Key Takeaways
- In the U.S., 73.6% of fall 2023 postsecondary students reported they used online learning at least sometimes (including in combination with in-person).
- In the U.S., the number of degree-granting postsecondary institutions offering distance education was 3,655 in 2020-21.
- In the U.S., 14.1% of all degree-granting postsecondary students were enrolled exclusively in distance education in fall 2020.
- Global e-learning market size was valued at $247 billion in 2023.
- Global e-learning market is projected to reach $457 billion by 2027.
- In the U.S., in 2020, the market for online education was estimated at $82.0 billion.
- In a 2023 meta-analysis, students in online learning conditions performed modestly better than students receiving face-to-face instruction (Hedges g = 0.20).
- In a 2020 systematic review (U.S. DoEd-affiliated), average effect of blended learning on achievement was around 0.24 SD.
- In a large RAND evaluation, students in online course pathways were 0.3 standard deviations higher in math compared with traditional instruction (reported).
- In a 2021 survey, 29% of adults in the U.S. reported they did not have broadband internet at home.
- In the U.S., 10% of U.S. households lacked a desktop/laptop computer in 2021.
- In the U.S., 22% of rural households lacked high-speed internet access in 2022 (FCC measure).
- In the U.S., 84% of K-12 teachers used some form of online learning during the 2020 school year (survey measure).
- In the U.S., 93% of school districts reported using a Learning Management System (LMS) or other platform during remote instruction in 2020.
- In the U.S., 63% of districts reported providing live instruction (synchronous) to students in 2020.
Distance learning expanded massively, blending online classes with proven support despite access gaps.
Enrollment & Participation
Enrollment & Participation Interpretation
Market & Economics
Market & Economics Interpretation
Learning Outcomes & Effectiveness
Learning Outcomes & Effectiveness Interpretation
Access, Equity & Digital Divide
Access, Equity & Digital Divide Interpretation
Policy, Infrastructure & Operations
Policy, Infrastructure & Operations Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Catherine Wu. (2026, February 13). Distance Learning Statistics. Gitnux. https://gitnux.org/distance-learning-statistics
Catherine Wu. "Distance Learning Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/distance-learning-statistics.
Catherine Wu. 2026. "Distance Learning Statistics." Gitnux. https://gitnux.org/distance-learning-statistics.
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