Student-Level Data


In education, student-level data refers to any information that educators, schools, districts, and state agencies collect on individual students, including data such as personal information (e.g., a student’s age, gender, race, place of residence), enrollment information (e.g., the school a student attends, a student’s current grade level and years of attendance, the number of days a student was absent), academic information (e.g., the courses a student completed, the test scores and grades a students earned, the academic requirements a student has fulfilled), and various other forms of data collected and used by educators and educational institutions (e.g., information related to disciplinary problems, learning disabilities, medical and health issues, etc.). It should be noted that an increasing number of organizations, institutions, or companies may also collect or have access to student-level data on public-school students, typically as a part of a contract for services or a research study conducted in collaboration with schools, districts, or state education agencies.

It should be noted that a wide variety of terms may be used when referring to student-level data in education, including individual-level data, individual student-level data, student unit-level data, unit-record data, student unit-record data, record-level data, and record-level student data, among others. Because these terms may or may be used synonymously in certain technical contexts, it is important to determine precisely how the term is being defined when investigating or reporting on student data.

Increasingly, new educational technologies are redefining the definition of “student-level data,” given that educational software and online learning programs, for example, can collect a huge amount of information and metadata about the students who use them—information that was formerly impossible to track before the advent of sophisticated technologies and analytical tools—which includes information such as the geographic location of the computer being used by a student or the amount of time it took a student to answer certain questions or solve certain problems. Many online learning programs routinely collect hundreds or even thousands of distinct data points while students are using the systems—data that may then be used for any number of educational or non-educational purposes (e.g., to improve the software, modify the questions or problems students see, study how children and youth learn, or market the product to potential buyers).


Student-level data is collected and used for a wide variety of purposes, and it intersects with efforts to improve schools and educational systems in a number of ways—too many to comprehensively describe here. To cite just a few representative examples, however, student-level data may be used to:

  • Maintain more robust, accurate, and comprehensive student records for educators, students, graduates, parents, collegiate institutions, employers, and others who may need or request the information.
  • Inform or improve the instructional process by giving teachers and other educators and specialists information about the distinct learning needs, academic progress, and educational achievements of specific students.
  • Inform or improve various student-support strategies or systems, which may include any number of academic, behavioral, mental, health, or social services that students may need or access.
  • Improve the accuracy and reliability of aggregate educational data—such as graduation, dropout, or enrollment rates reported for schools, districts, and states—that originates from individual data collected on a large number of students (for a related discussion, see unique student identifier).
  • Track trends in the educational performance of individual students or educational systems over time using information such as school-completion data or standardized-test scores, for example.
  • Identify problems or weaknesses in the educational performance of students, teachers, schools, or districts for the purpose of improving academic achievement, teaching effectiveness, or educational results.

Before the advent of technologies and software applications that allow schools, districts, and state agencies to collect an array of highly detailed data on individual students, student-level data was generally limited to teacher grade books, report cards, school transcripts, attendance files, and other administrative records maintained by schools and districts. Because this information was largely or entirely paper-based—and therefore difficult, time consuming, and costly to collect, organize, or analyze—it limited the ability of educators, researchers, and others to use student-level data to diagnose education problems, track trends in performance over time, or improve the effectiveness of schools or teaching, for example. Advances in educational software, computing technologies, internet access, and innovations such as cloud-based data storage and “big data” analytics have fueled a dramatic increase in the collection and use of student-level data in recent years.

Since at least the early 2000s, some districts and state education agencies have been using large-scale data systems capable of collecting, archiving, and generating reports on a vast array of student-level data originating from multiple sources, ranging from schools to standardized tests. As technological advances make the collection of data on individual students more efficient, inexpensive, and potentially valuable to the educational process, an increasingly large, diverse, and ever more complex body of student-level data is being collected, archived, analyzed, and used at all levels of the educational system and by a growing number of researchers, institutions, organizations, and companies.

It should be noted that if student-level data is being collected for reasons other than maintaining academic records for students and their families, it is almost certainly being used, in some form, to reform or improve schools and education systems—even if the purpose is merely to provide more accurate, useful, and detailed information about performance to those working to improve schools.

While much of the discussion about student-level data in public education is focused on the large-scale collection of personal data on individual students—and on the potential applications and possible abuses of that information—the term also encompasses any information that teachers and other educators or specialists may use during the process of educating individual students. For example, teachers may keep journals, logs, or other records detailing the distinct learning needs or progress of individual students—information that may or may not be shared with colleagues and administrators or formally reported to state education agencies and other entities outside of the school. Personal learning plans, for example, are one of the many possible methods that educators might use to collect data on individual students. Early warning systems—usually databases of academic, attendance, and disciplinary information that educators use to identify and monitor students who are struggling academically or in danger of dropping out of school or not graduating on time—are another example.


Teachers and schools have always collected and maintained records of student-level data, but the transition from paper-based systems to digital systems, and from small-scale data collection by schools to large-scale data collection by state agencies and private companies, has given rise to numerous debates about student-level data and student privacy. For this reason, most debates related to the collection, storage, and use of student-level data are connected to concerns about student privacy.

For a more in-depth discussion of debates related to student-level data, see personally identifiable information.

Recommended APA Citation Format Example: Hidden curriculum (2014, August 26). In S. Abbott (Ed.), The glossary of education reform. Retrieved from