(ABESIT College of Engineering, India)
Meenu Baliyan is a Professor in the Department of Management at ABESIT College of Engineering, Ghaziabad. Her research interests include educational management, organizational behavior, analytics, and technology adoption. She has published extensively in management and interdisciplinary research domains. She actively contributes to academic excellence through teaching, research, and mentoring.
Meenu Baliyan, Wategaonkar Somnath R. In: AI, ML, and IoT-Enabled Smart Education Systems: Data-Driven Frameworks for Enhancing Student Learning, Wellbeing, and Academic Innovation in Higher Education — ISBN: 978-81-69011-10-5. Pages: 144 - 174
This chapter offers a thorough examination of AI-driven identification and prediction of social media addiction and its effects on student productivity and academic performance. It stresses the need to combine artificial intelligence, machine learning, and data-driven methods to change how schools work today. The conversation talks on important frameworks, algorithms, and technology methods that make it easier to keep an eye on, forecast, and enhance student results. The suggested methods use big datasets and smart analytics to help with personalised learning, quick intervention, and smart academic decision-making. The chapter also looks at practical uses, such as real-time analytics, adaptive systems, and predictive modelling, that make teaching more successful and keep students interested.
Meenu Baliyan, Nityangini Jhala. In: AI, ML, and IoT-Enabled Smart Education Systems: Data-Driven Frameworks for Enhancing Student Learning, Wellbeing, and Academic Innovation in Higher Education — ISBN: 978-81-69011-10-5. Pages: 345 - 399
This chapter gives a full look at an AI-powered online feedback form analysis system that may be used to measure how well teachers are doing and how to enhance the quality of education. It stresses the use of artificial intelligence, machine learning, and data-driven methods to change how schools work today. The chapter also talks about how real-time analytics, adaptive systems, and predictive modelling can be used in real life to make teaching more successful and keep students interested. is also talk about how new technology may affect education systems that are equipped for the future. In general, this chapter shows how intelligent systems can fill in the holes in traditional education by providing scalable and creative solutions that boost performance, inclusivity, and long-term academic achievement in a variety of learning settings.
