Title
Learning Analytics' Privacy on the Blockchain.
Abstract
Learning Analytics collect sensitive data from students. In some cases, the ethics behind the use or access by third parties are not clear. This situation raises adverse reactions and feelings of fear that generates a negative perception towards the use of Learning Analytics. In consequence, it is questioned whether privacy and security can be preserved when collecting educational data. As a result, some policies and good practices are set to frame how student data should be used in the application of this analytical approach. Its objective is to increase confidence in the application of Learning Analytics. However, some of these legal actions, which are limited to the areas in which they are originated, are the result of allegations of data leakage. Hence, these initiatives can do little to insure the use of sensitive data of students in unknown situations. To ensure continuity and an increase of confidence in the application of Learning Analytics is necessary to bind to legality a new approach to safeguard privacy of students' data in its current and future uses. Considering the above, it is possible to add a technological layer above these policies that ensures its viability. Some emerging technologies such as blockchain and smart contracts are strong candidates to ensure privacy and secure sensible data of students. The use of smart contracts allows the automation of legal actions so that they are executed as soon as irregularities in the use or data collection are detected. In this work, we propose a series of actions to preserve the identity of students and secure their data with emerging technologies such as blockchain.
Year
DOI
Venue
2018
10.1145/3284179.3284231
SIXTH INTERNATIONAL CONFERENCE ON TECHNOLOGICAL ECOSYSTEMS FOR ENHANCING MULTICULTURALITY (TEEM'18)
Keywords
Field
DocType
Learning analytics,blockchain,data privacy,digital identity,data security management
Data collection,Internet privacy,Principle of legality,Learning analytics,Knowledge management,Automation,Emerging technologies,Engineering,Information privacy,Perception,Digital identity
Conference
Citations 
PageRank 
References 
0
0.34
4
Authors
5