In this report, LP Information studies the present scenario (with the base year being 2017) and the growth prospects of global Adaptive Learning Software market for 2018-2023.
Adaptive learning is an educational technique which uses computers as interactive teaching devices rendering to the unique needs of each learner. It adapts the presentation of educational material according to the students’ learning needs, as shown by their responses to questions and tasks. Adaptive learning systems are being used as online courses and within blended learning frameworks.
Over the next five years, LPI(LP Information) projects that Adaptive Learning Software will register a xx% CAGR in terms of revenue, reach US$ xx million by 2023, from US$ xx million in 2017.
This report presents a comprehensive overview, market shares and growth opportunities of Adaptive Learning Software market by product type, application, key companies and key regions.
To calculate the market size, LP Information considers value generated from the sales of the following segments:
Segmentation by product type:
On-Premise
Cloud Based
Segmentation by application:
Ed-tech Companies
Education Institutes
We can also provide the customized separate regional or country-level reports, for the following regions:
Americas
United States
Canada
Mexico
Brazil
APAC
China
Japan
Korea
Southeast Asia
India
Australia
Europe
Germany
France
UK
Italy
Russia
Spain
Middle East and Africa
Egypt
South Africa
Israel
Turkey
GCC Countries
The report also presents the market competition landscape and a corresponding detailed analysis of the major players in the market. The key players covered in this report:
SAP
D2L
Dream Box Learning
Knewton
Smart Sparrow
EdSurge
Docebo
…
In addition, this report discusses the key drivers influencing market growth, opportunities, the challenges and the risks faced by key players and the market as a whole. It also analyzes key emerging trends and their impact on present and future development.
Research objectives
To study and analyze the global Adaptive Learning Software market size by key regions/countries, product type and application, history data from 2013 to 2017, and forecast to 2023.
To understand the structure of Adaptive Learning Software market by identifying its various subsegments.
Focuses on the key global Adaptive Learning Software players, to define, describe and analyze the value, market share, market competition landscape, SWOT analysis and development plans in next few years.
To analyze the Adaptive Learning Software with respect to individual growth trends, future prospects, and their contribution to the total market.
To share detailed information about the key factors influencing the growth of the market (growth potential, opportunities, drivers, industry-specific challenges and risks).
To project the size of Adaptive Learning Software submarkets, with respect to key regions (along with their respective key countries).
To analyze competitive developments such as expansions, agreements, new product launches and acquisitions in the market.
To strategically profile the key players and comprehensively analyze their growth strategies.
SECONDARY RESEARCH
Secondary Research Information is collected from a number of publicly available as well as paid databases. Public sources involve publications by different associations and governments, annual reports and statements of companies, white papers and research publications by recognized industry experts and renowned academia etc. Paid data sources include third party authentic industry databases.
PRIMARY RESEARCH
Once data collection is done through secondary research, primary interviews are conducted with different stakeholders across the value chain like manufacturers, distributors, ingredient/input suppliers, end customers and other key opinion leaders of the industry. Primary research is used both to validate the data points obtained from secondary research and to fill in the data gaps after secondary research.
MARKET ENGINEERING
The market engineering phase involves analyzing the data collected, market breakdown and forecasting. Macroeconomic indicators and bottom-up and top-down approaches are used to arrive at a complete set of data points that give way to valuable qualitative and quantitative insights. Each data point is verified by the process of data triangulation to validate the numbers and arrive at close estimates.
EXPERT VALIDATION
The market engineered data is verified and validated by a number of experts, both in-house and external.
REPORT WRITING/ PRESENTATION
After the data is curated by the mentioned highly sophisticated process, the analysts begin to write the report. Garnering insights from data and forecasts, insights are drawn to visualize the entire ecosystem in a single report.
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