Big Data and Data Science in Educational Research

Dear Colleagues,

The growing volume of data generated by machines, humans, applications, sensors and networks, together with the associated complexity of the research environment, requires innovation in educational research. In education, the ability to work with new forms of data and analytical tools can provide educational institutions with the knowledge they need to operate efficiently in highly technical and challenging research environments. Moreover, the growing research interest in Big Data and analytics in education suggests that the field of educational research is likely to become a data-intensive in the near future.

Educational Data Science(EDS) is a growing field of inquiry, primarily concerned with the extraction of information from a large and complex set of educational data, with the purpose of discerning valuable and actionable knowledge. EDS techniques can be applied to explore large quantities of data on students’ learning trajectories in learning management systems, social media interaction, faculty teaching practices. These data can be harvested and analysed to reveal useful patterns and insights to support better decisions relating to student learning, teaching and optimisation of institutional resources.

This Special Issue will present selected examples of the latest research on the application of Big Data and Data Science concepts, approaches, models, methods and methodologies in educational research. It will cover fundamental concepts and advanced Data Science approaches and analytic methods used in educational research, and ultimately open up opportunities to research and develop new analytical methods and techniques in Big Data applications in educational research.

Dr. Ben Kei Daniel
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Big Data and Cognitive Computing is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.