As Web culture permeates the higher education experience, from Yik Yak conversations to collaborative digital assignments, questions of data privacy are gaining national attention. In 2015, 46 states introduced 182 bills addressing student data privacy, according to nonprofit advocacy group the Data Quality Campaign.
These attempts to protect personal information treat student data as something to be managed and controlled—but don’t give students themselves a voice in how they want their data to be used.
About 50 students and alums took advantage of their rights under the Family Educational Rights and Privacy Act of 1974 by sending requests for personal records to the Office of Admission and the Office of the Registrar this academic year, said Dean of Admission Jim Miller ’73. In a typical year, only one or two students request to see their academic files, said Christopher Dennis, deputy dean of the College.
The dramatic uptick comes after Stanford University students created an anonymous newsletter called “The Fountain Hopper” designed to encourage other students to invoke FERPA to receive admission records. The newsletter sparked a wave of current and former students demanding to see their records at colleges and universities across the country.
Six principles should inform the collection, storage, distribution and analysis of data derived from human engagement with learning resources. The principles are stated here at a level of generality to assist learners, scientists, and interested citizens in understanding the ethical issues associated with research on human learning.
- Respect for the rights and dignity of learners. Data collection, retention, use, and sharing practices must be made transparent to learners, and findings made publicly available, with essential protections for the privacy of individuals. Respect for the rights and dignity of learners requires responsible governance by institutional repositories and users of learner data to ensure security, integrity, and accountability. Researchers and institutions should be especially vigilant with regard to the collection and use of identifiable learner data, including considerations of the appropriate form and degree of consent.
- Beneficence. Individuals and organizations conducting learning research have an obligation to maximize possible benefits while minimizing possible harms. In every research endeavor, investigators must consider potential unintended consequences of their inquiry and misuse of research findings. Additionally, the results of research should be made publicly available in the interest of building general knowledge.
- Justice. Research practices and policies should enable the use of learning data in the service of providing benefit for all learners. More specifically, research practices and policies should enable the use of learning data in the service of reducing inequalities in learning opportunity and educational attainment.
- Openness. Learning and scientific inquiry are public goods essential for well-functioning democracies. Learning and scientific inquiry are sustained through transparent, participatory processes for the scrutiny of claims. Whenever possible, individuals and organizations conducting learning research have an obligation to provide access to data, analytic techniques, and research results in the service of learning improvement and scientific progress.
- The humanity of learning. Insight, judgment, and discretion are essential to learning. Digital technologies can enhance, do not replace, and should never be allowed to erode the relationships that make learning a humane enterprise.
- Continuous consideration. In a rapidly evolving field there can be no last word on ethical practice. Ethically responsible learner research requires ongoing and broadly inclusive discussion of best practices and comparable standards among researchers, learners, and educational institutions.
All 10 are listed below:
1) Student data belongs to the student.
2) Student data should never be sold or shared without explicit permission.
3) Student data should only be used to improve learning outcomes.
4) Student data should be easy to manage.
5) Student data should be very carefully protected.
6) Student data should be clear and comprehensible.
7) Students should be able to consolidate their data.
8) Student data should be portable.
9) Student data analysis should be completely stoppable — and recoverable.
10) Institutional IP should be protected.