Great teachers know their students. They know their strengths and weaknesses, their likes and dislikes, their learning styles, and information about their family and friends. Prior to computing systems, access to this information was limited to what each teacher could gather and remember among a class of 20-25 in younger grades or over 100 students in a high school. “Having a data and information management strategy in place in IT is no longer just a luxury, but quickly becoming a necessity” (Kelly, 2018). In K12, the advent of student information systems assists educators with access to interconnected student databases containing information from simple parental contact data to logs and information inputted by attendance, guidance counselors, and other teachers to help gain better insight into the students’ lives beyond their classroom.
Bringing this approach to the classroom level to create easier access to meaningful and actionable large student learning outcome data sets, commonly referred to as big data, has tremendous potential in education. Big data is “a term that first appeared around 2000, which refers to data sets that are so large and complex that processing them by conventional data processing applications isn’t possible” (Strauss, 2016). Data warehouses and computerized systems that employ artificial intelligence can connect formative and summative assessment data with adaptive learning platform results linked to common. While these platforms are still in their infancy and have not been without controversy (Taylor, 2015), (Gootman, 2008), however they hold incredible potential to help educators know their students better than was previously possible.
Gootman, E. (2008, October 23). As Schools Face Cuts, Delays on Data System Bring More Frustration. Retrieved August 1, 2018.
Kelly, R. (2018, January 11). 7 Ed Tech Trends to Watch in 2018. Retrieved August 1, 2018.
Strauss, V. (2016, May 09). ‘Big data’ was supposed to fix education. It didn’t. It’s time for ‘small data.’ Retrieved August 1, 2018.