Adaptive Learning Software Market Size, Share, Growth and Global Industry Analysis By Type & Application, Regional Insights and Forecast to 2024-2032
Growth Factors of Adaptive Learning Software Market
The adaptive learning software market size was valued at USD 1.61 billion in 2019, and the market is now projected to grow from USD 7.94 billion in 2027 to USD 17.64 billion by 2031, exhibiting a CAGR of 22.1% during the forecast period of 2020-2027.
According to the recently launched market reports of 2021-2024, the Adaptive Learning Software Market has displayed a high growth rate. This software integrates artificial intelligence and machine learning in delivering relevant education contents to learner hence enhancing learning interest individually. Leading vendors are McGraw Hill, Pearson, DreamBox Learning, and Knewton and have solutions for K-12, higher education and professional segments. The overall interconnection of the elements of gamification, data processing, and immediate personalized feedback has been a value addition to the fields of user experience. As the global use of e-learning continues to grow, the adaptive learning software market share is expected to rise where regions develop advanced learning technological systems.
One of the main driving factors of the Adaptive Learning Software Market is the increasing focus on individualized learning. There is growing understanding that institutions and organizations have to get adjusted to students and professionals and to their learning paces and styles to foster success. Adaptive learning software is the usage of Artificial Intelligence in identifying oriented learning that corresponds with general approaches to the learning process under conditions of inclusive learning and efficiency. Therefore, these discussed factors are main enablers for the adaptive learning software market growth.
In SDL approach, learning roles are shifted to the learner whereby they learn at their own discretion and convenience with or without supervision. This approach allows the learners to evaluate, monitor and supervise their learning activities. When using this approach, one of the technologies employed is the adaptive learning software that generates data on the learners as they undergo training modules or e-learning courses. In the traditional method, it becomes very hard to monitor the performance of each student. Through these platforms, the performance of students can be monitored online and made feedback to the existing learning setting of students.
Comprehensive Analysis of Adaptive learning software Market
The adaptive learning software market is responding quite an unprecedented rate of growth because of its market segmentation. This indicators growth in different regions by substituting the major forces of supply and demand which define the shape of local pharmacy benefit management market. Therefore, they are logically divided into 2 Segments, By Deployment Analysis and By End User Analysis. Based on the deployment, the adaptive learning software market has been segmented into on-premise and cloud. Of which, cloud segment is expected to show the highest CAGR, during the forecast period, owing to the low investment needed in installing cloud-based software. It offers flexibility and customization advantage in the least cost implication. For organizations that chose cloud software, they get to pay for only those services that they require. The on-premise segment is dominating the market in terms of market share due to security issues. Big attributes of on-premise platforms are security since the data is stored in the organization’s infrastructure. It does not even need to rely on a third-party company to own and control the structure. Depending on the end user the market is divided into K-12, Higher education and corporate. From the above, the k-12 segment has the highest adaptive learning software market share due to the growing use of effective and engaging eLearning software applications by teachers to make learning fun for children. Increasing demand for challenge-oriented games along with goal-oriented computer-based modules to enhance learner’s interest level is expected to fuel the growth of the global market. In addition, the corporate segment is likely to offer the highest growth rate throughout the forecast period. The use of this software in training and offering different instruction, training, and suggestions to the employees is somewhat fuelling the growth of the market. Also, this software contributes to growing the working rate of individuals, enhances the competency level of its employees, and contributes to making the learning process faster.
The market size in North America had a considerable presence in the global market. The increasing MNDAs and affiliations of digital education vendors and institutes for including new software in traditional education systems contribute significantly to the expansion of the market in North America.
The top players in the market play a crucial role in the hardware & software IT industry assuring industrial prospectus growth and setting market standards. These players include, Cerego (U.S.), Curriculum Associates, LLC (U.S.), D2L Corporation (Canada), Docebo (Canada), DREAMBOX LEARNING (U.S.), Fishtree (U.S.), Houghton Mifflin Harcourt (U.S.), Imagine Learning (U.S.), Kidaptive (U.S.), Knewton, Inc. (US), Macmillan (US), McGraw Hill (US), New Leaf Technologies (India), Paradiso (US), Pearson ( U.K.), Realizeit (Ireland), SAS (U.S.), Scootpad (U.S.), Smart Sparrow, Pty Ltd (Australia), Fuel Education LLC (U.S.), EdSurge Inc. (U.S.), Wiley (U.S.), aNewSpring (Zuid Holland), Intetics Inc. (U.S.), HCL Technologies Limited (India), intellAdapt (U.S.), Domoscio (France) and GradeSlam (Canada).
In February 2020, McGraw-Hill signed a partnership deal with Proctorio, an organization in the business of offering learning integrity solutions. The collaboration allowed McGraw-Hill to incorporate Proctorio’s remote proctoring and browser locking tools at the McGraw-Hill Connect Digital Learning Platform for college courses starting in Fall 2020 first.
Segmentation Table
ATTRIBUTE DETAILS
Study Period 2016–2027
Base Year 2019
Forecast Period 2020–2027
Historical Period 2016– 2018
Unit Value (USD billion)
Segmentation Deployment; End User and Region
By Deployment
On Premise
Cloud
By End User
K-12
Higher Education
Corporate
By Region
North America
US
By End User
Canada
By End User
Mexico
By End User
South America
Brazil
By End User
Argentina
By End User
Rest of South America
Europe
UK
By End User
Germany
By End User
France
By End User
Italy
By End User
Spain
By End User
Russia
By End User
Benelux
By End User
Nordics
By End User
Rest of Europe
The Middle East and Africa
Turkey
By End User
Israel
By End User
GCC
By End User
North Africa
By End User
South Africa
By End User
Rest of MEA
Asia Pacific
China
By End User
Japan
By End User
India
By End User
South Korea
By End User
ASEAN
By End User
Oceania
By End User
Rest of APAC
- 1. Introduction
- 1.1. Definition, By Segment
- 1.2. Research Methodology/Approach
- 1.3. Data Sources
- 2. Key Takeaways
- 3. Market Dynamics
- 3.1. Macro and Micro Economic Indicators
- 3.2. Drivers, Restraints, Opportunities and Trends
- 3.3. Impact of COVID-19
- 3.3.1. Short-term Impact
- 3.3.2. Long-term Impact
- 4. Competition Landscape
- 4.1. Business Strategies Adopted by Key Players
- 4.2. Consolidated SWOT Analysis of Key Players
- 4.3. PESTLE Analysis
- 4.4. Porter’s Five Force Analysis
- 4.5. Supply chain Analysis
- 5. Global Adaptive Learning Software Key Players Market Share Insights and Analysis, 2019
- 6. Key Market Insights and Strategic Recommendations
- 7. Primary Interviewee’s Key Responses
- 8. Companies Profiled (Covered for key 10 players only)
- 8.1. Overview
- 8.1.1. Key Management
- 8.1.2. Headquarters etc
- 8.2. Offerings/Business Segments
- 8.3. Key Details (Key details are subjected to data availability in public domain and/or on paid databases)
- 8.3.1. Employee Size
- 8.3.2. Key Financials
- 8.3.2.1. Past and Current Revenue
- 8.3.2.2. Gross Margin
- 8.3.2.3. Geographical Share
- 8.3.2.4. Business Segment Share
- 8.4. Recent Developments
- 9. Annexure / Appendix
- 9.1. Global Adaptive Learning Software Market Size Estimates and Forecasts (Quantitative Data), By Segments, 2016-2027
- 9.1.1. By Deployment (Value)
- 9.1.1.1. On Premise
- 9.1.1.2. Cloud
- 9.1.2. By End User (Value)
- 9.1.2.1. K-12
- 9.1.2.2. Higher Education
- 9.1.2.3. Corporate
- 9.1.3. By Region (Value)
- 9.1.3.1. North America
- 9.1.3.2. South America
- 9.1.3.3. Europe
- 9.1.3.4. Middle East & Africa
- 9.1.3.5. Asia Pacific
- 9.2. North America Adaptive Learning Software Market Size Estimates and Forecasts (Quantitative Data), By Segments, 2016-2027
- 9.2.1. By Deployment (Value)
- 9.2.1.1. On Premise
- 9.2.1.2. Cloud
- 9.2.2. By End User (Value)
- 9.2.2.1. K-12
- 9.2.2.2. Higher Education
- 9.2.2.3. Corporate
- 9.2.3. By Country (Value)
- 9.2.3.1. United States
- 9.2.3.1.1. By End User
- 9.2.3.1.1.1. K-12
- 9.2.3.1.1.2. Higher Education
- 9.2.3.1.1.3. Corporate
- 9.2.3.2. Canada
- 9.2.3.2.1. By End User
- 9.2.3.2.1.1. K-12
- 9.2.3.2.1.2. Higher Education
- 9.2.3.2.1.3. Corporate
- 9.2.3.3. Mexico
- 9.2.3.3.1. By End User
- 9.2.3.3.1.1. K-12
- 9.2.3.3.1.2. Higher Education
- 9.2.3.3.1.3. Corporate
- 9.3. South America Adaptive Learning Software Market Size Estimates and Forecasts (Quantitative Data), By Segments, 2016-2027
- 9.3.1. By Deployment (Value)
- 9.3.1.1. On Premise
- 9.3.1.2. Cloud
- 9.3.2. By End User (Value)
- 9.3.2.1. K-12
- 9.3.2.2. Higher Education
- 9.3.2.3. Corporate
- 9.3.3. By Country (Value)
- 9.3.3.1. Brazil
- 9.3.3.1.1. By End User
- 9.3.3.1.1.1. K-12
- 9.3.3.1.1.2. Higher Education
- 9.3.3.1.1.3. Corporate
- 9.3.3.2. Argentina
- 9.3.3.2.1. By End User
- 9.3.3.2.1.1. K-12
- 9.3.3.2.1.2. Higher Education
- 9.3.3.2.1.3. Corporate
- 9.3.3.3. Rest of South America
- 9.4. Europe Adaptive Learning Software Market Size Estimates and Forecasts (Quantitative Data), By Segments, 2016-2027
- 9.4.1. By Deployment (Value)
- 9.4.1.1. On Premise
- 9.4.1.2. Cloud
- 9.4.2. By End User (Value)
- 9.4.2.1. K-12
- 9.4.2.2. Higher Education
- 9.4.2.3. Corporate
- 9.4.3. By Country (Value)
- 9.4.3.1. United Kingdom
- 9.4.3.1.1. By End User
- 9.4.3.1.1.1. K-12
- 9.4.3.1.1.2. Higher Education
- 9.4.3.1.1.3. Corporate
- 9.4.3.2. Germany
- 9.4.3.2.1. By End User
- 9.4.3.2.1.1. K-12
- 9.4.3.2.1.2. Higher Education
- 9.4.3.2.1.3. Corporate
- 9.4.3.3. France
- 9.4.3.3.1. By End User
- 9.4.3.3.1.1. K-12
- 9.4.3.3.1.2. Higher Education
- 9.4.3.3.1.3. Corporate
- 9.4.3.4. Italy
- 9.4.3.4.1. By End User
- 9.4.3.4.1.1. K-12
- 9.4.3.4.1.2. Higher Education
- 9.4.3.4.1.3. Corporate
- 9.4.3.5. Spain
- 9.4.3.5.1. By End User
- 9.4.3.5.1.1. K-12
- 9.4.3.5.1.2. Higher Education
- 9.4.3.5.1.3. Corporate
- 9.4.3.6. Russia
- 9.4.3.6.1. By End User
- 9.4.3.6.1.1. K-12
- 9.4.3.6.1.2. Higher Education
- 9.4.3.6.1.3. Corporate
- 9.4.3.7. Benelux
- 9.4.3.7.1. By End User
- 9.4.3.7.1.1. K-12
- 9.4.3.7.1.2. Higher Education
- 9.4.3.7.1.3. Corporate
- 9.4.3.8. Nordics
- 9.4.3.8.1. By End User
- 9.4.3.8.1.1. K-12
- 9.4.3.8.1.2. Higher Education
- 9.4.3.8.1.3. Corporate
- 9.4.3.9. Rest of Europe
- 9.5. Middle East & Africa Adaptive Learning Software Market Size Estimates and Forecasts (Quantitative Data), By Segments, 2016-2027
- 9.5.1. By Deployment (Value)
- 9.5.1.1. On Premise
- 9.5.1.2. Cloud
- 9.5.2. By End User (Value)
- 9.5.2.1. K-12
- 9.5.2.2. Higher Education
- 9.5.2.3. Corporate
- 9.5.3. By Country (Value)
- 9.5.3.1. Turkey
- 9.5.3.1.1. By End User
- 9.5.3.1.1.1. K-12
- 9.5.3.1.1.2. Higher Education
- 9.5.3.1.1.3. Corporate
- 9.5.3.2. Israel
- 9.5.3.2.1. By End User
- 9.5.3.2.1.1. K-12
- 9.5.3.2.1.2. Higher Education
- 9.5.3.2.1.3. Corporate
- 9.5.3.3. GCC
- 9.5.3.3.1. By End User
- 9.5.3.3.1.1. K-12
- 9.5.3.3.1.2. Higher Education
- 9.5.3.3.1.3. Corporate
- 9.5.3.4. North Africa
- 9.5.3.4.1. By End User
- 9.5.3.4.1.1. K-12
- 9.5.3.4.1.2. Higher Education
- 9.5.3.4.1.3. Corporate
- 9.5.3.5. South Africa
- 9.5.3.5.1. By End User
- 9.5.3.5.1.1. K-12
- 9.5.3.5.1.2. Higher Education
- 9.5.3.5.1.3. Corporate
- 9.5.3.6. Rest of MEA
- 9.6. Asia Pacific Adaptive Learning Software Market Size Estimates and Forecasts (Quantitative Data), By Segments, 2016-2027
- 9.6.1. By Deployment (Value)
- 9.6.1.1. On Premise
- 9.6.1.2. Cloud
- 9.6.2. By End User (Value)
- 9.6.2.1. K-12
- 9.6.2.2. Higher Education
- 9.6.2.3. Corporate
- 9.6.3. By Country (Value)
- 9.6.3.1. China
- 9.6.3.1.1. By End User
- 9.6.3.1.1.1. K-12
- 9.6.3.1.1.2. Higher Education
- 9.6.3.1.1.3. Corporate
- 9.6.3.2. India
- 9.6.3.2.1. By End User
- 9.6.3.2.1.1. K-12
- 9.6.3.2.1.2. Higher Education
- 9.6.3.2.1.3. Corporate
- 9.6.3.3. Japan
- 9.6.3.3.1. By End User
- 9.6.3.3.1.1. K-12
- 9.6.3.3.1.2. Higher Education
- 9.6.3.3.1.3. Corporate
- 9.6.3.4. South Korea
- 9.6.3.4.1. By End User
- 9.6.3.4.1.1. K-12
- 9.6.3.4.1.2. Higher Education
- 9.6.3.4.1.3. Corporate
- 9.6.3.5. ASEAN
- 9.6.3.5.1. By End User
- 9.6.3.5.1.1. K-12
- 9.6.3.5.1.2. Higher Education
- 9.6.3.5.1.3. Corporate
- 9.6.3.6. Oceania
- 9.6.3.6.1. By End User
- 9.6.3.6.1.1. K-12
- 9.6.3.6.1.2. Higher Education
- 9.6.3.6.1.3. Corporate
- 9.6.3.7. Rest of Asia Pacific
- 10. Companies Analyzed (In order to estimate the market size and/or understanding the market ecosystem) (Note that the purpose of the below list is to highlight the exhaustiveness of coverage. Only top 10 players are profiled in the scope. Additionally, we are open to profile additional company(s) on specific request)
- 10.1. Cerego
- 10.2. Curriculum Associates, LLC.
- 10.3. D2L Corporation
- 10.4. Docebo
- 10.5. DREAMBOX LEARNING
- 10.6. Fishtree
- 10.7. Houghton Mifflin Harcourt
- 10.8. Imagine Learning
- 10.9. Kidaptive
- 10.10. Knewton, Inc.
- 10.11. Macmillan
- 10.12. McGraw Hill
- 10.13. New Leaf Technologies
- 10.14. Paradiso
- 10.15. Pearson
- 10.16. Realizeit
- 10.17. SAS
- 10.18. Scootpad
- 10.19. Smart Sparrow, Pty Ltd
- 10.20. Fuel Education LLC
- 10.21. EdSurge Inc.
- 10.22. Wiley
- 10.23. aNewSpring
- 10.24. Intetics Inc.
- 10.25. HCL Technologies Limited
- 10.26. intellAdapt
- 10.27. Domoscio
- 10.28. GradeSlam
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