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Special Issue on Big Data in Education
Internet users worldwide are currently producing more and more data of various types such
as emails, social media, search queries, etc. Such data are big data by nature. Big data
techniques hold promise for disruptive innovations leading to better health care, cleaner
environment, safer cities, more effective marketing strategies, and even new ways of
doing science. The reach of big data and analytic knowledge is impressive and pervasive.
Much of the widespread discussion around big data has focused on surveillance, marketing,
or other exploitation of data about people. The papers included in this special issue,
however, should demonstrate the impact and potential for data science to improve
education both from school administration and teaching/learning points of view. They
should address new methodologies and new applications of big data in education, the
challenges and possibilities that such enlarged scale brings for teaching and learning in this
This special issue "Big Data in Education" aspires to contribute to the further development
and advancement of the dialogue among the research pioneers of big data in education
at international level.
The topics of this special issue include but are not limited to:
Learning and academic analytics in education
The role and perspectives of big data in Information Systems programs curricula
Applications and use cases of big scholarly data by teachers and students
Strategies for learning and teaching with big data applications such as Google Trends
and Google Correlate, among others
Applications and use cases of big science by teachers and students
Privacy, security, and ethical issues related to the use of students' data
Benefits and case studies of curriculum personalization through big data
Critical perspectives on whether big data leads to big knowledge
Adaptations needed by information systems, computer science, and industrial
engineering programs to the world of big data
The extent to which students shall be introduced to the fundamentals of analytics
and appropriate ethics for handling data to meet the market needs
Lessons learned creating programs for or teaching big data and analytics to all levels
Lessons that can be applied from other research fields
These submissions can be:
Papers describing and evaluating new and/or existing methods that can be used to
solve educational challenges
Position papers that describe data science challenges that need to be overcome in
order to make methods more suited to solving large-scale educational challenges
Papers describing implementations of data mining/analytics/big data/data science
systems in school settings.
Problem descriptions that highlight significant educational
problems that could use data science expertise and skills, but are not being tackled
deadline: June
notification: August
version: November
Publication: December, 2015
Guest editor
Renato P. dos Santos, ULBRA - Lutheran University of Brazil, Brazil,
[email protected]