From Data Dolt to Superhero: Leveraging Micro-Data Trends for Personalization

Written by Leilani Cauthen on September 13, 2018

This brief was published originally by The Learning Counsel. It addresses the data issues that keep leaders from getting to real personalization from data collection, and provide the five steps to becoming a data superhero.

Micro-data is an observation data-point collected on an individual subject—a statistical unit, as in one question with answer, one quiz, or one piece of personal identity. Being the modern data superhero is using this small data for personalization.

The problem with introducing this interesting new data management idea is that a lot of school executives and teachers see ever-increasing data collection, and the drive to personalization as a sort of peril. First, according to the Data Quality Campaign, “While state and federal policies incentivized data use, the focus was initially on building systems for compliance and accountability.” Accountability implies repercussions, so after decades of forced reporting to multiple task masters in State and Federal governments in pursuit of “Big Data,” it’s no wonder educators get a teensy defensive. Additionally, personalization ultimately means changing a teacher’s routine to give very focused attention to each student—a burden on top of an already
enormous load.

Yet, remaining a data dolt is the equivalent to keeping one’s “head in the sand” on collecting, analyzing and using data, especially without regard to encouraging new tech developments. It’s resistance to an evolution in practice that refines the blunt instrument of human teaching and learning interaction into a masterwork. Small data, not just big trends, is the trick.

Enter a trend of micro-data in teaching and learning. Small points efficiently gathered and able to provide timely learning interjection that personalizes teaching for students. The pathway to becoming an education super-hero is being paved by these small increments of assessment data, plus “running data” or compilations of student progress, while also producing needed compliance reports. Like all new things on the education landscape rushing to bring innovation,
there are issues—villains to be defeated by a superhero.

The Issues

1. Low-tech = Unwitting High-cost

What leaders don’t know, they of course don’t prioritize. A lot of schools run “spread-marts,” land-locked islands of data collected into spreadsheets or proprietary systems to run school operations and reporting requirements. Secretarial staff and administrators do this work or require some entry by teachers, a cumulative cost of staff hours that’s easy to overlook when you just don’t know that an alternative exists or have reviewed the volume of duplication of efforts. “If teachers must manually integrate systems or enter data multiple times, the rate at which they can use current information to make decisions is greatly reduced,” Josh Klein, Chief Information Officer, Portland Public Schools.

2. Data Quality

Data quality is an issue when collected incompletely or indifferently. “Good enough” data is often used to show how a school is doing in systems that don’t allow granular inspection. This combination is a recipe for despair when data mistakenly shows failures. This big turn-off inhibits schools from a desire to use data.

3. Bad User Interface

Old analytics systems have had proprietary archaic user interfaces that required copious amounts of training to use with any degree of acumen. Dedicating staff was an added cost that has turned off schools in the past.

4. Lack of Stakeholder Involvement

For lack of involving teachers, parents and students in needs, systems in the past have been built with a focus on only administrative data. The Data Quality Campaign found that, “Teachers were not asked what data they needed—and in what format—to differentiate instruction, increase student achievement, and reflect on their own practice. Teachers did not have access to data to help them improve teaching and learning, yet it was being used to evaluate their
performance in the classroom.” The issue is the hard work of involving all the important stakeholders to get to actual utility with data.

5. Data Driven vs. Data Informed

Just using data can result in students being treated like little percentage rankings—evaluated but not necessarily helped. Getting to a point where teaching is data informed, with correct actions being taken to enhance learning should be the overriding concern—and can only be done when
micro-data is a major focus.

6. Perception of Prohibitive Cost

While most schools use one or more student information systems for grades, attendance, and more, only about fifty percent use a learning management system or any repository. The disparity between the larger districts and those below the top 200 in size nationally is wide in
this respect. In the bulk of the smaller districts and schools, getting a major system in place is often perceived as cost prohibitive. In addition, perception is that schools must have
a “major system” to get to complex analytics with data. If they don’t have one, they make-do with whatever low-level tools they have to hand.

To find more on data literacy, you can access The Learning Counsel’s special report on “Analytics and Onboarding.”

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