Educational Technology News

SUBMIT A 1-2 PAGE CHAPTER PROPOSAL

Deadline Extended - July 1, 2017

 

Title:

 

Responsible Analytics and Data Mining in Education: Global Perspectives on Quality, Support, and Decision-Making

 

Synopsis:

 

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. For example:

 

• Who collects and controls the data? 
• Is it accessible to all stakeholders?
• How are the data being used, and is there a possibility for abuse?
• How do we assess data quality? 
• Who determines which data to trust and use?
• What happens when the data analysis yields flawed results?   
• How do we ensure due process when data-driven errors are uncovered?
• What policies are in place to address errors?
• Is there a plan for handling data breaches?

 

This book, published by Routledge Taylor & Francis Group, will provide insights and support for policy makers, administrators, faculty, and IT personnel on issues pertaining the responsible use data analytics and data mining in education.

 

For more information and to submit a proposal, please visit:

https://big-data-in-education.blogspot.com

Via EDTECH@UTRGV

SUBMIT A 1-2 PAGE CHAPTER PROPOSAL

Deadline Extended - July 1, 2017

 

Title:

 

Responsible Analytics and Data Mining in Education: Global Perspectives on Quality, Support, and Decision-Making

 

Synopsis:

 

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. For example:

 

• Who collects and controls the data? 
• Is it accessible to all stakeholders?
• How are the data being used, and is there a possibility for abuse?
• How do we assess data quality? 
• Who determines which data to trust and use?
• What happens when the data analysis yields flawed results?   
• How do we ensure due process when data-driven errors are uncovered?
• What policies are in place to address errors?
• Is there a plan for handling data breaches?

 

This book, published by Routledge Taylor & Francis Group, will provide insights and support for policy makers, administrators, faculty, and IT personnel on issues pertaining the responsible use data analytics and data mining in education.

 

For more information and to submit a proposal, please visit:

https://big-data-in-education.blogspot.com