Dive Brief:

• Predictive technology, increasingly used at the college level, is meant to flag students at risk of failing, but concerns about students being pigeon-holed and falling through the cracks persist as its use grows at the K-12 level.
• Community college students shared their concerns during an EduCon 2.9 panel at Philadelphia’s Science Leadership Academy last month, according to an article by The Hechinger Report, and they explained issues of digital redlining and privacy.
• If predictive programs flag students as being behind, absent any context about what was happening in the students’ lives outside of school in that particular class, there is a chance an inaccurate reputation will follow them through later classes.

Dive Insight:

Technology can sometimes create double-edged sword situations. This is one of them. Collecting more data about students can help inform supports in later years and give teachers an opportunity to create more personalized responses based on student needs.

Still, there is a lot of research on the consequences of teacher assumptions. If a teacher sees poor performance in a prior year but doesn’t get any anecdotal information about the fact that a parent was incarcerated or a family lost their home, that student could be hurt by the teacher’s low expectations or mistaken conclusions. Districts will have to consider this risk, especially as they create data profiles of students that will follow them from an elementary to a middle or high school, for example.