According to data from Pi Datametrics, the search term related to E-learning that saw the biggest growth on Google in the UK from 2018 to 2020 was "physics gcse online". "Free online education course" saw the second highest increase, followed by "free teaching course online".

E-learning market has seen year-on-year growth since 2015

As of August 2019 - shortly before the Coronavirus pandemic hit Europe, sales of e-learning material was at an all-time high in the UK with ** percent of respondents surveyed saying they had made purchases under the category in the past year. In 2011 this figure stood at a mere * percent. Despite this, most working adults questioned during the same year still said that they preferred to learn with others in a classroom setting, given the choice. Among all responses, online and online group learning (for example via webinars) were the two least popular methods selected.

Learning has been helping young adults cope during lockdown

A survey conducted during the Coronavirus lockdown in 2020 found that after face-to-face calls, watching TV/films and exercising, learning new skills was one of the most vital activities in helping young adults deal with their mental health and wellbeing at home – more helpful than reading or gaming. While nearly half of those using general online learning resources were aged between 16 to 24 years old, the main consumers of e-learning courses were adults aged between 25 and 34. Overall, more men tended to use the internet for learning compared to women.

According to data from Pi Datametrics, the search term related to electricals that saw the biggest year-on-year growth on Google in the UK from January to April 2020 compared to the same period in 2019 was "free online learning". "Free online learning" saw the second highest increase, followed by "security training courses".

The statistic describes the annual growth of the revenue generated by online education in China from 2011 to 2018, with forecasts up to 2020. In 2019, China's online education market was estimated to grow by ** percent compared to the previous year.

Snapshot img

India Online Education Market Size 2025-2029

The India online education market size is forecast to increase by USD 8.53 billion at a CAGR of 29% between 2024 and 2029.

The India Online Education Market is segmented by end-user (higher education, K-12), product (content, services), and geography (APAC: India). This segmentation reflects the market's rapid growth, driven by increasing demand for digital content and services in higher education and K-12 sectors, fueled by widespread internet access, affordable devices, and a growing emphasis on skill development and remote learning across India.
The market is witnessing significant growth, driven by the increasing focus on skill development and employment. With the emergence of cloud computing, online learning platforms have become more accessible and convenient, catering to the needs of a diverse student population. However, the market faces challenges in providing an adequate learning environment and infrastructure, which can hinder the quality of education and student engagement. The demand for online education in India is fueled by the need for upskilling and reskilling in a rapidly evolving job market. Cloud computing has enabled the delivery of education through digital platforms, making it accessible from anywhere, at any time.
This flexibility is particularly valuable for students in India, where geographical barriers and limited resources can often hinder access to quality education. Despite these opportunities, the market faces challenges in providing an optimal learning environment and infrastructure. The lack of reliable internet connectivity and limited access to devices can hinder the student experience, potentially impacting engagement and learning outcomes. Addressing these challenges will be crucial for companies seeking to capitalize on the market's growth potential and deliver high-quality online education solutions to students in India.

What will be the size of the India Online Education Market during the forecast period?

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The Indian online education market is experiencing dynamic shifts, with various technologies and methodologies shaping its landscape. Interactive whiteboards and edtech accelerators are transforming classroom instruction, enabling more engaging learning experiences. AI-powered tutoring systems and the flipped classroom methodology are driving personalized instruction, catering to students' unique needs. Virtual labs and adaptive testing are revolutionizing science education, making it more accessible and effective. Synchronous learning and project-based learning are fostering real-time collaboration and problem-solving skills. Self-paced learning and gamified platforms are catering to diverse learning styles and keeping students engaged. SAAS education platforms like Microsoft Teams and Google Classroom are streamlining administrative tasks and enhancing communication.
Edtech integrators are bridging the gap between traditional and digital learning, while the Khan Academy model sets new standards for free education. Blockchain in education is ensuring data security and transparency, with digital badges and learning communities fostering lifelong learning and professional development. Asynchronous learning and social learning tools are enabling flexible and collaborative learning environments, making education more accessible and inclusive.

How is this market segmented?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

End-user

  Higher education
  K-12


Product

  Content
  Services


Geography

  APAC

    India

By End-user Insights

The higher education segment is estimated to witness significant growth during the forecast period.

The Indian online education market is experiencing significant growth due to the increasing demand for equitable education opportunities. Video lectures, educational apps, and virtual classrooms offer flexible learning solutions, enabling students to access quality education regardless of their location or time constraints. The government's Digital India Initiative, under the Ministry of Human Resource Development (MHRD) and National Mission on Education through Information and Communication Technology (NMEICT), is promoting online education as a viable alternative to traditional methods. Professional development courses, test preparation, and corporate training are popular choices in this space, with many institutions offering freemium models to attract students.

Learning analytics and personalized learning paths are essential features that enhance the learning exp

This statistic shows the annual growth rate of the online education market in China from 2017 to 2020, with forecasts until 2024. After **** percent growth in 2020, market growth is forecast to slow down in the following years.

Snapshot img

The online higher education market share in the US is expected to increase by USD 33.35 billion from 2021 to 2026, and the market’s growth momentum will accelerate at a CAGR of 19.82%.

This online higher education market in the US research report provides valuable insights on the post COVID-19 impact on the market, which will help companies evaluate their business approaches. Furthermore, this report extensively covers online higher education market in the US segmentation by subjects (commerce and management, STEM, Arts, and others) and courses (non-degree courses and degree courses). The online higher education market in the US report also offers information on several market vendors, including American Public Education Inc., Adtalem Global Education Inc., Apollo Education Group Inc., Graham Holdings Co., Grand Canyon Education Inc., ITT Educational Services Inc., LINCOLN EDUCATIONAL SERVICES Corp., Perdoceo Education Corp., Strategic Education Inc., and Zovio Inc. among others.

What will the Online Higher Education Market Size in the US be During the Forecast Period?

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Online Higher Education Market in the US: Key Drivers, Trends, and Challenges

The collaborations between enterprises and educational institutions is notably driving the online higher education market growth in the US, although factors such as designing e-learning courses may impede the market growth. Our research analysts have studied the historical data and deduced the key market drivers and the COVID-19 pandemic impact on the online higher education industry in the US. The holistic analysis of the drivers will help in deducing end goals and refining marketing strategies to gain a competitive edge.

Key Online Higher Education Market Driver in the US

The collaborations between enterprises and educational institutions is one of the key drivers supporting the online higher education market growth in the US. Although such collaborations can take numerous forms, the most common are training, partnerships, or R&D partnerships. For instance, IBM-Charlotte was designed by the University of North Carolina-Charlotte (UNC-Charlotte) and IBM with the aim of enhancing the university’s technical vitality, expanding its local personnel resource bank, and ultimately offering IBM's technical communicators a way of earning degrees in their field of work. For UNC-Charlotte, the relationship with IBM gave its developing Technical Communication program community support and visibility and simultaneously provided faculty with research opportunities and practical experience at the workplace. Such collaborations are driving the growth of the online higher education market in the US during the forecast period.

Key Online Higher Education Market Trend in the US

Increased use of wearable gadgets is another factor supporting the online higher education market growth in the US. Technologies such as augmented reality (AR) are also changing the learning experience of participants. 3D simulations and scenarios that are developed using wearable technology devices give users a chance to learn in different learning environments. Moreover, the theoretical explanation of various concepts and step-by-step training on operations in an organization, followed by familiarizing students with on-the-floor working environments, are time-consuming. Therefore, wearable technology devices can help universities or educational institutions to engage with students directly on the floor. This reduces the duration and makes students more comfortable with online learning. Thus, the affordable prices of wearable gadgets will foster their greater adoption, in turn fostering the growth of the online higher education market in the US

Key Online Higher Education Market Challenge in the US

Designing e-learning courses is one of the factors hindering the online higher education market growth in the US. A significant amount of time, money, and resources are needed for developing the content for online courses. On average, moderately interactive online content takes about 90-240 hours to develop and costs developers approximately $10,000 per produced hour for moderate-level content. Similarly, the cost keeps rising as the complexity of the content increases. The major factors impacting the cost incurred on creating online education content are the resources needed, the state of the source content, the elements embedded in the online content, and the interactivity and instructional complexities involved. Therefore, this is a challenging factor for the growth of the online higher education market in the US.

This online higher education market in the US analysis report also provides detailed information on other upcoming trends and challenges that will have a far-reaching

Abstract

Opportunity-focused, high-growth entrepreneurship and science-led innovation are crucial for continued economic growth and productivity. Working in these fields offers the opportunity for rewarding and high-paying careers. However, the majority of youth in developing countries do not consider either as job options, affecting their choices of what to study. Youth may not select these educational and career paths due to lack of knowledge, lack of appropriate skills, and lack of role models. We provide a scalable approach to overcoming these constraints through an online education course for secondary school students that covers entrepreneurial soft skills, scientific methods, and interviews with role models.

The study comprises three experimental trials provided Before and during COVID-19 pandemic in different regions of Ecuador. This catalog entry includes data from Experiment 3: Coastal Educational Regime (Régimen Costa) 2020/2021. The data from the other two experiments are also available in the catalog.

Experiment 3: Coastal Educational Regime (Régimen Costa) 2020/2021

A randomized experiment conducted in high schools in Ecuador as rapid fire response to the hurdles of COVID-19 for the Coastal Educational regimes schools (Régimen Costa); Students finish the program in December 2020). The intervention is an online education course that covers entrepreneurial soft skills, scientific methods, and interviews with role models. This course is taken by students at home during the COVID-19 pandemic under teachers’ supervision. We work mostly with 14-22-year-old students (16,441 students) in 598 schools assigned to the program. We randomly assign schools either to treatment (and receiving the entrepreneurship courses online), or placebo-control (receiving a placebo treatment of online courses from standard curricula) groups. We also cross-randomize the role models and evaluate set of nimble interventions to increase take-up. The details of intervention can be found in AEA registry: Asanov, Igor and David McKenzie. 2021. Scaling up virtual learning of online learning in high schools. AEA RCT Registry. March 23 Merged datasets from the baseline, midline, endline survey for each experiment administrated through online learning platform in school during normal educational hours before COVID-19 pandemic or at student’s home during COVID-19 pandemic are documented here. The detailed information about the questioner and each item can be found in the codebooks (Baseline 1, Baseline 2, Midline, Endline 1, Endline 2) for corresponding experiments.

Geographic coverage

Experiment 3: Coastal Educational Regime (Régimen Costa) 2020/2021 We cover students of last year of education in School K12 of technical specialization (Bachillerato técnico) that study in Coastal Educational Regime (Régimen Costa) 2020/2021, suppose to finish their education in school in March 2021 and we capable to register on the online platform. The schools in highlands educational regime covered in this experiment scatter over the next educational zones 1, 2, 3, 4, 5, 6, 7, 8, 9.
Taken together in the experiment 2,3 we offered the program across all Ecuador to schools that have technical specialization track.

Analysis unit

Student

Kind of data

Sample survey data [ssd]

Sampling procedure

All students in selected schools who were present in classes filled out the baseline questionnaire

Mode of data collection

Internet [int]

Research instrument

Questionnaires We execute three main sets of questioners. A. Internet (Online Based survey)

The survey consists of a multi-topic questionnaire administered to the students through online learning platform in school during normal educational hours before COVID-19 pandemic or at home during the COVID-19 pandemic. We collect next information: 1. Subject specific knowledge tests. Spanish, English, Statistics, Personal Initiative (only endline), Negotiations (only endline). 2. Career intentions, preferences, beliefs, expectations, and attitudes. STEM and entrepreneurial intentions, preferences, beliefs, expectations, and attitudes. 3. Psychological characteristics. Personal Initiative, Negotiations, General Cognitions (General Self-Efficacy, Youth Self-Efficacy, Perceived Subsidiary Self-Efficacy Scale, Self-Regulatory Focus, Short Grit Scale), Entrepreneurial Cognitions (Business Self-Efficacy, Identifying Opportunities, Business Attitudes, Social Entrepreneurship Standards). 4. Behavior in (incentivized) games: Other-regarding preferences (dictator game), tendency to cooperate (Prisoners Dilemma), Perseverance (triangle game), preference for honesty, creativity (unscramble game). 5. Other background information. Socioeconomic level, language spoken, risk and time preferences, trust level, parents background, big-five personality traits of student, cognitive abilities. Background information (5) collected only at the baseline. B. First follow-up Phone-based Survey Zone 2, Summer (Phone Based). The survey replicates by phone shorter version of the internet-based survey above. We collect next information: 1. Subject specific knowledge tests.
2. Career intentions, preferences, beliefs, expectations, and attitudes. 3. Psychological characteristics

C. (Second) Follow-up Phone-Based Survey, Winter, Zone 2, Highlands Educational Regime.

We execute multi-topic questionnaire by phone to capture the first life-outcomes of students who finished the school. We collect next information:

1. Life Outcome 1- Education. The set of questions that aims to measure the learning success, career/study intentions, propensity to plan and approach others with studying tasks, entrepreneurial intentions.
2. Life Outcome 2- Labor. The set of questions that aims to measure employment status and income, job searching behavior, time devoted for working/business, salary expectations and knowledge about the careers, self-initiated contribution to the family.
3. Personal Initiative/Negotiations related and other measures. The set of questions that aim to measure level of personal initiative, negotiation strategies, pregnancy rate, gender stereotypes, math/STEM self-efficacy, gender attitudes, parent-student communication effects.

Cleaning operations

Data Editing A. Internet, Online-based surveys. We extracted the raw data generated on online platform from each experiment and prepared it for research purposes. We made several pre-processing steps of data: 1. We transform the raw data generated on platform in standard statistical software (R/STATA) readable format. 2. We extracted the answer for each item for each student for each survey (Baseline, Midline, Endline). 3. We cleaned duplicated students and duplicated answers for each item in each survey based on administrative data, performance and information given by students on platform. 4. In case of baseline survey, we standardized items/scales but also kept the raw items.

B. Phone-based surveys. The phone-based surveys are collected with help of advanced CATI kit. It contains all cases (attempts to call) and indication if the survey was effective. The data is cleaned to be ready for analysis. The data is anonymized but contains unique anonymous student id for merging across datasets.

Snapshot img

E-learning IT Infrastructure Market Size 2024-2028

The e-learning IT infrastructure market size is forecast to increase by USD 344.85 million at a CAGR of 17.4% between 2023 and 2028.

The emergence of virtual schools is a key driver of the e-learning IT infrastructure market. As educational institutions transition to fully online models, the demand for robust IT infrastructure grows. Virtual schools require scalable, secure, and efficient systems to support a seamless learning experience for students and educators, leading to increased investments in e-learning.
In the APAC region, the market is poised for significant expansion due to the area's rapid technological advancements and high Internet penetration rates. As more students and institutions in APAC adopt online education, the need for advanced IT infrastructure grows, fueling market growth. This trend is expected to continue as digital education becomes more widespread across the region

What will be the Size of the Market During the Forecast Period?

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E-learning, a form of education and corporate training delivered via electronic technologies, has become an integral part of the modern learning landscape. The infrastructure that supports e-learning encompasses various components, including hardware infrastructure, software, and networking equipment. Hardware infrastructure is the foundation of e-learning IT infrastructure. Servers and storage systems are crucial elements in this category. Servers facilitate the processing and delivery of e-learning content, while storage systems ensure the availability and accessibility of vast amounts of data. Software applications, such as learning management systems (LMS) and video conferencing tools, play a pivotal role in e-learning.

How is this market segmented and which is the largest segment?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Component

  Connectivity
  Hardware
  Software


End-user

  Academic
  Enterprise
  Others


Geography

  North America

    Canada
    US


  APAC

    China


  Europe

    Germany
    UK


  Middle East and Africa



  South America

By Component Insights

The connectivity segment is estimated to witness significant growth during the forecast period.

In the modern educational landscape, e-learning has become an essential component for both private and public schools. To deliver seamless and uninterrupted learning experiences, schools and e-learning companies require reliable connectivity infrastructure. This infrastructure facilitates the creation, distribution, and consumption of e-learning content on various connected devices, including PCs, tablets, smartphones, and other mobile devices. Key factors influencing the adoption of connectivity infrastructure in the education sector include the number of simultaneous network users, the reliability of network service providers, and IT security policies. The growing use of e-learning tools and techniques, such as smart classrooms, webinars, language learning market, and medical advice, necessitates a strong connectivity infrastructure.

Moreover, the integration of cloud infrastructure, home security systems, energy use monitoring, and language translation tools adds to the complexity of the e-learning ecosystem. A stable connectivity infrastructure is crucial to ensure the smooth delivery of e-learning services, enabling students and teachers to access resources from anywhere, at any time. The increasing demand for e-learning services and the need for uninterrupted connectivity have led to substantial investments in the development and maintenance of connectivity infrastructure. In conclusion, the e-learning market's growth is significantly influenced by the availability and reliability of connectivity infrastructure. Schools and educational institutions must ensure a stable and secure network to provide effective e-learning services, enabling students to learn from anywhere, anytime, and on any device.

Get a glance at the market report of share of various segments Request Free Sample

The connectivity segment was valued at USD 88.02 million in 2018 and showed a gradual increase during the forecast period.

Regional Analysis

APAC is estimated to contribute 39% to the growth of the global market during the forecast period.

Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

For more insights on the market share of various regions, Request Free Sample

The market in North America is poised for expansion due to the region's technological advancements and high Internet penetration rates. With the increasing adoption of cloud c

In 2023, seven percent of students strongly agreed that it was worthwhile for borrowers to take out loans for education after high school that is a predominantly online program in the United States. In comparison, 12 percent strongly disagreed with this belief.

The global E-learning market was valued at USD 214.26 billion in 2021 and is expected to grow at a CAGR of 20.5% during the forecast period.

The global e-learning market size reached USD 342.4 Billion in 2024. Looking forward, IMARC Group expects the market to reach USD 682.3 Billion by 2033, exhibiting a growth rate (CAGR) of 8.0% during 2025-2033. North America currently dominates the market, holding a market share of over 35.0% in 2024. The regional market is principally propelled by magnified internet penetration, cutting-edge technological infrastructure, and robust implementation of digital learning solutions across both corporate and educational segments.

IMARC Group provides an analysis of the key trends in each segment of the global e-learning market, along with forecast at the global, regional, and country levels from 2025-2033. The market has been categorized based on technology, provider, and application.

The experimental study was conducted at the Moscow State University of Psychology and Education (MSUPE) in the framework of the research project “Digital Technologies in Higher Education: Development of Technology for Individualizing Learning Using E-Courses” in 2019 - 2021. The project design was approved by the MSUPE Scientific Expert Council and by the MSUPE Scientific Council.Datasets and main research results are presented. MSUPE students participated in e-courses (ECs) in mathematical methods in psychology (MMinP) using blended learning (BL) format in the fall semester 2019 - spring semester 2020 or online learning (OL) format in the fall semester 2020.The data and results of comparative analysis of the attitudes of Russian Federation (RF) university teachers towards using of digital educational technologies (DET) in higher education (HE) are presented.Scale for assessing university digital educational environment (AUDEE Scale) was developed and validated

Snapshot img

E-Learning Market Size 2025-2029

The e-learning market size is forecast to increase by USD 326.9 billion, at a CAGR of 18.9% between 2024 and 2029.

The market is experiencing significant growth and transformation, driven by the increasing adoption of technology in the academic sector. This shift is leading to the integration of advanced learning tools and techniques, such as microlearning, to enhance the overall learning experience. Furthermore, the trend towards in-house content development is gaining momentum, allowing organizations to customize their training programs and maintain control over their learning resources. However, this dynamic market is not without challenges. The proliferation of free and low-cost learning resources available online poses a threat to the commercial E-Learning industry. Additionally, ensuring the accessibility and compatibility of E-Learning content across various devices and platforms remains a significant challenge.
To capitalize on market opportunities and navigate these challenges effectively, companies must focus on delivering high-quality, customizable, and accessible learning solutions. By staying abreast of technological advancements and addressing the evolving needs of learners, organizations can differentiate themselves in the competitive E-Learning landscape.

What will be the Size of the E-Learning Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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In the ever-evolving the market, dynamics continue to unfold as technology advances and learning needs evolve. Personalized learning experiences, enabled by adaptive technology, bridge the skill gap and cater to diverse learner needs. Augmented reality and virtual reality enhance immersive learning, while mobile learning and language learning cater to a global audience. User interface and data security ensure a seamless learning experience, safeguarding sensitive information. Interactive learning and machine learning facilitate engaging and effective instruction. Adult learning, certification programs, and soft skills training prioritize professional development. Instructional design, curriculum development, and learner engagement strategies are refined, driving better learning outcomes.

Virtual classroom and live streaming facilitate real-time interaction, while learning management systems and content delivery networks streamline content access. Blended learning and talent management solutions integrate e-learning with traditional training methods. Learning analytics and artificial intelligence optimize personalized recommendations and adaptive learning paths. Compliance training, knowledge management, and privacy regulations ensure a secure and effective learning environment. E-learning content and online courses cater to various sectors, including K-12 education, higher education, and corporate training. Learning objectives and technical skills training are tailored to meet specific industry requirements. The ongoing integration of these technologies and trends shapes the e-learning landscape, ensuring continuous growth and innovation.

How is this E-Learning Industry segmented?

The e-learning industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.End-userHigher educationCorporateK-12DeploymentOn-premisesCloudProviderContentServiceTypeCustom E-LearningResponsive E-LearningGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyUKMiddle East and AfricaEgyptKSAOmanUAEAPACChinaIndiaJapanSouth AmericaArgentinaBrazilRest of World (ROW)

By End-user Insights

The higher education segment is estimated to witness significant growth during the forecast period.

The market dynamics are shaped by the increasing adoption of technology in education, with cloud-based Learning Management Systems (LMSs) like Talent LMS gaining popularity in higher education institutions. These platforms facilitate the delivery and tracking of online education and training. In K-12 education, Bring Your Own Device (BYOD) policies simplify technology implementation for students. Universities, such as NIIT, Massachusetts Institute of Technology, and Yale University, develop e-learning content using authoring tools or source it from companies. Skill development and certification programs are key components of e-learning, with personalized recommendations and adaptive learning enhancing the user experience.

Instructional design, curriculum development, and learner engagement are crucial elements of effective e-learning. Virtual classrooms and live streaming enable real-time interaction between learners and instructors. Immersive learning experiences, including virtual reality and augme

Abstract

Opportunity-focused, high-growth entrepreneurship and science-led innovation are crucial for continued economic growth and productivity. Working in these fields offers the opportunity for rewarding and high-paying careers. However, the majority of youth in developing countries do not consider either as job options, affecting their choices of what to study. Youth may not select these educational and career paths due to lack of knowledge, lack of appropriate skills, and lack of role models. We provide a scalable approach to overcoming these constraints through an online education course for secondary school students that covers entrepreneurial soft skills, scientific methods, and interviews with role models.

The study comprises three experimental trials provided Before and during COVID-19 pandemic in different regions of Ecuador. This catalog entry includes data from Experiment 2: Highlands Educational Regime (Régimen Sierra-Amazonía) 2020. The data from the other two experiments are also available in the catalog.

Experiment 2: Highlands Educational Regime (Régimen Sierra-Amazonía) 2020 In course of Showing Life Opportunities project we provided a randomized experiment in Ecuador as rapid fire response to the hurdles of COVID-19 for the Highlands Educational regimes schools (Régimen Sierra 2020); Students finish the program in July 2020. The intervention is an online education course that covers entrepreneurial soft skills, scientific methods, and interviews with role models. This course is taken by students at home during the COVID-19 pandemic under teachers’ supervision. We work mostly with 14-22-year-old students (14,451 students) in 416 schools assigned to the program. We randomly assign schools either to treatment (and receiving the entrepreneurship courses online), or placebo-control (receiving a placebo treatment of online courses from standard curricula) groups. We also cross-randomize the role models and evaluate set of nimble interventions to increase take-up. The details of intervention can be found in AEA registry: Asanov, Igor and David McKenzie. 2021. Scaling up virtual learning of online learning in high schools. AEA RCT Registry. March 23. cross-randomize schools to a role model treatment of interviews with successful scientists and entrepreneurs. In addition, we provide information about career options.

Geographic coverage

Experiment 2: Highlands Educational Regime (Régimen Sierra-Amazonía) 2020 We cover students of last year of education in SchoolK12 of technical specialization (Bachillerato técnico) that study in Highlands Educational Regime (Régimen Sierra-Amazonía), suppose to finish in education in school in July 2020, and we capable to register on the online platform. The schools in highlands educational regime covered in this experiment scatter over the next educational zones 1,2,3, and 5,6,7, and 9.

Analysis unit

Student

Kind of data

Sample survey data [ssd]

Sampling procedure

All students in selected schools who were present in classes filled out the baseline questionnaire

Mode of data collection

Internet [int]

Research instrument

Questionnaires We execute three main sets of questioners. A. Internet (Online Based survey)

The survey consists of a multi-topic questionnaire administered to the students through online learning platform in school during normal educational hours before COVID-19 pandemic or at home during the COVID-19 pandemic. We collect next information: 1. Subject specific knowledge tests. Spanish, English, Statistics, Personal Initiative (only endline), Negotiations (only endline). 2. Career intentions, preferences, beliefs, expectations, and attitudes. STEM and entrepreneurial intentions, preferences, beliefs, expectations, and attitudes. 3. Psychological characteristics. Personal Initiative, Negotiations, General Cognitions (General Self-Efficacy, Youth Self-Efficacy, Perceived Subsidiary Self-Efficacy Scale, Self-Regulatory Focus, Short Grit Scale), Entrepreneurial Cognitions (Business Self-Efficacy, Identifying Opportunities, Business Attitudes, Social Entrepreneurship Standards). 4. Behavior in (incentivized) games: Other-regarding preferences (dictator game), tendency to cooperate (Prisoners Dilemma), Perseverance (triangle game), preference for honesty, creativity (unscramble game). 5. Other background information. Socioeconomic level, language spoken, risk and time preferences, trust level, parents background, big-five personality traits of student, cognitive abilities. Background information (5) collected only at the baseline. B. First follow-up Phone-based Survey Zone 2, Summer (Phone Based). The survey replicates by phone shorter version of the internet-based survey above. We collect next information: 1. Subject specific knowledge tests.
2. Career intentions, preferences, beliefs, expectations, and attitudes. 3. Psychological characteristics

C. (Second) Follow-up Phone-Based Survey, Winter, Zone 2, Highlands Educational Regime.

We execute multi-topic questionnaire by phone to capture the first life-outcomes of students who finished the school. We collect next information:

1. Life Outcome 1- Education. The set of questions that aims to measure the learning success, career/study intentions, propensity to plan and approach others with studying tasks, entrepreneurial intentions.
2. Life Outcome 2- Labor. The set of questions that aims to measure employment status and income, job searching behavior, time devoted for working/business, salary expectations and knowledge about the careers, self-initiated contribution to the family.
3. Personal Initiative/Negotiations related and other measures. The set of questions that aim to measure level of personal initiative, negotiation strategies, pregnancy rate, gender stereotypes, math/STEM self-efficacy, gender attitudes, parent-student communication effects.

In March 2020, the number of search queries on the web page of the online school Foxford in Moscow increased by 1,255 percent compared to the same month of the previous year. The online education and distant learning services segment in Russia were forecast to increase by 37.5 percent as a result of the COVID-19 pandemic in 2020.

According to Cognitive Market Research, the global Online coding for kids market size will be USD 6492 million in 2025. It will expand at a compound annual growth rate (CAGR) of 18.60% from 2025 to 2033.

North America held the major market share for more than 40% of the global revenue with a market size of USD 2402.04 million in 2025 and will grow at a compound annual growth rate (CAGR) of 17.3% from 2025 to 2033.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 1882.68 million.
APAC held a market share of around 23% of the global revenue with a market size of USD 1558.08 million in 2025 and will grow at a compound annual growth rate (CAGR) of 21.7% from 2025 to 2033.
South America has a market share of more than 5% of the global revenue with a market size of USD 246.70 million in 2025 and will grow at a compound annual growth rate (CAGR) of 19.0% from 2025 to 2033.
Middle East had a market share of around 2% of the global revenue and was estimated at a market size of USD 259.68 million in 2025 and will grow at a compound annual growth rate (CAGR) of 19.1% from 2025 to 2033.
Africa had a market share of around 1% of the global revenue and was estimated at a market size of USD 142.82 million in 2025 and will grow at a compound annual growth rate (CAGR) of 14.4% from 2025 to 2033.
Middle school category is the fastest growing segment of the Online coding for kids industry

Market Dynamics of Online Coding for kids Market

Key Drivers for Online coding for kids Market

Growing Popularity of Online Education Boost Market Growth

The broader trend towards online education has a significant impact on the Online Coding Learning Platform Market. The COVID-19 pandemic accelerated this trend, causing educational institutions and businesses to shift to remote learning. Self-paced learning, interactive content, and a diverse range of resources are all advantages of using online platforms. Users can personalise their learning experiences to fit their schedules and skill levels, increasing enrollment rates. Furthermore, the proliferation of mobile devices has made it easier for students to take coding classes at any time and from any location. As online education becomes more popular, coding platforms are capitalising on a growing market of learners seeking flexible, high-quality training. Several platforms, including Upgrade, Udacity, and Udemy, offer free and paid comprehensive courses that prepare them for the job market. In the year 2020, there was a shift to online learning, 44,254 people attended or graduated from coding bootcamps, and the growth rate increased by 30.32% from 2019.

https://careerkarma.com/blog/bootcamp-market-report-2021/

Increasing Demand for Technical Skills Boost Market Growth

The Online Coding Market is driven by the increasing demand for technical skills in a digital economy. As businesses rely more on technology, there is a greater demand for skilled programmers in a variety of languages. This growth is driven by industries such as software development, data analysis, artificial intelligence, and machine learning. To stay competitive, organisations prioritise upskilling their workforce. Furthermore, the rise of remote work has made learning more accessible, allowing people to study coding from anywhere. As a result, online platforms that offer flexible, accessible, and practical coding education are rapidly expanding, catering to both professionals and aspiring developers looking to improve their skills.

Restraint Factor for the Online coding for kids Market

Technological barriers Will Limit Market Growth

Technological barriers impose constraints on the Online Coding Market, limiting accessibility and effectiveness. Users must have a stable internet connection and compatible devices to participate in online courses, which can limit participation in areas with inadequate infrastructure. In addition, the rapid pace of technological advancement requires platforms to frequently update their content and tools, necessitating significant investments in technology and training. Furthermore, learners may struggle with complex software installations or integrations, resulting in a learning curve that turns off potential users. Smaller platforms may struggle to achieve long-term growth due to the need for continuous technological adaptation

Market Trends in Online Coding for kids Market

Technological Advanc...

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The online language learning market is expected to grow at a CAGR of 20% during the forecast period. This market growth can be attributed to various factors including increasing enrollment of foreign students.

The online language learning market report offers several other valuable insights such as:

CAGR of the market during the forecast period 2020-2024
Detailed information on factors that will drive online language learning market growth during the next five years
Precise estimation of the online language learning market size and its contribution to the parent market
Accurate predictions on upcoming trends and changes in consumer behavior
The growth of the online language learning market industry across APAC, Europe, North America, South America, and MEA
A thorough analysis of the market’s competitive landscape and detailed information on vendors
Comprehensive details of factors that will challenge the growth of online language learning market vendors

In 2020, 58 percent of internet users in the United Kingdom (UK) aged between 16 and 24 used the internet to take part in online learning activities. Among 25-to-34-year-olds this share decreased to 36 percent. Among the other age groups, 55-to-64-years-olds were least likely do take part in online learning activities. Overall, the share of people using the internet for this purpose increased since 2015. The European questionnaire on Information and Communication Technologies Data reveals a disparity between the internet usage among different age groups. This disparity, although present in most countries, differs widely in its severity.

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The online language learning market research report estimates the market size to be $ 21.57 bn in 2020-2024. The incremental growth and the decelerate growth momentum present a positive outlook for the market. This will encourage established as well as new vendors to make investments and strengthen their position in the online language learning market.

The online language learning market research report offers several other key information including:

CAGR of the market during the forecast period 2020-2024
Detailed information on factors that will drive online language learning market growth during the next five years
Precise estimation of the online language learning market size and its contribution to the parent market
Accurate predictions on upcoming trends and changes in consumer behavior
The growth of the online language learning market industry across APAC, Europe, North America, South America, and MEA
A thorough analysis of the market’s competitive landscape and detailed information on vendors
Comprehensive details of factors that will challenge the growth of online language learning market vendors

Abstract

Opportunity-focused, high-growth entrepreneurship and science-led innovation are crucial for continued economic growth and productivity. Working in these fields offers the opportunity for rewarding and high-paying careers. However, the majority of youth in developing countries do not consider either as job options, affecting their choices of what to study. Youth may not select these educational and career paths due to lack of knowledge, lack of appropriate skills, and lack of role models. We provide a scalable approach to overcoming these constraints through an online education course for secondary school students that covers entrepreneurial soft skills, scientific methods, and interviews with role models.

The study comprises three experimental trials provided Before and during COVID-19 pandemic in different regions of Ecuador. This catalog entry includes data from Experiment 1: Educational Zone 2/Municipality of Quito 2019-2020. The data from the other two experiments are also available in the catalog.

Experiment 1: Educational Zone 2/Municipality of Quito 2019-2020 In course of Showing Life Opportunities project we conducted a randomized control trial in high schools in Educational Zone 2, Ecuador and Municipality of Quito, Ecuador in 2019-2020; Students finish the program in July 2020. The intervention is an online education course that covers entrepreneurial soft skills, scientific methods, and interviews with role models. This course is taken by students at school (some students finish the program at school during COVID-19 outbreak). We work with mostly 14-19 year-old students (16,570 students). The experimental program covers 126 schools in Educational Zone 2 and 11 schools in Municipality of Quito. We randomly assign schools either to treatment (and receiving the entrepreneurship courses online), or placebo-control (receiving a placebo treatment of online courses from standard curricula) groups. We also cross-randomize the role models and evaluate set of nimble interventions to increase take-up.

The details of intervention can be found in AEA registry: Asanov, Igor and David McKenzie. 2020. Showing Life Opportunities: Increasing opportunity-driven entrepreneurship and STEM careers through online courses in schools. AEA RCT Registry. July 19.

Geographic coverage

Experiment 1: Municipality of Quito and Educational Zone 2 Educational Zone 2 has its administrative headquarters in the city of Tena, Napo province. Its covers provinces of Napo, Orellana and Pichincha, 8 districts (15D01, 22D01, 17D10, 17D11, 15D02, 17D12, 22D02, 22D03), its 16 cantons and 68 parishes. It has an area of 39,542.58 km². The educational zone 2 spread from east to the western border of the Ecuador. We cover students of age 14-18 in schools that has sufficient access to the internet and classes of the K10, K11, or K12. We included the municipality of Quito in the study to enrich the coverage of program by having large (capital) city in the sample.

Analysis unit

Student

Kind of data

Sample survey data [ssd]

Sampling procedure

All students in selected schools who were present in classes filled out the baseline questionnaire

Mode of data collection

Internet [int]

Research instrument

Questionnaires We execute three main sets of questioners. A. Internet (Online Based survey)

The survey consists of a multi-topic questionnaire administered to the students through online learning platform in school during normal educational hours before COVID-19 pandemic or at home during the COVID-19 pandemic. We collect next information: 1. Subject specific knowledge tests. Spanish, English, Statistics, Personal Initiative (only endline), Negotiations (only endline). 2. Career intentions, preferences, beliefs, expectations, and attitudes. STEM and entrepreneurial intentions, preferences, beliefs, expectations, and attitudes. 3. Psychological characteristics. Personal Initiative, Negotiations, General Cognitions (General Self-Efficacy, Youth Self-Efficacy, Perceived Subsidiary Self-Efficacy Scale, Self-Regulatory Focus, Short Grit Scale), Entrepreneurial Cognitions (Business Self-Efficacy, Identifying Opportunities, Business Attitudes, Social Entrepreneurship Standards). 4. Behavior in (incentivized) games: Other-regarding preferences (dictator game), tendency to cooperate (Prisoners Dilemma), Perseverance (triangle game), preference for honesty, creativity (unscramble game). 5. Other background information. Socioeconomic level, language spoken, risk and time preferences, trust level, parents background, big-five personality traits of student, cognitive abilities. Background information (5) collected only at the baseline. B. First follow-up Phone-based Survey Zone 2, Summer (Phone Based). The survey replicates by phone shorter version of the internet-based survey above. We collect next information: 1. Subject specific knowledge tests.
2. Career intentions, preferences, beliefs, expectations, and attitudes. 3. Psychological characteristics

C. (Second) Follow-up Phone-Based Survey, Winter, Zone 2, Highlands Educational Regime.

We execute multi-topic questionnaire by phone to capture the first life-outcomes of students who finished the school. We collect next information:

1. Life Outcome 1- Education. The set of questions that aims to measure the learning success, career/study intentions, propensity to plan and approach others with studying tasks, entrepreneurial intentions.
2. Life Outcome 2- Labor. The set of questions that aims to measure employment status and income, job searching behavior, time devoted for working/business, salary expectations and knowledge about the careers, self-initiated contribution to the family.
3. Personal Initiative/Negotiations related and other measures. The set of questions that aim to measure level of personal initiative, negotiation strategies, pregnancy rate, gender stereotypes, math/STEM self-efficacy, gender attitudes, parent-student communication effects.

Cleaning operations

Data Editing A. Internet, Online-based surveys. We extracted the raw data generated on online platform from each experiment and prepared it for research purposes. We made several pre-processing steps of data: 1. We transform the raw data generated on platform in standard statistical software (R/STATA) readable format. 2. We extracted the answer for each item for each student for each survey (Baseline, Midline, Endline). 3. We cleaned duplicated students and duplicated answers for each item in each survey based on administrative data, performance and information given by students on platform. 4. In case of baseline survey, we standardized items/scales but also kept the raw items.

B. Phone-based surveys. The phone-based surveys are collected with help of advanced CATI kit. It contains all cases (attempts to call) and indication if the survey was effective. The data is cleaned to be ready for analysis. The data is anonymized but contains unique anonymous student id for merging across datasets.