Policy and Educational Data Mining

Call for Papers: Policy and Educational Data Mining: Norms, Risks, & Safeguards


Educational Data Mining is now common practice. Administrators and policymakers use data to evaluate educational programs, rate instructors, and plan for future needs. Researchers use data to develop new interventions. And students, parents, and instructors rely on data-driven guidance for support.

As EDM has become commonplace so too has widespread data retention. Existing laws such as the U.S. Every Student Succeeds Act have imposed new mandates for data collection and reporting as have smaller scale laws that require publication of "school report cards" and even grade-based pay. Schools have likewise come to rely on cloud-based applications to support instruction, administration, and even personal modeling. New technologies and new uses pose new policy questions such as:

  • Who owns the educational data and trained models?
  • Are data-driven models susceptible to bias or attack? If so how do we secure them?
  • Who can audit or challenge the decisions of these models, and how?
  • What safeguards should be put in place to preserve privacy and educational integrity?
  • Can students, parents, or educators opt-out of tracking or modeling?
  • Who should pay for data retention?
  • Should educational data be portable?

In this workshop we will discuss this new policy landscape, the technical and social approaches to addressing these risks, and what other closely-related communities have done. We welcome submission of:

  • Position papers (up to 5 pages): that address the policy questions above or describe practical experience with policy issues.
  • Survey papers (up to 8 pages): that provide an overview of a relevant research area or policy framework.
  • Research papers (up to 8 pages): that describe substantive work on new technologies to address important policy concerns.

Submission Instructions

  • Submission deadline: Friday June 22nd.
  • Submissions should be formatted using the EDM style
  • Submission via EasyChair


  • Collin F. Lynch: North Carolina State University.
  • Beverly Park Woolf: University of Massachusetts.

Survey on Educational Data Mining Policy

Below is a survey to poll current members of the IEDMS to assess their views on current policy issues related to Educational Data Mining and to collect initial opinions on a draft policy statement for the society.

Please complete the questions in the survey attached to this link.

Schedule of Events (Sunday, July 15th)

  • 8:30 - 9:15 Opening Remarks, Introductions, and summary of past events.
  • 9:15 - 9:35 Paper 1 (20 min)
  • 9:35 - 9:55 Paper 4 (20 min)
  • 9:55 - 10:15 Breakout 1: Issues of importance, primary concerns.

  • 10:30 - 10:40 Paper 2
  • 10:40 - 10:50 Paper 3
  • 10:50 - 11:20 Experience Panel Ken, Steven, Christina
  • 11:20 - 11:40 Closing working groups.
  • 11:40 - 12:00 Closing Wrapup.