Global Adaptive Learning Software Market Size, Status and Forecast 2021-2027

SKU ID : QYR-17720737 | Publishing Date : 18-Mar-2021

Adaptive learning is an educational technique which uses computers as interactive teaching devices rendering to the unique needs of each learner.
USA is the largest region of adaptive learning software in the world in the past few years and it will keep increasing in the next few years. USA market took up about 53.7% the global market in 2018, while Europe and China were about 19.6%, 4.3%. From the perspective of the players,DreamBox Learning, SAS, Wiley (Knewton), Docebo, D2L, etc. are the key suppliers in the global adaptive learning software market. Top 5 took up 41% of the global market in 2018.

Market Analysis and Insights: Global Adaptive Learning Software Market
The global Adaptive Learning Software market size is projected to reach US$ 1074.8 million by 2027, from US$ 477.2 million in 2020, at a CAGR of 12.3% during 2021-2027.
With industry-standard accuracy in analysis and high data integrity, the report makes a brilliant attempt to unveil key opportunities available in the global Adaptive Learning Software market to help players in achieving a strong market position. Buyers of the report can access verified and reliable market forecasts, including those for the overall size of the global Adaptive Learning Software market in terms of revenue.
On the whole, the report proves to be an effective tool that players can use to gain a competitive edge over their competitors and ensure lasting success in the global Adaptive Learning Software market. All of the findings, data, and information provided in the report are validated and revalidated with the help of trustworthy sources. The analysts who have authored the report took a unique and industry-best research and analysis approach for an in-depth study of the global Adaptive Learning Software market.

Global Adaptive Learning Software Scope and Market Size
Adaptive Learning Software market is segmented by company, region (country), by Type, and by Application. Players, stakeholders, and other participants in the global Adaptive Learning Software market will be able to gain the upper hand as they use the report as a powerful resource. The segmental analysis focuses on revenue and forecast by Type and by Application in terms of revenue and forecast for the period 2016-2027.

Segment by Type
Cloud Based
On-Premises
Adaptive learning software are mainly classified into the following types: cloud based and on-premises. Cloud based is the most widely used type which takes up about 83.5% of the total sales in 2018.

Segment by Application
K-12
Higher Ed/College
Corporate
Adaptive learning software have wide range of applications, such as K-12, higher Ed/college and corporate, etc. K-12 was the most widely used area which took up about 66.4% of the global total in 2018. Higher Ed/College and corporate sectors market a higher growth rate.

By Region
North America
U.S.
Canada
Europe
Germany
France
U.K.
Italy
Russia
Nordic
Rest of Europe
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA

By Company
SAS
D2L
DreamBox Learning
Wiley (Knewton)
Smart Sparrow
Cogbooks
Docebo
ScootPad
Imagine Learning
Fishtree
McGraw-Hill
Paradiso
IBM

Frequently Asked Questions

This market study covers the global and regional market with an in-depth analysis of the overall growth prospects in the market. Furthermore, it sheds light on the comprehensive competitive landscape of the global market. The report further offers a dashboard overview of leading companies encompassing their successful marketing strategies, market contribution, recent developments in both historic and present contexts.
  • By product type
  • By End User/Applications
  • By Technology
  • By Region
The report provides a detailed evaluation of the market by highlighting information on different aspects which include drivers, restraints, opportunities, and threats. This information can help stakeholders to make appropriate decisions before investing.
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