[AISWorld] CALL FOR CHAPTERS_Responsible Analytics & Data Mining in Education

[Mariaelena Corbeil]

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SUBMIT 1 – 2 PAGE CHAPTER PROPOSAL

by July 1, 2017
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For complete details, please visit the Call for Chapter Proposals: https://big-data-in-education.blogspot.com<https://big-data-in-education.blogspot.com/>

OVERVIEW

Due to rapid advancements in our ability to collect, process, and analyze massive amounts of data, it is now possible for educators at all levels to gain new insights into how people learn. According to Bainbridge, et. al. (2015), using simple learning analytics models, educators now have the tools to identify, with up to 80% accuracy, which students are at the greatest risk of failure before classes even begin. As we consider the enormous potential of data analytics and data mining in education, we must also recognize a myriad of emerging issues and potential consequences—intentional and unintentional—to implement them responsibly.

The following chapter topics are still available:

Chapter 7: Technical Requirements for Data Analytics in Education: Managing Server Capacities, Bandwidth, Security, and Backups

Chapter 8: Supporting Data Analytics in Education: Human and Technical Resources Needed for Collecting, Storing, Analyzing, and Mining Data

Chapter 9: Moving Towards Semantic Interoperability through the Adoption of Open Standards

Chapter 10: Assessing Data Quality: Determining What Data to Trust and Use

Chapter 12: Data Cybersecurity Issues: Contingency Plans for Handling Data Breaches

Chapter 13: Ensuring Due Process for Data-Driven Errors. Establishing Policies to Address Errors

Publisher: Taylor & Francis Group