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Research Paper | Computer Science & Engineering | India | Volume 4 Issue 11, November 2015

Data Analysis and Knowledge Extraction in Educational Data Mining (EDM)

K. Sirisha ^[2] | Pathuri Siva Kumar ^[6]

Abstract: While the field of educational data mining (EDM) has generated many innovations for improving educational software and student learning, the mining of student data has recently come under a great deal of scrutiny. Many stakeholder groups, including public officials, media outlets, and parents, have voiced concern over the privacy of student data and their efforts have garnered national attention. The momentum behind and scrutiny of student privacy has made it increasingly difficult for EDM applications to transition from academia to industry. Based on experience as academic researchers transitioning into industry, we present three primary areas of concern related to student privacy in practice policy, corporate social responsibility, and public opinion. Our discussion will describe the key challenges faced within these categories, strategies for overcoming them, and ways in which the academic EDM community can support the adoption of innovative technologies in large-scale production.

Keywords: Student privacy, student data, policy

Edition: Volume 4 Issue 11, November 2015,

Pages: 109 - 113