Using data for learning

What is small data for learning?

small data and learning

Allen Bonde provided the formal definition of small data, which is data that “connects people with timely, meaningful insights (derived from big data and/or “local” sources), organized and packaged – often visually – to be accessible, understandable, and actionable for everyday tasks.”[1]

In other words, small data is data small enough for humans to comprehend. On the contrary, big data is a mass collection and analysis of complex data useful for discovering trends and patterns. One problem is that large universities have the ability and amount of data to analyze using big data methods while small institutions are not able to collect enough data or use sophisticated tools to use big data reliably.

Instead of using big data to determine students’ potential and learning processes, institutions (not just smaller ones) would benefit from using small data to tailor courses and teaching methods to each student’s needs.

The use of technology in teaching is generating many types of data which, though not qualifying for “big data,” may provide insights that in turn will guide improvement actions.

Practical tips for using small data for learning

  1. Use data to improve teaching by collecting formative evaluations instead of summative evaluations and making feedback more specific rather than generic when collected at the end of the semester.
  2. Use Learning Management System (LMS) to collect data and improve learning by supervising overall class performance or individual performance analytics provided by the LMS used. Analyze quiz and test results to tailor a more effective online class.
  3. Depending on the particular concern, check the access report, interaction report, assignment analysis, assessment analysis, or gradebook from LMS to effectively administer to students.
  4. Encourage students to use technology to generate their own data in order to improve their own learning, gain greater experience, stretch themselves beyond familiar content, and get advice and feedback from experts in relevant fields.


Shewmaker, J. & Fang, B. (2016). The case for small data in higher education. Psychology, 1, 159-168. doi:10.3233/978-1-61499-690-3-159


[1] Scott, J. (2015). Understanding the value of small data. Retrieved from