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Adaptive Learning Software Development/Supply

Active

State & Local

Response Deadline10/30/2026, 09:00:00 PM UTC

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

AI Contract Overview

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This subcontract for Adaptive Learning Software Development and Supply involves providing and configuring practice engines for prime contractors working on UNC System Office educational technology projects. The scope of work focuses on the delivery of a functional adaptive practice module that utilizes data analytics dashboards for retention tracking and implements specialized algorithms for mastery-based progression and spaced repetition to dynamically adjust content difficulty based on student performance. The project is categorized under NAICS code 513210 and mandates strict adherence to FERPA regulations and WCAG 2.1 Level AA accessibility standards. Interested parties should note the response deadline of October 30, 2026, for this North Carolina state agency initiative.

General Info

Agency

North Carolina → Unc - System Office

NAICS

513210 - Software Publishers

Place of Performance

NC, USA

Set-Aside

NONE

Documents

This scope was carved out of RFP-EDTECH-2026-01.

The full solicitation package (1 document), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

Educational Technology Tool/Solution

AI Contract Breakdown

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Timeline

PostedOct 12

subcontract

Response DeadlineOct 30

Submission deadline

Response Deadline

10/30/2026, 09:00:00 PM UTCin 17 days

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Organization & Contact Information

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AgencyNorth Carolina → Unc - System Office

ContactsNo contacts available

OfficeN/A

Organization / AgencyNorth Carolina → Unc - System Office

Office AddressN/A

ContactsNo contact information available

Full Description

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Supplies and configures practice engines for prime contractors on UNC - System Office educational technology projects. Implements algorithms for spaced repetition and mastery-based progression to adjust content difficulty based on student performance. Utilizes adaptive learning algorithms and data analytics dashboards for retention tracking. Requires WCAG 2.1 Level AA and FERPA compliance. Delivers a functional adaptive practice module.

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