This book shares original innovations, research, and lessons learned regarding teaching and technological perspectives on trust-based learning systems. Both perspectives are crucial to enhancing the e-Assessment process. In the course of the book, diverse areas of the computer sciences (machine learning, biometric recognition, cloud computing, and learning analytics, amongst others) are addressed. In addition, current trends, privacy, ethical issues, technological solutions, and adaptive educational models are described to provide readers with a global view on the state of the art, the latest challenges, and potential solutions in e-Assessment. As such, the book offers a valuable reference guide for industry, educational institutions, researchers, developers, and practitioners seeking to promote e-Assessment processes.

This book constitutes the proceedings of the 20th International Conference on Technology Enhanced Assessment, TEA 2017, held in Barcelona, Spain, in October 2017. The 17 papers presented were carefully selected from 42 submissions. They are centered around topics like e-learning, computer-assisted instruction, interactive learning environments, collaborative learning, computing education, student assessment. Chapter "Student perception of scalable peer-feedback design in Massive Open Online Courses" is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/). For further details see license information in the chapter.