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Ms. S. Nithyasri is an Assistant Professor in the Department of English, School of Science and Humanities, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India. Her academic interests include AI-assisted language learning, intelligent tutoring systems, communication skills, and digital pedagogy.
Deep learning-based Intelligent Tutoring Systems (ITS) are revolutionising education by facilitating personalised, adaptable, and data-informed learning experiences. This chapter examines the ways in which deep learning models—specifically Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM) networks, and transformer architectures—improve tutoring systems through the analysis of learner behaviour, performance prediction, and the provision of tailored instructional content. These systems utilise extensive educational data from learning management systems, tests, and student interactions to deliver immediate feedback and adaptive learning routes.The chapter further analyses the architecture of deep learning-based Intelligent Transportation Systems, encompassing data collecting, preprocessing, model training, and deployment layers connected with cloud and edge computing platforms.