56 Examples of Student Data

John Spacey, September 03, 2021

Student data is data that relates to the performance, health, characteristics, behavior and identity of a student. This can be personally identifiable or anonymized. Student data is compliance intensive data that relates to the privacy of children and adults such that it is surrounded in complex security and ethical issues. The following are common examples of student data.

Achievements	Address
Administrator Produced Rankings & Scores	Algorithmic Rankings & Scores
Assignment Scores	Attendance Records
Awards	Behavior Categorization
Behavior Observations	Benchmark Assessments
Courses	Data from Partners (e.g. Internships)
Data from Service Providers (e.g. school bus operator)	Date of Birth
Digitized Assignments	Digitized Homework
Digitized Test Answers	Digitized Yearbooks
Disciplinary Actions	Disciplinary Observations
Economic Status	Emergency Contacts
Enrolment History	Ethnicity / Race
Extracurricular Activities	Gender
Geographical Location Data (e.g. GPS Tracking)	Grades
Health History	Health Status
Immigration Status	Interests
Media	Name
Nationality	Parent Comments
Parent Information	Photographs
Placements	Self-Assessments
Special Needs	Sports Participation
Sports Results	Standardized Test Scores
Student Attitudes	Student Comments
Student Number	Student Opinions
Student Personality Characteristics	Student Surveys (potentially capturing indepth information)
Teacher Designed Test Scores	Teacher Observations (potentially capturing indepth information)
Teacher Produced Rankings & Scores	Vendor Calculated Scores & Rankings
Video Recordings	Voice Recordings

Poorly structured outsourcing of student data can give a vendor leverage over a school system such that the relationship becomes difficult to exit.

Student data can be problematic. For example, a teacher who uses popular psychology to stereotype a student into a "learning style." This may be viewed by all of a student's future teachers resulting in this stereotype influencing the student's entire academic career. Where data is broadly shared, this can result in the stereotype sticking even where the student changes schools or districts.

Some uses of student data can be criticized as the industrialization of education whereby the human experience is over-measured and commoditized.

Basic student data such as name, address, age, current enrollment and emergency contacts is required for administrative purposes.

Student data can have an oppressive or chilling effect with the sense that everything a student does goes on their "permanent record." This can be addressed with a clear data retention policy whereby most student data is only retained for a few years.

If student data is leaked, it may be tied to an individual for the rest of their life as data can't be retracted from public disclosure.

In some nations and jurisdictions, students and parents may have the right to view their data at any time and to have inaccuracies or outdated negative information removed.

Many parents and students may have concerns about data collection such that public or private schools that offer minimal data collection may be preferred. In other words, marketing a school as a data-driven experience may backfire, although this will certainly appeal to some parents.

Several of the data fields listed above may be extremely problematic. For example, fields such as economic status where they are based on an administrator's opinion or bias.

Sharing of public education data with private companies such as tutoring firms is ethically problematic. Likewise, sharing student data with non-government organizations can be problematic where data isn't securely anonymized.

Schools can consider anonymized data for the purposes of data collection and reporting. For example, a fully anonymous survey that captures statistics about ethnicity and gender at a school that avoids the complex issues related to personally identifiable information. It should be noted that in many cases is possible to de-anonymize data, particularly where it originates with personally identifiable data collections.