A Case Study Using Qlik For K12 Decision Making During The Time of COVID-19

By Rachel Johnson, Director, Enterprise Solutions, Loudoun County Public Schools

Loudoun County Public Schools (LCPS) was able to purchase 1,500 total hotspots from different vendors in early March, in anticipation of school closures for a small percentage of families and staff who do not have access to the internet in their homes.

LCPS needed to identify household data, not just students, in order to equitably distribute the devices to families. In addition, a triage approach for need was established to provide hotspots to families based on these needs:

1. Households identified with a disadvantaged status

2. Households with multiple students

3. Households with students in higher grade levels (starting with High School as a top priority)

Each hotspot can serve up to 15 devices in a household.

The Department of Digital Innovation was asked to identify families and staff who needed a WiFi hotspot during the closure of buildings.

A Google form survey was sent out to the public school families and staff requesting the following information:

1. Student name, address, LCPS school

2. Parent/Guardian name and contact information

The results of the survey were then loaded into Qlik, connected to additional data, and a set of visualizations developed.

Sheet 1 - Map of Addresses w/Student Count is a geo-map of the responses from the survey.

Sheet 2 - Prioritization Data identifies students and household counts, along with the decision factors such as Disadvantaged status, number of students in a household, and grade levels (3-12 to ensure instructional delivery online).

By reviewing the data we identified specific clusters (high school feeder zones that include elementary, middle and high schools in a region). In this example, the JCH (John Champe HS) cluster showed the highest number of respondents:

However, the number of Disadvantaged students was lower than PVH (Park View HS) cluster.

Thus, we were able to identify households in the PVH cluster as the first set of recipients for the hotspot devices.

Sheet 3 - Contact Information shows the data we needed to contact families via all of our methods and stage pick up processes outside of the school. The student data is tied to the student information system tables and shows indicators for English Learners and Special Education students as well.


As hotspots were distributed, data was reloaded and adjustments made based on usage metrics and feedback from principals who were in touch with families. The Qlik app significantly improved our ability to identify households in need of hotspots and quickly contact and deploy devices.

@LCPSOfficial using @Qlik was able to identify and triage WiFi hotspot allocations to students/households in greatest need in anticipation of school closures related to #COVID-19. Read the blog post by Rachel Johnson @LCPSOfficial.

 

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