According to a survey conducted in 2022, 47 percent of students in higher education agreed that the quality of online instruction in higher education is the same as the quality of in-person instruction in the United States, while 43 percent said that the quality was worse.

The online higher education market is experiencing robust growth, fueled by increasing accessibility, affordability demands, and technological advancements. The market's Compound Annual Growth Rate (CAGR) of 19.82% from 2019 to 2024 suggests a significant expansion, likely driven by factors such as the rising adoption of online learning platforms, flexible learning options catering to working professionals and geographically dispersed students, and the increasing recognition of online degrees by employers. The market segmentation, encompassing diverse types of online programs (e.g., bachelor's, master's, certificate programs) and applications across various fields (e.g., business, technology, healthcare), contributes to its broad appeal and expansion. Major players like American Public Education, Adtalem Global Education, and others are deploying competitive strategies focused on enhancing the learning experience, improving student support services, and expanding their program offerings to maintain a competitive edge. The geographic distribution indicates strong growth across North America and Asia-Pacific, driven by higher internet penetration and a growing young population seeking educational opportunities. However, challenges remain, including concerns about the perceived quality of online education compared to traditional institutions, the digital divide limiting access for certain demographics, and the need for continuous investment in technology and curriculum development to meet evolving learner needs. Looking ahead to 2033, the online higher education market is projected to maintain significant momentum, further expanding its reach and influence. Continued technological innovation, including advancements in virtual reality and artificial intelligence, will enhance the learning experience and attract a broader range of students. The growing importance of lifelong learning and upskilling will also drive demand for online courses and degree programs. Competitive pressures will likely lead to further innovation in pricing models, program offerings, and marketing strategies, fostering a dynamic and evolving market landscape. To fully capitalize on this growth, educational institutions must prioritize creating engaging and effective online learning environments, addressing concerns around quality and accessibility, and adapting to the ever-changing needs of students in a globally competitive market.

During a survey conducted in Spring 2023 in the United States, the most popular factor for choosing online education was the affordability of the program, with 77 percent of respondents reporting this was one of their top three reasons. The second most popular factor was the reputation of the school or program.

Online learning (e-learning) course enrolment totals by course and year for public and Catholic schools. School boards report this data using the Ontario School Information System (OnSIS).

Includes:

• course code
• course name
• online learning course enrolment totals by year

Enrolment totals include withdrawn or dropped courses. A student enrolled in more than one course is counted for each course.

Data excludes private schools and Education and Community Partnership Program (ECPP) facilities.

Not all courses offered by school boards are available to students via online learning.

Cells are suppressed in categories with less than 10 students. Enrolment totals are rounded to the nearest five.

Final as of October 4, 2024

In 2025, Texas A&M University-College Station was ranked as the best distance learning institution in the United States, with 40 percent of its students enrolled online. Florida International University, University of Florida, Arizona State University Digital Immersion, and University of Arizona rounded out the top five.

no. 8

2022

The six data sets were created for an undergraduate course at the Babes-Bolyai University, Faculty of Mathematics and Computer Science, held for second year students in the autumn semester. The course is taught both in Romanian and English with the same content and evaluation rules in both languages. The six data sets are the following: - FirstCaseStudy_RO_traditional_2019-2020.txt - contains data about the grades from the 2019-2020 academic year (when traditional face-to-face teaching method was used) for the Romanian language - FirstCaseStudy_RO_online_2020-2021.txt - contains data about the grades from the 2020-2021 academic year (when online teaching was used) for the Romanian language - SecondCaseStudy_EN_traditional_2019-2020.txt - contains data about the grades from the 2019-2020 academic year (when traditional face-to-face teaching method was used) for the English language - SecondCaseStudy_EN_online_2020-2021.txt - contains data about the grades from the 2020-2021 academic year (when online teaching was used) for the English language - ThirdCaseStudy_Both_traditional_2019-2020.txt - the concatenation of the two data sets for the 2019-2020 academic year (so all instances from FirstCaseStudy_RO_traditional_2019-2020 and SecondCaseStudy_EN_traditional_2019-2020 together) - ThirdCaseStudy_Both_online_2020-2021.txt - the concatenation of the two data sets for the 2020-2021 academic year (so all instances from FirstCaseStudy_RO_online_2020-2021 and SecondCaseStudy_EN_online_2020-2021 together)Instances from the data sets for the 2019-2020 academic year contain 12 attributes (in this order): - the grades received by the student for 7 laboratory assignments that were presented during the semester. For assignments that were not turned in a grade of 0 was given. Possible values are between 0 and 10 - the grades received by the student for 2 practical exams. If a student did not participate in a practical exam, de grade was 0. Possible values are between 0 and 10. - the number of seminar activities that the student had. Possible values are between 0 and 7. - the final grade the student received for the course. It is a value between 4 and 10. - the category of the final grade: - E for grades 10 or 9 - G for grades 8 or 7 - S for grades 6 or 5 - F for grade 4Instances from the data sets for the 2020-2021 academic year contain 10 attributes (in this order): - the grades received by the student for 7 laboratory assignments that were presented during the semester. For assignments that were not turned in a grade of 0 was given. Possible values are between 0 and 10 - a seminar bonus computed based on the number of seminar activities the student had during the semester, which was added to the final grade. Possible values are between 0 and 0.5. - the final grade the student received for the course. It is a value between 4 and 10. - the category of the final grade: - E for grades 10 or 9 - G for grades 8 or 7 - S for grades 6 or 5 - F for grade 4

The majority of Romanian parents stated that the most significant limitation of online learning during the coronavirus (COVID-19) pandemic was the lack of interaction with children of the same age, according to a survey from January 2021. Furthermore, nearly six in ten did not like the fact that children spent too much time in front of screens. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

One of the sectors that felt the impact of the Corona Virus Disease 2019 (COVID-19) pandemic was the educational sector. The outbreak led to the immediate closure of schools at all levels thereby sending billions of students away from their various institutions of learning. However, the shut down of academic institutions was not a total one as some institutions that were solely running online programmes were not affected. Those who were running face to face and online modes quickly switched over to the online mode. Unfortunately, institutions that have not fully embraced online mode of study were greatly affected. 85% of academic institutions in Nigeria are operating face to face mode of study, therefore, majority of Nigerian students at all levels were affected by the COVID-19 lockdown. Social media platforms and emerging technologies were the major backbones of institutions that are running online mode of study, therefore, this survey uses the unified theory of acceptance and use of technology (UTAUT) model to capture selected Face to face Nigerian University students accessibility, usage, intention and willingness to use these social media platforms and emerging technologies for learning. The challenges that could mar the usage of these technologies were also revealed. Eight hundred and fifty undergraduate students participated in the survey.

The dataset includes the questionnaire used to retrieve the data, the responses obtained in spreadsheet format, the charts generated from the responses received, the Statistical Package of the Social Sciences (SPSS) file and the descriptive statistics for all the variables captured. This second version contains the reliability statistics of the UTAUT variables using Cronbach's alpha. This measured the reliability as well as the internal consistency of the UTAUT variables. This was measured in terms of the reliability statistics, inter-item correlation matrix and item-total statistics. Authors believed that the dataset will enhance understanding of how face to face students use social media platforms and how these platforms could be used to engage the students outside their classroom activities. Also, the dataset exposes how familiar face to face University students are to these emerging teaching and learning technologies.

The 2021-2022 School Learning Modalities dataset provides weekly estimates of school learning modality (including in-person, remote, or hybrid learning) for U.S. K-12 public and independent charter school districts for the 2021-2022 school year and the Fall 2022 semester, from August 2021 – December 2022. These data were modeled using multiple sources of input data (see below) to infer the most likely learning modality of a school district for a given week. These data should be considered district-level estimates and may not always reflect true learning modality, particularly for districts in which data are unavailable. If a district reports multiple modality types within the same week, the modality offered for the majority of those days is reflected in the weekly estimate. All school district metadata are sourced from the National Center for Educational Statistics (NCES) for 2020-2021. School learning modality types are defined as follows: In-Person: All schools within the district offer face-to-face instruction 5 days per week to all students at all available grade levels. Remote: Schools within the district do not offer face-to-face instruction; all learning is conducted online/remotely to all students at all available grade levels. Hybrid: Schools within the district offer a combination of in-person and remote learning; face-to-face instruction is offered less than 5 days per week, or only to a subset of students. Data Information School learning modality data provided here are model estimates using combined input data and are not guaranteed to be 100% accurate. This learning modality dataset was generated by combining data from four different sources: Burbio [1], MCH Strategic Data [2], the AEI/Return to Learn Tracker [3], and state dashboards [4-20]. These data were combined using a Hidden Markov model which infers the sequence of learning modalities (In-Person, Hybrid, or Remote) for each district that is most likely to produce the modalities reported by these sources. This model was trained using data from the 2020-2021 school year. Metadata describing the location, number of schools and number of students in each district comes from NCES [21]. You can read more about the model in the CDC MMWR: COVID-19–Related School Closures and Learning Modality Changes — United States, August 1–September 17, 2021. The metrics listed for each school learning modality reflect totals by district and the number of enrolled students per district for which data are available. School districts represented here exclude private schools and include the following NCES subtypes: Public school district that is NOT a component of a supervisory union Public school district that is a component of a supervisory union Independent charter district “BI” in the state column refers to school districts funded by the Bureau of Indian Education. Technical Notes Data from August 1, 2021 to June 24, 2022 correspond to the 2021-2022 school year. During this time frame, data from the AEI/Return to Learn Tracker and most state dashboards were not available. Inferred modalities with a probability below 0.6 were deemed inconclusive and were omitted. During the Fall 2022 semester, modalities for districts with a school closure reported by Burbio were updated to either “Remote”, if the closure spanned the entire week, or “Hybrid”, if the closure spanned 1-4 days of the week. Data from August

Snapshot img

Distance Learning Market Size 2024-2028

The distance learning market size is forecast to increase by USD 149.23 billion at a CAGR of 9.65% between 2023 and 2028.

The growing demand for distance learning, fueled by the continuous development of technology, is a key driver of the distance learning market. As technology improves, online education becomes more accessible, engaging, and effective, allowing students to learn remotely with ease. The integration of advanced tools such as video conferencing, AI-driven assessments, and interactive content is further enhancing the appeal of distance learning.
In North America, the market is experiencing significant growth due to the integration of advanced technologies and shifting educational preferences. With a growing emphasis on flexible, personalized learning experiences, including self-paced e-learning, institutions are increasingly offering distance learning programs that cater to diverse student needs. This trend is expected to continue, contributing to the market's expansion in the region.

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

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The market is experiencing significant growth due to the increasing adoption of remote learning solutions among K-12 students and higher education students. Online assessments, video conferencing sessions, and virtual schools are becoming popular flexible education options for students who require flexibility in their learning schedules. Website-based mediums and application-based mediums, such as e-learning platforms, are increasingly being used to deliver educational programs. Internet access is essential for distance learning, making online learning platforms an indispensable tool for universities and colleges.

Market Segmentation

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

Type

  Traditional
  Online


Method

  Synchronous distance learning
  Asynchronous distance learning


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK


  APAC

    China


  Middle East and Africa



  South America

By Type Insights

The traditional segment is estimated to witness significant growth during the forecast period. The market encompasses various methods and technologies, including gamification, personalized learning pathways, educational environments, and remote learning techniques. Traditional distance learning, characterized by asynchronous online courses, pre-recorded lecture books, and minimal instructor interaction, remains a significant revenue contributor. This approach caters to a broad audience, particularly those with limited access to digital devices or high-internet connectivity. Academic institutions and the government sector continue to offer traditional distance learning programs, such as those provided by the Open University in the UK via mail. However, corporate blended learning, online education solutions, and personalized learning solutions are gaining popularity due to their interactive and technologically advanced nature.

These methods include learning management systems, virtual classrooms, mobile e-learning platforms, and cloud-based e-Learning platforms. Moreover, the use of intranet connection, computers, tutorials, podcasts, recorded lectures, e-books, and machine learning technology enhances the learning experience. The market also serves academic users and corporate users through service providers and content providers. The increasing literacy rate, internet penetration, and the need for continuous skill upgrading further fuel the market's growth.

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The traditional segment accounted for USD 152.29 billion in 2018 and showed a gradual increase during the forecast period.

Regional Insights

North America is estimated to contribute 34% 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 experiencing significant growth due to the integration of advanced technologies and shifting educational preferences. With the rise of gamification, personalized learning pathways, and educational environments, online education solutions have become increasingly popular. Academic institutions and the government sector are expanding their digital services, offering distance learning programs through Learning Management Systems and cloud-based e-Learning platforms. Remote learning methods, such as pre-recorded lectures, tutorials

Online and Distance Education at Postsecondary Institutions, 2006-07 (PEQIS 16), is a study that is part of the Postsecondary Education Quick Information System (PEQIS) program; program data is available since 1997 at . PEQIS 16 (https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2009044) is a survey that collects data on the prevalence and delivery of distance education courses in the 2006-07 12-month academic year, including the number of courses and enrollment for online courses, hybrid/blended online courses, and all other distance education courses. The survey also collects information about numbers of degree or certificate programs designed to be completed entirely through distance education and the technologies used for the instructional delivery of credit-granting distance education courses. The study was conducted using paper and web surveys. The weighted response rate was 87 percent. Postsecondary institutions were sample for this study. Key statistics produced from PEQIS 16 relate to information on the prevalence, types, delivery, policies, and acquisition or development of distance education courses and programs.

Subject: EducationSpecific: Online Learning and FunType: Questionnaire survey data (csv / excel)Date: February - March 2020Content: Students' views about online learning and fun Data Source: Project OLAFValue: These data provide students' beliefs about how learning occurs and correlations with fun. Participants were 206 students from the OU

Historical Dataset of Madison Online Learning Academy is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2022-2023),Distribution of Students By Grade Trends,Hispanic Student Percentage Comparison Over Years (2022-2023),White Student Percentage Comparison Over Years (2022-2023),Two or More Races Student Percentage Comparison Over Years (2022-2023),Diversity Score Comparison Over Years (2022-2023)

Historical Dataset of Online High School is provided by PublicSchoolReview and contain statistics on metrics:Distribution of Students By Grade Trends

Historical Dataset of Karval Online Education is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2005-2023),Total Classroom Teachers Trends Over Years (2005-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2005-2023),American Indian Student Percentage Comparison Over Years (2005-2023),Asian Student Percentage Comparison Over Years (2008-2012),Hispanic Student Percentage Comparison Over Years (2005-2023),Black Student Percentage Comparison Over Years (2005-2023),White Student Percentage Comparison Over Years (2005-2023),Diversity Score Comparison Over Years (2005-2023),Free Lunch Eligibility Comparison Over Years (2009-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2009-2023),Reading and Language Arts Proficiency Comparison Over Years (2010-2014),Math Proficiency Comparison Over Years (2010-2014),Overall School Rank Trends Over Years (2010-2014),Graduation Rate Comparison Over Years (2011-2014)

Snapshot img

North America Virtual Schools Market Size 2025-2029

The virtual schools market in North America size is forecast to increase by USD 2.24 billion billion at a CAGR of 14.2% between 2024 and 2029.

The market is experiencing significant growth, driven by the need for cost-effective teaching models and the emergence of E-learning via mobile devices. The increasing popularity of open-source learning content is another key trend fueling market expansion. With budget constraints and the desire for flexible learning options, virtual schools offer an attractive solution for students and educators alike.
This shift towards virtual education is transforming the education landscape, presenting both opportunities and challenges.Staying abreast of these market dynamics is essential for stakeholders looking to capitalize on the potential of this rapidly evolving sector.

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

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The market is experiencing significant growth, driven by the increasing adoption of online collaboration tools and educational innovation. Virtual school management systems facilitate online school choice for students, enabling personalized instruction and improved student retention. Educational research highlights the effectiveness of digital accessibility and virtual learning technology integration in enhancing learning outcomes. Student engagement strategies, such as educational video and interactive simulations, are essential components of virtual school design. The future of education lies in the development of digital learning ecosystems, which incorporate online reputation management, equity in education, and learning analytics. Virtual schools require robust online learning infrastructure to support student support systems and ensure digital accessibility for all students.
The integration of learning technology and online learning platforms into virtual schools is crucial for delivering effective instruction and promoting student success. Virtual school governance is a critical aspect of the virtual schools market, ensuring the provision of high-quality education and addressing the digital divide. Online learning platforms must prioritize student engagement and provide effective student support systems to mitigate potential challenges and promote positive learning experiences. The use of virtual schools and online learning infrastructure offers significant benefits, including increased flexibility, accessibility, and personalized instruction. However, challenges remain, including the need for effective online reputation management and ensuring equity in education.The market will continue to evolve, with a focus on developing innovative learning technologies and digital content to enhance the virtual learning experience.

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 billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Type

  For-profit EMO
  Non-profit EMO


Application

  Elementary schools
  Middle schools
  High schools
  Adult education


Delivery Mode

  Online Courses
  Learning Management Systems
  Mobile Learning
  Virtual Classrooms


Subject Area

  STEM
  Business & Management
  Healthcare
  Creative Arts


Deployment Type

  Cloud-Based
  On-Premises


Geography

  North America

    US
    Canada
    Mexico

By Type Insights

The for-profit emo segment is estimated to witness significant growth during the forecast period.

For-profit Education Management Organizations (EMOs) are private entities that offer administrative and operational support, curriculum development, and teacher training to schools or districts while aiming for profit generation. These organizations have extensive experience and expertise in delivering virtual education programs. They invest in advanced technology infrastructure, learning management systems, and instructional resources to create engaging virtual learning experiences for students. For-profit EMOs prioritize personalized learning, student engagement, and parent involvement through digital textbooks, online curriculum, and interactive digital learning platforms. They also emphasize student success by providing online tutoring, adaptive learning, and data analytics. Virtual classrooms and mobile learning enable students to access education from anywhere, while virtual field trips offer immersive educational experiences.

For-profit EMOs build educational partnerships to expand their offerings, including virtual labs, online libraries, and virtual school networks. They also focus on online marketing, branding, and student recruitment to attract a diverse student population. Higher education institutions collaborate with for-profit

Historical Dataset of Odyssey Online Learning School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2013-2023),Total Classroom Teachers Trends Over Years (2013-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2013-2023),Asian Student Percentage Comparison Over Years (2010-2015),Hispanic Student Percentage Comparison Over Years (2013-2023),Black Student Percentage Comparison Over Years (2013-2023),White Student Percentage Comparison Over Years (2013-2023),Diversity Score Comparison Over Years (2013-2023),Free Lunch Eligibility Comparison Over Years (2013-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2013-2023),Reading and Language Arts Proficiency Comparison Over Years (2010-2018),Math Proficiency Comparison Over Years (2010-2018),Overall School Rank Trends Over Years (2010-2018),Graduation Rate Comparison Over Years (2011-2018)

Solution Probability Model and Fairness Evaluation

This in-session prediction model seeks to predict the users’ performance on the Orthografietrainer.net platform. The target variable is binary and predicts if the user will do the following sentence correctly or not. For fairness evaluations the best models (MLP and DTE), and the worst model (SVM) are considered. A random state is not set, thus, results might differ marginally.

A detailed description of the solution probability model and the fairness evaluation can be found here: tba