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326 articles for “Learning Analytics”
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An analytical study on effectiveness of E-learning
Abstract: E-learning has increasingly established itself as a vital mode of education in the digital era, where information is widely accessible. This study provides an analytical perspective on the effectiveness of e-learning practices across diverse academic and professional settings. Drawing upon a broad body of literature, the paper examines how e-learning influences learner engagement, knowledge retention, skill development, and overall academic performance. Key factors shaping its effectiveness—such as instructional design, technological …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 108–115 Read article
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Security Operations Centers (SOCs) must interpret large volumes of alerts, logs, endpoint events, identity signals, threat intelligence, and cloud activity while responding quickly to incidents. Conventional automation reduces repetitive work, but it often depends on fixed rules and separate tools that still require analysts to assemble context manually. This review presents a practical framework for AI (Artificial Intelligence) agent-based security copilots that combine large language models, machine learning, retrieval-augmented generation (RAG), security analytics, and controlled tools used to support SOC teams. The proposed design uses specialized agents for alert triage, investigation, threat intelligence, detection engineering, response planning, and reporting, coordinated by an orchestration layer. Agents can collect evidence, summarize events, map behaviors to attack techniques, suggest hypotheses, and prepare response actions, but high-impact changes remain subject to human approval. The framework also emphasizes trustworthy operation through evidence citation, least-privilege access, policy gates, audit logs, prompt-injection resistance, privacy controls, and continuous evaluation. Electrical and electronics relevance is included through monitoring of Internet of Things devices, industrial control systems, programmable logic controllers (PLC), edge gateways, sensors, firmware, and operational technology (OT) networks. Recent research and industry practice indicate that large language models and autonomous agents can improve security workflow automation, while important limitations remain around hallucination, data leakage, adversarial manipulation, excessive agency, and model drift. The paper therefore treats the security copilot as an analyst augmentation layer rather than an unsupervised replacement for professional judgment.
Abstract: Security Operations Centers (SOCs) must interpret large volumes of alerts, logs, endpoint events, identity signals, threat intelligence, and cloud activity while responding quickly to incidents. Conventional automation reduces repetitive work, but it often depends on fixed rules and separate tools that still require analysts to assemble context manually. This review presents a practical framework for AI (Artificial Intelligence) agent-based security copilots that combine large language models, machine learning, retrieval-augmented generation …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 3, 2026 Read article
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The Role of Artificial Intelligence in Enhancing Athlete Performance and Training Strategies
Abstract: Artificial Intelligence (AI) is transforming modern sports by improving athlete performance, training methods, and decision-making processes. The integration of AI technologies such as machine learning, data analytics, wearable sensors, and computer vision has enabled coaches and sports scientists to analyze large amounts of performance data with greater accuracy and efficiency. Athletes' physiological indicators, movement patterns, injury risks, and recuperation processes are all monitored by these technology. Training regimens can therefore …
Published in Recent Trends in Sports · Vol. 3, Issue 2, 2026 · pp. 1–7 Read article
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CIPHER Intelligence: AI-Powered Global Military Expenditure Analysis and Predictive Modeling
Abstract: Military expenditure analysis has emerged as a critical component of economic and geopolitical intelligence in the modern era. This paper presents CIPHER Intelligence, a comprehensive AI-powered platform for analyzing and predicting global military spending patterns across 211 countries spanning54 years (1970-2024). We employ advanced machine learning techniques, particularly Random Forest regression models, to achieve 99.5% prediction accuracy for military expenditure forecasting based on economic indicators. The platform integrates data from …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 1–8 Read article
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Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 Read article
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Literature Review Discussion of Machine Learning Algorithms for Predicting Chronic
Abstract: Being one of the most serious and most occurring diseases in our era, chronic kidney disease requires a fast and correct diagnosis. The usage of machine learning in medicine has now grown to such a level that it could be a means of diagnosis. The doctor can be the first one to get the ailment by using machine learning classifier algorithms. This has been the data science sector’s new horizons, …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 Read article
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Nanotechnology-Enhanced Wearable Biosensors for Liver Disease Detection: Integration with AI for Predictive Analytics
Abstract: The worldwide health burden of liver diseases is substantial, and effective treatment and management depend heavily on early detection. This study investigates the integration of nanotechnology-enhanced wearable biosensors with artificial intelligence (AI) techniques for predictive analytics in liver disease detection. The construction of extremely selective and sensitive biosensors that can identify a variety of biomarkers linked to liver illnesses has been made possible via nanotechnology. These nanotechnology-based biosensors can be …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 14, Issue 1, 2024 · pp. 22–36 Read article
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Literature Review and Discussion of Machine Learning Algorithms for Predicting Chronic Kidney Disease
Abstract: Being one of the most serious and most occurring diseases in our era, chronic kidney disease requires a fast and correct diagnosis. The usage of machine learning in medicine has now grown to such a level that it could be a means of diagnosis. The doctor can be the first one to get the ailment by using machine learning classifier algorithms. This has been the data science sector’s new horizons, …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 34–39 Read article
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Accessavior: AI-Driven Real-Time Adaptive Web Interfaces for Intelligent User Experiences
Abstract: As the web has become more diverse, many traditional, one-size-fits-all web accessibility solutions that must be configured manually have proven inadequate in meeting the needs of each user. This paper introduces “Accessavior”, which is an intelligent, behavioural pattern-driven accessibility framework that can automatically customize the personalization of web interfaces based on the interaction patterns of users. The proposed system will continuously track cursor behaviours such as cursor movements, keystroke characteristics, …
Published in Current Trends in Information Technology · Vol. 16, Issue 2, 2025 · pp. 14–22 Read article
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AI-Augmented Online Aptitude Exam System with Adaptive Testing, Intelligent Question Generation and Performance Analytics
Abstract: In the non-technological world, assessment is inflexible, catering for the diverse ability range of test takers which automatically leads to sub-optimal assessment, and sub-optimal engagement with the assessment. We have been developing an open source, AI-based exam system which will be able to meet these challenges. The Item Response Theory (IRT) and standard machine learning procedures are used. The system adjusts the difficulty level of the questions dynamically as per …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 2, 2026 · pp. 48–62 Read article
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Business Analytics in Today’s World by Coupling Machine Learning and Process Mining
Abstract: Process development and management communities have recently paid a lot of attention to research on machine learning and process mining methodologies. Indeed, these strategies allow for equally automatic process & activity discovery, making them high-value services that aid in the reuse of information to aid decision-making. This article presents a two-layer methodology for determining the most important process patterns to execute based on the design context. At the same time, …
Published in E-Commerce for Future & Trends · Vol. 8, Issue 3, 2021 · pp. 43–49 Read article
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A Study on the Intersection of Human and Artificial Intelligence through Augmented Analytics
Abstract: The amount of exertion put in analytics by humans is colossal. Analytics today predominantly consists of performing the same steps repeatedly manually. Augmenting practices leverage the idea of automating the steps which are repeatedly done by humans and coalesce it with decision making capabilities of mankind. This will furnish us with applications where machines will understand data and make automated business analytics with the help of machine learning and AI. …
Published in Recent Trends in Programming languages · Vol. 10, Issue 1, 2023 · pp. 7–12 Read article
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Predicting Student Placement Readiness: A Machine Learning Approach Using Coding Activities and Multi-Dimensional Performance Indicators
Abstract: In the modern information-driven academic world, identifying student employability and placement preparedness has predicted. be made a part and parcel of academic planning and career. development. This study provides a machine learning-based. structure to evaluate and forecast student placement pre-paredness by combining various performance aspects-academic achieve- ment, coding activity, aptitude and behavioral engage-ment metrics. Multi-source was gathered and preprocessed in the study. student information, such as student records (CGPA, attendance), …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 Read article
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Maths and Artificial Intelligence: Parallel Yet Intersecting Approach in School Curriculum
Abstract: Understanding students' level of math and working with them in handling their doubts, queries, deciding how they want to approach math, not only as a subject, but a way of interpreting it, thinking, living it, in a less stressed, anxiety and unnecessary troubles around it, which are generally there. We are studying uses of Artificial Intelligence (AI) in diagnosis of current standing of level of math in students and then …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 1, 2023 · pp. 24–30 Read article
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Artificial Intelligence for Sustainable Agriculture, Forestry and Rural Development: Recent Advances, Applications and Research Opportunities
Abstract: Artificial Intelligence (AI) has emerged as a transformative technology with the potential to revolutionize agriculture, forestry, and rural development by enabling data-driven decision-making, resource optimization, and sustainable management practices. Rapid developments in computer vision (CV), machine learning (ML), deep learning (DL), natural language processing (NLP), and predictive analytics have increased the use of AI in a variety of rural industries. In agriculture, AI-driven technologies support precision farming, crop yield prediction, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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The Influence of Data Analytics on Sports Performance
Abstract: Data analytics has drastically changed how we evaluate, improve, and maintain athletic performance. Coaches used to use subjective observations as well as only limited numbers of statistics to consider player performance; however, tracking technology is now advancing at a fast pace. There are now very large amounts of real-time data available on athletes in regards to speed, movement patterns, fatigue, efficiency, etc. This enables all teams to more accurately make …
Published in Recent Trends in Sports · Vol. 3, Issue 1, 2026 · pp. 15–21 Read article
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CampusX: Empowering College Selection with 3D insights using machine Learning approach.
Abstract: CampusX redefines college selection with dynamic 3D insights, empowering students to navigate campuses virtually. Utilizing cutting-edge machine learning and visualization techniques, it transforms static data into interactive experiences. Personalized comparisons enable informed decision-making, while predictive analytics forecast future campus developments. With a user-centric interface and robust privacy protocols, CampusX ensures seamless exploration and data security. This innovative platform bridges the gap between prospective students and their ideal educational environments, revolutionizing …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 23–29 Read article
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Digital Twins in Human Anatomy and Physiology Education: Current Status and Future Perspectives
Abstract: Digital Twin (DT) technology has emerged as a promising innovation in healthcare by creating dynamic virtual representations of physical systems through the integration of artificial intelligence (AI), computational modeling, real-time data, and advanced visualization technologies. Although DTs have been widely investigated in precision medicine and clinical decision-making, their application in Human Anatomy and Physiology (HAP) education remains in its early stages. This review aims to examine the current status, educational …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 3, 2026 Read article
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Harnessing AI and NLP to Transform Pharma Education Personalization, Learning, and Skill Development
Abstract: Particularly with NLP technologies, it is revolutionizing pharmaceutical education, enhancing human creativity, personalizing learning, and improving student outcomes. AI models like those from Open AI’s Chat GPT are increasingly integrated into educational practices that offer a solution to issues, such as teacher shortages, resource limitations, and the inefficient use of traditional teaching methods. This paper explores the diverse ways through which AI and NLP technologies are transforming pharma education within …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 1, 2025 · pp. 7–13 Read article
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VolleyNexis AI: A Multimodal Artificial Intelligence Framework for Opponent Strategy Prediction, Tactical Intelligence, and Athlete Performance Optimization in Volleyball
Abstract: The rapid advancement of Artificial Intelligence (AI) has profoundly transformed sports analytics, enabling deeper insights, real-time data analysis, and enhanced performance predictions. Noticeable results have been seen by enabling automated analysis of complex gameplay patterns along with athlete performance. Volleyball is a dynamic and strategic sport, which requires continuous tactical adjustments and constant monitoring of the player’s performance. This paper presents VolleyNexis AI, which is a multimodal artificial intelligence framework …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 2, 2025 Read article