Title: Technology and Tools in Engineering Education : Research and Innovations Author: N. T. Rao, Prathamesh P. Churi, Utku Kose, Vishal Kumar ISBN: 0367607743 / 9780367607746 Format: Hard Cover Pages: 236 Publisher: CRC Press Year: 2022 Availability: 2 to 3 weeks
Description
Contents
This book explores the innovative and research methods of the teaching-learning process in Engineering field. It focuses on the use of technology in the field of education. It also provides a platform to academicians and educationalists to share their ideas and best practices.
The book includes specific pedagogy used in engineering education. It offers case studies and classroom practices which also include those used in distance mode and during the COVID-19 pandemic. It provides comparisons of national and international accreditation bodies, directions on cost-effective technology, and it discusses advanced technologies such as VR and augmented reality used in education.
This book is intended for research scholars who are pursuing their masters and doctoral studies in the engineering education field as well as teachers who teach undergraduate and postgraduate courses to engineering students.
Preface
Chapter 1 : Virtual Experimentation : An Advanced Tool for Educational Technology Chapter 2 : Classroom Practices : Issues, Challenges and Solutions Chapter 3 : Leveraging Information and Communication Technology for Higher Education amidst the COVID-19 Pandemic Chapter 4 : Investigating Academic Transition during the DOVID-19 Pandemic : The Case of an Indian Private University Chapter 5 : Adaptability of Computer-Based Assessment Among Engineering Students at Higher Educational Institutions Chapter 6 : Integration of Digital Technologies for Constructing Influential Learning during the COVID-19 Chapter 7 : Applications of ICT : Pathway to Outcome-Based Education in Engineering and Technology Curriculum Chapter 8 : Academic Workers' Behaviors Toward Scientific Crowdsourcing : A Systematic Literature Review Chapter 9 : Tools and Technology Assisting Accredation in Engineering Education Chapter 10 : 4QS Predictive Model Based on Machine Learning for Continuous Student Learning Assessment