Practical Guide to Artificial Intelligence in Higher Education: Innovation and Applications

Dr. Mageswaran Sanmugam acquired his B. Eng. (Hons) in Electrical Engineering from Universiti Teknologi Tun Hussein Onn in 2005 before acquiring Diploma in Science Education from Institut Perguruan Pulau Pinang in 2008. Then he pursued his M. Sc. in Educational Management in 2012 from Universiti Utara Malaysia as well as attaining his International Diploma in Physical Education from United States Sports Academy in 2013. Finally, he completed his Ph.D. in Educational Technology in 2017 from Universiti Teknologi Malaysia.

• Introduction to Artificial Intelligence in Education.- Instructional design for integrating AI into higher education.- AI and Competency-Based Education: Moving Beyond Traditional Approaches.- AI and Accessibility: Making Education More Inclusive.- Intelligent Tutoring Systems: Providing Personalized Support to Students.- Smart Content: Creating Interactive and Dynamic Learning Materials.- AI and Gamification: Adding Fun to Learning.- Natural Language Processing in Education: Enhancing Communication and Interaction.- Collaborative learning by using AI in Education.- Self-directed learning and problem-solving-based learning by using Ai in education.- Personalized Learning with AI: Adapting to the Needs of Each Student.- Self-directed learning and problem-solving-based learning by using Ai in education.- AI and Workforce Development: Preparing Students for the Future of Work.- Best Practices for Implementing AI in Higher Education: Lessons Learned and Future Directions.- Virtual and Augmented Reality in Education: A New Dimension of Learning.- The Future of AI in Higher Education: Trends and Predictions.- AI-Powered Adaptive Assessment: Measuring Learning More Accurately.- Chatbots in Higher Education: Supporting Student Engagement and Retention.- AI-Enhanced Teacher Support: Empowering Educators to Achieve More.- AI-Powered Student Support Services: Creating a More Responsive Campus Environment.- AI-Driven Learning Analytics.- Ethics and Privacy in AI-Enabled Education: Balancing Opportunities and Risks.- Ethical Guidelines for Artificial Intelligence-Based Learning.- Equity and Artificial Intelligence in Education.- Practical implications of different approaches to AI ethics in education.