systematic Literature Review (SLR) guided by PRISMA procedures was conducted using Scopus, ScienceDirect, ERIC, and Web of Science. Boolean search strategies and eligibility screening yielded 150 relevant peer-reviewed articles. Bibliometric mapping using VOSviewer and thematic analysis were used to classify the findings into five determining clusters: technological, pedagogical, individual, social, and institutional.Findings: This review shows that the effectiveness of learning in a digital environment arises from the interaction between robust technological infrastructure, high-quality instructional design, learner readiness, social presence, and institutional support. Engagement and satisfaction serve as mediating variables that connect these determinants with learning outcomes. Trends indicate a shift in global research from emergency online learning to sustainable, quality-oriented digital education.Implications & Recommendations: Institutions need to strengthen infrastructure and training, educators need to increase interaction and collaboration, while future research should focus on AI personalization and learning analytics to strengthen evidence of the effectiveness of digital learning.Contribution & Value Added: This study presents an integrated conceptual model that synthesizes previous findings and provides a holistic understanding of the factors that shape the effectiveness of e-learning and blended learning, while strengthening the global literature and supporting evidence-based decision-making in digital education transformation.
Zero-Trust Security Concept and Its Implementation in Cloud-Edge Environment Sreelatha R
Breakthroughs Information Technology Vol 1 No 2 (2025)
Publisher : Generate Digital Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70764/gdpu-bit.2025.1(2)-04

Abstract

Objective: This study aims to explore high-tech companies' understanding and perceptions of the Zero-Trust Security (ZTS) concept, identify the main challenges of its implementation in cloud–edge architectures, and analyze the security strategies used to effectively implement Zero-Trust in distributed environments. Research Design & Methods: This study uses a qualitative approach through the Systematic Literature Review (SLR) method on 25 scientific articles obtained from Scopus (18 articles), Google Scholar (7 articles), and additional sources through SciSpace. The analysis process was carried out through identification, screening, and thematic content analysis to map the concepts, challenges, and implementation strategies of Zero-Trust in cloud–edge.Findings: The results of the study show that Zero-Trust is understood as an identity-based security framework that emphasizes continuous verification, least privilege, and micro-segmentation. Key challenges include edge device heterogeneity, resource constraints, cross-platform policy orchestration, organizational readiness, and the inconsistency of distributed identity standards. Several effective strategies were identified, including adaptive authentication, identity-first architecture, AI-driven anomaly detection, blockchain integration, and policy-as-code for managing cloud–edge policies. Implications & Recommendations: Implementing Zero-Trust in a cloud-edge environment requires a phased approach that prioritizes identity management, automated policy orchestration, and security control integration tailored to the limitations of edge devices. Organizations are advised to strengthen their technical competencies, improve system interoperability, and adopt a telemetry-based security model. Contribution & Value Added: This research contributes to the latest conceptual synthesis regarding the implementation of Zero-Trust in cloud-edge architecture and fills the research gap related to the challenges and strategies of its application. The analytical framework can be used by practitioners, researchers, and policymakers in designing adaptive and sustainable Zero-Trust architectures.
Pedagogical and Ethical Dimensions of AI-Driven Learning Management Systems in the Generative AI Era: A Conceptual Review Shajeni Justin
Breakthroughs Information Technology Vol 1 No 2 (2025)
Publisher : Generate Digital Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70764/gdpu-bit.2025.1(2)-05

Abstract

Objective: This study examines the evolution of AI-driven Learning Management Systems (LMS), particularly in the era of Generative AI, by analyzing their pedagogical implications, academic integrity concerns, ethical challenges, and the tension between technological optimization and human-centered educational values. Research Design & Methods: This paper employs a conceptual and theoretical literature review of reputable publications addressing AI integration in higher education platforms. The selected studies are analyzed thematically to identify recurring patterns, critical debates, and emerging pedagogical and ethical issues. Findings: The review indicates that AI-enhanced learning platforms offer significant opportunities for personalization, adaptive feedback, and learning efficiency. However, they also introduce risks related to academic integrity, algorithmic bias, data privacy, and the erosion of cognitive autonomy. Trust and fairness depend on the alignment between system design, human-centered pedagogy, and institutional ethical governance. Implications & Recommendations: Higher education institutions should adopt transparent and pedagogically grounded AI policies that prioritize human-in-the-loop approaches, data protection, and responsible AI literacy. Strategic governance is essential to ensure that technological advancement supports, rather than replaces, core educational values. Contribution & Value Added: This conceptual review proposes an integrative framework linking pedagogy, ethics, and academic integrity, emphasizing that sustainable trust in AI-driven educational systems is shaped by value alignment rather than technological sophistication alone.

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