With Big Data comes Big Responsibility for Science Equity Research

Research output: Contribution to journalJournal articleResearchpeer-review


  • jmbe-20-12

    Final published version, 296 KB, PDF document

Our ability to collect and access large quantities of data over the last decade has been revolutionary for many social sciences. Suddenly, it is possible to measure human behavior, performance, and activity on an unprecedented scale, opening the door to fundamental advances in discovery and understanding. Yet such access to data has limitations that, if not sufficiently addressed and explored, can result in significant oversights. Here we discuss recent research that used data from a large global sample of high school students to demonstrate, paradoxically, that in nations with higher gender equality, fewer women pursued science, technology, engineering, and mathematics (STEM) degrees than would be expected based on aptitude in those subjects. The reasons for observed patterns is central to current debates, with frequent disagreement about the nature and magnitude of problems posed by the lack of female representation in STEM and the best ways to deal with them. In our international efforts to use big data in education research, it is necessary to critically consider its limitations and biases.
Original languageEnglish
JournalJournal of Microbiology and Biology Education
Issue number1
Pages (from-to)1-4
Number of pages4
Publication statusPublished - 2019

Number of downloads are based on statistics from Google Scholar and www.ku.dk

No data available

ID: 218178957