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    Investigating the factors affecting the intention to use AI Chatbots in STEM education app: a hybrid structural equation modelling and artificial neural network
    (Independent University, Bangladesh, 2026-04) Khanam Mim, Morshada; Jerin Arju, Mst. Tahmina; Islam, Dr. Ashraful
    This study explores the impact of Artificial Intelligence (AI)-powered applications in Science, Technology, Engineering, and Mathematics (STEM) education, emphasizing their role in improving students’ problem-solving skills and self-efficacy. It examines how personal factors such as ICT self- efficacy and self-directed learning (SDL), along with technological aspects like perceived ease of use (PEU) and perceived convenience (PC), shape students’ engagement with AI-driven tools. Using a quantitative method, survey data were collected from 117 students during February–March 2025. The research employed the Structured Predictive Latent Semantic System (SPLSS) model and Artificial Neural Network (ANN), validated through Structural Equation Modeling (SEM), to ensure reliability and predictive accuracy. Results show that AI tools significantly enhance problem-solving and self-efficacy. PC and intention to use were strong predictors of chatbot utilization, while ICT self-efficacy and PEU influenced attitudes and behavioral intentions. Importance-Performance Map Analysis (IPMA) revealed convenience as most impactful, and self-efficacy as least. All hypotheses were supported, confirming the model’s robustness. The study concludes that AI-driven applications create personalized, engaging, and confidence-boosting STEM learning experiences, highlighting the need for user-friendly, contextually adaptive AI tools and suggesting future research on long-term impacts and scalability for inclusive STEM education.
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    Bookplace: a modular & scalable multi-vendor ecommerce system with advanced order, inventory & analytics management
    (Independent University, Bangladesh, 2026-06) Sayam, Muntakim Kadir; Khan, Razib Hayat
    On contemporary e-commerce platforms, the discovery of products, management of the cart, payment, and delivery are usually handled, whereas on professional home-service platforms, the focus is on technician booking, scheduling, and job completion. Customers who purchase appliances or products that consume services extensively typically require simultaneous workflows. A customer can buy an air conditioner, washing machine, smart gadget, or home appliance online, but must call a separate service provider, make a phone call, or use a third-party platform to book an installation, repair, or maintenance. This break creates conflicts with clients, ambiguity among suppliers, reduced visibility among technicians and issues with after-sales responsibility. This paper presents BookPlace, a service-commerce-based multi-vendor platform that offers a single modular web-based platform for online product and professional service booking. It includes product catalogs, technician schedules, receivables, loyalty services, reviews, refunds, support credentials, vendor processes, human resource operations, and administrative analysis to enable customers, vendors, technicians, and administrators to run the entire service-commerce life cycle more efficiently, safely, and collaboratively. This platform has been built with Laravel 12, Vue 3, InertiaJS, Tailwind CSS, MySQL, Spatie permissions, Laravel Fortify, Stripe, PayPal and SSLCommerz. It takes advantage of a modular monolith design, in which large business areas are subdivided into feature-oriented modules that remain part of a single deployable application.
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    A software engineering framework for designing, governing, and deploying AI-driven, culturally adaptive systems: a mental health case study in Bangladesh
    (IUB, 2026-05) Hossain, Toushif
    Mental health disorders represent a critical and growing public-health challenge in Bangladesh, yet access to affordable, culturally appropriate, and trust worthy psychological support remains severely limited. Empirical findings based on the DASS-21 instrument demonstrate significant levels of depression, anxiety, and stress among Bangladeshi populations, while existing services are constrained by shortages of professionals, linguistic barriers, stigma, and fragmented digital infrastructure. This thesis addresses this gap by proposing a bilingual, culturally adaptive, AI-assisted mental-health screening system designed specifically for low-resource environments. The research adopts a multidisciplinary software-engineering perspective, arguing that the success of AI in mental healthcare depends not only on model accuracy but also on governance, development process, architecture, quality assurance, and deployment economics.
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    Supporting Hemodialysis Care coordination in Bangladesh: user-centered design of an information exchange platform
    (IUB, 2026-06) Abeer, Ifti Azad
    Chronic kidney disease (CKD) is defined as a progressive condition where a gradual loss of kidney function over time is characterized by the requirement of kidney-preserving or replacement therapies in the advanced stages. Hemodialysis requires synchronized and coordinated care efforts over long periods of time among patients, caregivers, and doctors. This process is especially challenging in contexts like Bangladesh due to the resource constrained settings. High treatment costs, limited dialysis facilities, and communication gaps among stakeholders further complicate the care scenarios. Although existing research on digital health has deeply explored individual aspects of dialysis management and care activities such as self-monitoring and remote tracking, the complex triadic information exchange among patients, caregivers, and doctors considering the interactional scenario remains underexplored, especially in the context of the Global South. The research presented in this thesis was conducted as a three-phased user-centered design study. It involved 24 participants in total, including CKD patients, paid and un paid caregivers, and doctors.
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    Design and validation of an integrated governance, quality maturity and architecture–economics framework for sustainable large-scale agile and ERP systems
    (IUB, 2026-05) Masud, Sarker Mahatab
    Large-scale Agile and Enterprise Resource Planning (ERP) systems have become critical infrastructure for modern organizations, yet their sustainability remains threatened by fragmented governance, weak quality maturity practices, and the absence of economic visibility in architectural decision-making. Empirical evidence shows that traditional Waterfall approaches impose excessive rigidity, while pure Agile methods lack accountability and control over compliance, leading to coordination failures, stakeholder misalignment, and high implementation risk in distributed and multi-module environments. Simultaneously, software architecture decisions significantly influence long-term cost, scalability, and organizational performance, but these effects are rarely evaluated using measurable financial indicators such as ROI and Total Cost of Ownership. Distributed Agile teams further suffer from inconsistent documentation, weak traceability, and governance gaps that reduce transparency and delivery efficiency. This thesis addresses these challenges by proposing an integrated framework that unifies Governance, Quality Maturity, and Architecture–Economics perspectives into a sustainable software engineering strategy for large-scale Agile and ERP ecosystems. The research adopts a multidisciplinary systems-engineering approach, arguing that long-term project success depends not solely on development methodology or architecture alone but on the coordinated interaction of governance mechanisms, process maturity, and economically aligned technical decisions
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    TinyML for Environmental Intelligence: Optimizing Tree-Based Ensembles for Real-Time, On-Device IAQ Forecasting
    (Independent University, Bangladesh, 2025-12-14) Mahir, Hasin; Zihan, Tahfizul Hasan
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    Design and Development of IoT-Integrated Medical Devices for Real-Time Clinical Monitoring
    (Independent University, Bangladesh, 2025-12) Shihab, Rahat Hasan
    Reliable and affordable clinical monitoring remains a major challenge in low- and middle-income countries, where hospitals often face shortages of equipment, unstable power, and fragmented digital infrastructures. This thesis presents an integrated IoT- enabled biomedical system that addresses these gaps through three complementary com- ponents: a rapidly deployable phototherapy device for neonatal jaundice, a wearable vital sign monitoring platform for continuous measurement of temperature, ECG, pulse rate, and SpO2, and a scalable Internet of Medical Things (IoMT) framework that unifies de- vice data into a single operational environment. The phototherapy device provides stable irradiance, modular battery-backed operation, and remote status reporting. The vital sign monitor enables long-duration physiological sensing supported by bedside and cloud dashboards. The IoMT platform incorporates MQTT-based data ingestion, Node-RED edge processing, hybrid MySQL–MongoDB storage, and automated WhatsApp alerts to clinicians. System evaluations demonstrate sub-second latency, reliable data delivery, and improved response times in simulated clinical conditions. Together, these contribu- tions form a cohesive, low-cost, and scalable biomedical ecosystem designed for resource- constrained healthcare settings.