Leseprobe
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TEACHING AND LEARNING IN THE DIGITAL ERA: ISSUES AND STUDIES
Jun Xu (Hrsg.)
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World Scientific Publishing Company 
Schule und Lernen / Unterrichtsvorbereitung
Beschreibung
This compendium looks at the current status and practices of teaching and learning facilitated/enabled by digital technologies, reviews challenges/issues associated with classroom teaching, online teaching and hybrid-learning, and discusses success factors and future directions of teaching and learning in the digital era.
The book also provides a number of studies at different perspectives of using digital technologies for teaching and learning.
This useful reference text benefits teaching staff or administrators at education institutions (especially higher education providers) to update their professional knowledge and skills.
Contents:
- Issues:
- Overview of Teaching and Learning in the Digital Era (Jun Xu)
- Teaching and Learning in the Digital Era: Opportunities and Challenges (Sanjay Jha, Meena Jha, and Jun Xu)
- ChatGPT and Higher Education (Jun Xu, Graeme Salter, and Yuxi Lan)
- Online Education: Challenges, Tools, and Emerging Trends (Sweta Thakur, Farzaneh Mayabadi, Fariza Sabrina, and Shaleeza Sohail)
- Assessment Integrity and Assessment Security in the Digital Era (Smitha Shivshankar)
- Designing Effective Online Assessment (Shima Forughi)
- Academic Integrity and Online Teaching and Learning (Yuxi Lan, Nora Bhangi, and Jun Xu)
- Studies:
- Creating Engaging Online Lessons (Graeme Salter)
- Effectiveness of Game-Based Learning for Programming Courses (Mubashir Hussain)
- Monitor and Predict Student Engagement and Retention Using Learning Management System (LMS) (Behnaz Rezaie Ortakand)
- Enhancing Student Engagement by Using Machine Learning Algorithms (Mehrdad Razmjoo)
- Application of Big Data in Curriculum Development (Farzaneh Mayabadi, Sweta Thakur, Shaleeza Sohail, and Fariza Sabrina)
- ICT Programs in China: A Case Study of Shanxi Universities (Xin Gu, Fareed Ud Din, and Robert M X Wu)
- Technologies and Student Feedback Collection and Analysis (Gazi Farid Hossain, Deb Case, and Caitlin Smith)
Readership: Researchers, professionals, academics and graduate students in AI/Machine Learning, databases and digital security.
