Answering the Big Questions: A Holistic View for Better Understanding

To mitigate Covid-19 learning losses, school districts need data analytics built on digital identities. 

GUEST COLUMN | by Jim Harold

In the wake of the pandemic, K-12 superintendents face daunting expectations. Perhaps none is more challenging—and controversial—than mitigating COVID-19 learning losses. Initial reports have documented lost progress in math and English language arts (ELA) as well as widening racial and socioeconomic achievement gaps. Researchers fear that disruptions to education will impact students’ future educational attainment and income. 

In response, the U.S. government has allocated billions of dollars to school districts for mitigating learning losses. Parents, politicians, and school boards are anxious to know how superintendents will use these funds.

‘…the foundation of this scalable approach is digital identity, a construct for representing students and understanding their educational journeys.’

The truth is that standardized tests and grades are lagging indicators and therefore not able to identify learning losses in a timely way. Districts could benefit from new approaches to educational analytics that can answer the big questions about COVID-19’s impact. I believe the foundation of this scalable approach is digital identity, a construct for representing students and understanding their educational journeys.

Beyond tests and grades

Today, most K-12 districts rely on standardized tests and academic performance to measure educational outcomes. These are just two among many tools needed to measure and address learning losses. They have limitations.

First, although standardized testing may enable national and international comparisons between school systems, they receive too much weight. They don’t necessarily measure the success of students or the efficacy of their teachers and curricula. Researchers have found that in the U.S., standardized test results reflect a student’s living circumstances rather than the quality of their education. 

Second, both standardized tests and grades tend to be historical measurements. By the time a district can analyze and apply these data points, they may be outdated, and the learning loss may be far advanced. Some states can turn around standardized test results in two weeks, but again, the results have limited power to explain learning outcomes. 

Third, tests and grades do not capture all the data that differentiates individual students and cohorts of students. Students are complex, ever-changing beings. Technology needs to reflect this truth. Test results and grades are not necessarily more explanatory than behavioral, health, demographic, lifestyle, and relational attributes.  

Rather than settle with tests and grades, schools need a holistic collection of data to understand the cause of learning losses and efficacy of interventions. They need this data to be updated continuously so it can show learning losses days or weeks after they emerge instead of months or years later. That data is available in the typical educational technology (edtech) stack, but it’s not accessible—yet—because edtech applications and databases tend to live on separate islands without the ability to “talk” to each other.

The interoperability problem

Hypothetically, a school district’s edtech platforms can answer the big questions about COVID-19 learning losses. Especially since schools closed, students have created troves of data in platforms like ABC Mouse, Edgenuity, and Khan Academy. That data is rich with insight on learning losses. Unfortunately, those systems are not designed to pool data.

Like other sectors, education has an interoperability problem, meaning each platform has a different way to code and organize data about users. Khan Academy might have a record of a student named Jenna Smith, and so does Edgenuity, but those two platforms cannot communicate what they each know about Jenna. She has a different identity in each system.

As a result, when educators try to learn about Jenna—or a cohort in which Jenna is included—they look through the silo of one system that suffers from blind spots. Moreover, analyzing student progress one system or one student at a time isn’t scalable or cost effective. Rather than hope that edtech vendors will quickly adopt a universal data standard (unlikely), school districts need a practical, attainable way to make use of their data now. 

Digital identity helps answer the big questions 

My vision is that K-12 school districts will reorganize their edtech stacks around digital identities that humanize students and capture the richness of their experience. Edtech stacks could feed academic, behavioral, health, demographic, lifestyle, and relation data from systems to digital identities that represent a complete view of each student. School districts that organize their edtech around digital identity would be able to answer the big questions about learning losses and take effective action as progress begins to slow, not long after the lesson is over.

For example, examining cohorts of digital identities could reveal when learning losses occurred and in which units of which courses and subjects. Educators could examine whether learning losses correlate with, say, the location of one’s family home, at-home versus in-person learning, or other predictive variables. Most importantly, schools could react quickly to learning losses and test an intervention in a few weeks instead of a few months or years.      

For districts struggling to deal with COVID-19 learning losses and racial achievement gaps simultaneously, digital identities would offer insightful new data. Which units within which subjects are associated with learning gaps? Which interventions close or widen achievement gaps?

The power of digital identities is not only the speed and scale of analytics but also the specificity. Rather than compare radically different districts by arbitrary standards, educators could examine their community in its unique geographical, demographic, and cultural context. 

A new foundation for learning

This vision for digital identity begins with better ways to manage student, teacher, and staff access to edtech systems. It will eventually require collaboration among vendors, IT personnel, and curriculum and instruction (C&I) leaders. The aim is to design a learning environment that can understand and support students—initially through analytics and later through personalized learning.

In the meantime, superintendents are in the spotlight and expected to show how they will overcome COVID-19 learning losses. I can think of no better moment and reason to tap the data siloed inside their edtech stacks. The answers and solutions are there.

Jim Harold is CEO of Identity Automation, a digital identity platform providing identity and access management solutions to safeguard learning environments, simplify workflows and increase instructional time for educators. Connect with Jim through LinkedIn.


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