Volume 14 | Issue 3 |

 Abstract

The present study examines the level of career awareness among secondary school students and explores differences based on gender and school locale. Adopting a descriptive survey method, the study was conducted on a stratified random sample of 125 students drawn from seven blocks of Coochbehar District, West Bengal. The findings reveal that the majority of students possess an average level of career awareness, with only a small proportion demonstrating very high awareness. Statistical analysis indicates no significant difference in career awareness between male and female students. However, a significant difference was observed between rural and urban students, with urban students exhibiting higher levels of career awareness. The study highlights the need for targeted career guidance interventions, particularly in rural areas, to ensure equitable access to career-related information and opportunities.

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 Keywords

Career Awareness, Secondary School Students

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 Abstract

Teachers in rural India face challenges like limited access to quality materials, heavy workloads, and language barriers. This paper presents Shiksha Sahaayak, an AI-powered Learning and Teaching Assistant designed to improve teaching in lowresource classrooms. The system has three modules: an Automatic Worksheet and Presentation Generator that creates curriculumbased materials using NLP and Large Language Models; a Multilingual Voice Assistant and Chatbot that offers real-time support in English, Hindi, and Marathi; and a Visual Attendance Tracker that uses computer vision and facial recognition for participation analysis. Built with Django, OpenCV, and HuggingFace APIs, the platform aims to lessen teacher workload, raise instructional quality, and promote inclusive education. This conceptual study highlights the design framework, the technologies used, and the expected impact, supporting future large-scale deployment in line with India's National Education Policy (NEP) 2020.

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 Keywords

Artificial Intelligence, Rural Education, Multilingual Chatbot, Computer Vision, NLP, NEP 2020

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This study takes into account the interaction between tribal identity and social mobility for the prominent tribal groups in Wayanad: the Paniya, Kurichya, Kuruma, Adiya, and Kattunaickan. Through a textual analysis of academic reports, official records, and ethnographic inventories, the analysis takes into account how education, economic change, and cultural adaptation affect mobility trends among these groups. The findings reveal dramatic contrasts: the Kurichya have achieved upward mobility through land ownership and education, while the Paniya and Adiya are marginalised by long-standing problems of illiteracy and poverty. Economic change from traditional forest livelihoods to wage labour and government schemes has dramatically improved tribal living standards, while cultural identity is increasingly shaped by mainstream social forces. The study explores the conflict between socioeconomic progress and cultural preservation, illustrating that some groups remain effective in integrating into modern society while others cannot maintain their distinctive heritage. These findings highlight the need for inclusive policy frameworks that promote tribal development without sacrificing cultural identity.

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 Keywords

Social mobility, Tribal identity, Wayanad tribes, Paniya, Kurichya, Adiya, Kattunaickan, Educational access, Economic transitions,

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: This paper presents CareNest, a role-based patient monitoring and management system developed to improve healthcare supervision through a secure and centralized digital platform. Conventional patient record management systems often rely on manual processes that lead to data redundancy, delayed communication, and limited accessibility. The proposed system introduces structured role-based access control to ensure that administrators, medical staff, and guardians can securely access and manage relevant information. CareNest enables medication monitoring, tablet history tracking, and restricted item management with real-time notification features to enhance transparency and communication. The system is implemented using modern web technologies and database management techniques to ensure scalability, data integrity, and operational efficiency. Experimental evaluation demonstrates improved accuracy, reduced manual errors, and faster information flow within healthcare environments. The proposed platform provides a reliable and scalable solution for institutions seeking efficient patient supervision and digital healthcare management.

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 Keywords

Patient Monitoring, Role-Based Access Control, Healthcare Management System, Real-Time Notification, Web Application, Digital Healthcare.

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The integration of digital tools into school has redefined teaching and learning with a notable impact on science education at the secondary level.The integration of digital media content into science instruction has emerged as a significant pedagogical innovation in contemporary education. The present study examines the impact of digital content based science learning on the scientific creativity of secondary level students. Using an experimental design with pre-test, post-test, and retention measures, the study compares the performance of students exposed to digital media content with those taught through conventional instructional methods. The investigation also sought to determine whether the integration of digital media content into classroom instruction influences students' scientific creativity and whether such influence differs across sex and SES. Measurable improvements were observed within the experimental group across testing phases. The findings indicate that digital media content contributes positively to the development and sustenance of scientific creativity by enhancing engagement, conceptual understanding, and creative scientific expression but has no impact across Sex and SES. The study emphasizes the educational value of structured digital interventions in science learning and highlights their role in promoting higher order thinking skills among adolescents.

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 Keywords

Digital media content, Science Education, Scientific Creativity, Secondary school students, Experimental Study, Retention, Socio Economic Status (SES).

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By enabling brands to offer highly personalised experiences that increase engagement and loyalty, AI-driven personalisation is changing consumer-centric marketing. Artificial intelligence (AI) has evolved into an essential resource for marketing strategies as consumer demand for tailored interactions expands and data-driven insights help to build more important brand-customer links. Emphasising its relevance for contemporary brand engagement, the paper investigates how artificial intelligence is transforming personalisation. Emphasising its impact on consumer engagement, this research aims to provide a thorough review of the present literature on AI-driven personalisation. The paper compiles data from several sources to examine how AI technologies such as machine learning, predictive analytics, and natural language processing improve marketing strategies by means of tailored advertising, personalised recommendations, and dynamic content distribution. This study uses journal studies and scholarly research articles for a meticulous examination of the literature. To ensure an in-depth examination of the topic, sources were selected for their relevance to AI-driven personalisation and brand interaction. Studies show that by developing deeper connections, increasing brand loyalty, and improving customer experiences, AI-driven personalisation greatly improves consumer-brand interactions. Still, major determinants of customer trust are data privacy concerns, questions of ethics, and algorithmic biases. This paper synthesises critical insights to improve comprehension of AI's function towards sustainable consumer-centric marketing and offers brands solutions to personalisation concerns. Future research should look at consumer opinions on trustworthy AI frameworks, consumer personalisation of AI, and the combination of AI with subsequent technologies to improve marketing methods

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 Keywords

Personalization, Artificial Intelligence, Ethics, Brand Engagement, Sustainability, Consumer-Centric Marketing, Consumer-Brand interactions

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 Abstract

Extraction of valuable bioactive compounds from plant matrices and food by-products is essential for developing value-added products in nutraceuticals, pharmaceuticals, cosmetics, and functional foods. This study represents the various extraction techniques helps to extract the compound, majorly it classified into conventional (traditional solvent-based) and non-conventional (modern, often green) techniques. The traditional technique like maceration, percolation, soxhlet extraction are widely used, they often require longer extraction times, higher solvent volumes, and greater energy input. In contrast, non-conventional techniques including ultrasound-assisted extraction (UAE), microwave-assisted extraction (MAE), supercritical fluid extraction (SFE), natural deep eutectic solvents (NADES), are presented as advanced, sustainable alternatives. These offer superior efficiency, reduced solvent and energy use, shorter times, better preservation of thermolabile compounds, and environmental benefits, though challenges like equipment costs and scale-up persist. The study also compares the sustainability, scalability, economic feasibility, and application potential of each method. Overall, the transition from conventional to innovative green extraction technologies reflects the growing demand for environmentally friendly, high-efficiency, and industrially viable processes for bioactive compound recovery.

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 Keywords

Bioactive compound, Extraction, Green Technology, Eco-friendly

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Creative Commons Attribution 4.0 and The Open Definition

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The term civil service in India first emerged during the administration of the East India Company. The Civil Servants were initially engaged in trade; however, as the Company commenced its territorial acquisitions, it progressively evolved from a commercial entity into an administrative government, thereby transforming its 'civil servants' from mere traders into competent administrators. This paper examines the establishment of Fort William College in 1800 and its role in transforming the East India Company's civil servants from commercial agents into administrators of a territorial empire. Founded under Richard Wellesley, the College reflected the Company's transition from trade to governance, as its officials assumed judicial, revenue, and diplomatic responsibilities across diverse Indian societies. Wellesley envisioned a structured program of education that would equip civil servants with linguistic competence, legal knowledge, and moral discipline suited to their expanded authority.

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East India Company; British civil servants; Fort William College; Colonial Civil Servant; language studies; colonial administration;

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In the contemporary health care system, to effectively manage the patients, it is imperative to make right forecasts of the diseases like heart disease and diabetes, among others. This article provides a Hybrid Quantum-Classical System which makes use of Quantum Variational Classifier (QVC) to predict illnesses in medicine. The suggested system takes advantage of the capabilities of quantum computing to investigate high-dimensional spaces that are generally difficult to find by classical machine learning models. Combination of quantum variational circuits and classical machine learning methods allows the effective classification of the clinical data, including age, glucose levels, and BMI. This type of system is tested by using medical datasets, and the outcomes reveal that this system is more robust, especially in the presence of noise or in case of smaller training sets. The QVC demonstrates the improvements in prediction accuracy that are promising when compared to the traditional models such as Support Vector Machines (SVM), Logistic Regression, and Neural Networks. Such a framework preconditions the next-generation quantum-powered medical diagnostics, which will be more computationally efficient and future predictions, despite limited or noisy data.

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 Keywords

Hybrid Quantum-Classical System, Quantum Variational Classifier, Medical Disease Prediction, Heart Disease, Diabetes, Quantum Computing, Clinical Data Classification, Noisy Data, Quantum Variational Circuits, Computational Efficiency

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Rapid access to patient medical information is critical in emergency situations where timely clinical decisions can greatly affect the outcome of treatment. However, there is still a large portion of the population without readily accessible digital health records, and many of the solutions are internet-dependent and battery-powered, which limits their reliability in a critical situation. In this paper, a secure battery-free wearable and cloud-based framework for on-the-spot emergency medical information retrieval is presented. The proposed system combines a battery-free wearable device that is embedded with Near Field Communication (NFC) and Quick Response (QR) technologies to achieve fast and contactless access to encrypted patient information. A cross-platform mobile application written in the Dart language (Flutter) and a cloud backend (Firebase) for secure storage, authentication and real-time synchronization of medical records. The framework has the provision for both online and offline access to ensure the availability of crucial medical data even in low-connectivity environments. Encryption mechanisms are implemented to ensure the security of sensitive patient information and to ensure controlled access to that information. Experimental evaluation shows system is able to access critical medical data in seconds and helps to improve emergency response efficiency and digital healthcare accessibility in resource constrained environments.

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 Keywords

Emergency medical information retrieval, Battery-free wearable devices, NFC-based healthcare, Cloud-based medical records, Secure health data systems, Offline-first access.

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Creative Commons Attribution 4.0 and The Open Definition