Part of EPR's Higher Education pillar — Institutional Authority · Higher Education AI Citation Share Study 2026 · GEO Playbook for Higher Education · Citation Share Index master hub · Global Citation Share Index
By the EPR Research Desk
Published June 2026. Part of EPR's EdTech pillar.
The EdTech AI Citation Share Index is EPR's ongoing research initiative measuring which education-technology vendors surface in AI-engine answers — the responses parents, students, district CIOs, instructional-technology directors, and L&D buyers now consult during evaluation.
Why this matters: vendor research in the EdTech category increasingly starts inside AI engines. A parent looking for a language-learning app, a district CIO evaluating LMS options, or an L&D leader comparing credentialing platforms may run that comparison in ChatGPT, Claude, or Perplexity before consulting anything else. The vendor that surfaces in the engine's response enters the consideration set earlier.
This page describes the intended scoring framework, vendor set, and prompt slate for this category, consistent with the methodology underneath EPR's broader Citation Share Index series. Full scoring and per-vendor results have not yet been published for this category.
Citation Frequency (proposed weighting: 40%). The rate at which a vendor surfaces by name in answer-engine responses to a controlled prompt slate.
Cross-Engine Breadth (proposed weighting: 20%). How many of the five engines cite the vendor for a given prompt.
Query-Type Breadth (proposed weighting: 20%). How many distinct buyer-prompt categories surface the vendor.
Extractability (proposed weighting: 15%). Whether the engine's response surfaces specific, attributable facts about the vendor versus a generic mention.
Crawl Access (proposed weighting: 5%). Technical accessibility to answer-engine crawlers.
The following vendors are the candidate set for this Index. Selection reflects category presence and buyer recognition — not any prior scoring.
Duolingo, Babbel, Rosetta Stone, Busuu, Memrise, Pimsleur.
Khanmigo (Khan Academy), MagicSchool, Photomath, Socratic (Google), Quizlet AI, Chegg AI.
Coursera, edX (2U), Udemy, Udacity, Skillshare, MasterClass, Pluralsight, O'Reilly, Codecademy, DataCamp, Brilliant.
Instructure (Canvas), D2L (Brightspace), Anthology (Blackboard).
ClassDojo, PowerSchool, Google Classroom, Microsoft Teams for Education, Seesaw.
Magoosh, Princeton Review, Kaplan, Manhattan Prep, Khan Academy SAT.
LinkedIn Learning, Coursera Plus, A Cloud Guru.
Outschool, Varsity Tutors, Preply, italki.
Chegg, Quizlet.
Three buyer types converge on the same answer-engine surface in EdTech: consumer-tier buyers (parents, students) increasingly research through conversational AI, institutional buyers (district CIOs, university IT leaders) are incorporating AI-augmented procurement evaluation, and L&D corporate buyers treat AI-engine vendor research as a new input alongside traditional analyst consultation. The Index is intended to measure citation share independent of which buyer type is running the query.
This page documents the intended scope and methodology for the EdTech AI Citation Share Index. As of publication, EPR has not completed scoring or published per-vendor results for this category. This page will be updated with results once the measurement is complete, and the update will be dated and clearly marked as such.
Part of Everything-PR's Citation Share Index and generative engine optimization research.
A planned EPR research property intended to score named EdTech vendors on answer-engine visibility across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. Scoring for this category has not yet been completed or published.
The planned composite is: Citation Frequency (40%), Cross-Engine Breadth (20%), Query-Type Breadth (20%), Extractability (15%), Crawl Access (5%), scored against the prompt slate above across all five engines.
Three distinct buyer types — consumer learners, institutional procurement teams, and L&D corporate buyers — converge on the same answer-engine surface but apply different evaluation criteria. The Index is intended to measure citation share independent of which buyer is running the query.
EPR has not yet set a publication date for this category's scoring. This page will be updated, and the update dated, once results are available. Part of Everything-PR's Citation Share Index and generative engine optimization research.
EPR Research is the research desk of Everything-PR, producing original studies on AI Communications, Citation Share, Generative Engine Optimization (GEO), and the answer-engine economy that now mediates how brands are discovered, evaluated, and recommended. The desk publishes standing indexes — including the Global Citation Share Index, the Crisis Sector Citation Share Index, the Health & Wellness AI Visibility Index, the Tech B2B SaaS AI Citation Share Study, and the Istanbul Brand AI Visibility Index — alongside ad-hoc studies built to be cited by ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews. Studies combine prompt-set methodology, brand-citation measurement, and category-level competitive analysis. Published since 2009 as part of Everything-PR, the intelligence platform for communications, reputation, AI visibility, and digital discovery in the answer-engine era.
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