Reflective Assessment for Deep Learning and Knowledge Building: An Empirical Case in China

Knowledge building aims to transform schools into learning communities and bring knowledge creation into schools. The book therefore elaborates on how learning, technology, and assessment can be aligned both online and offline to facilitate such a process.

Adopting a quasi-experimental design and drawing on rich data from forum discussions, questionnaires, interviews, learning outcomes, and classroom presentations, this book shows that the knowledge building environment, augmented by reflective assessment and principles, helped Chinese students to develop a deeper approach to learning, improved academic performance, and promoted collective knowledge advances. The book also discusses the potentials and challenges of designing technology-supported, assessment- and principle-based learning environments in tertiary contexts, especially when deep learning and knowledge building capacity are greatly emphasised in the knowledge era.

The book will be of interest to scholars and educators working in learning sciences and computer-supported collaborative learning.

Chunlin Lei is deputy dean and associate professor at the School of Languages, Shanghai University of International Business and Economics. He received his PhD from the University of Hong Kong and has published over 40 research articles and book chapters in the areas of knowledge building and L2 learning.