2021.

The Massive Open Online Courses (MOOC) market has transformed the landscape of education, revolutionizing how learners access knowledge across the globe. As an innovative approach to education, MOOCs offer free or low-cost online courses delivered by universities, educational institutions, and industry leaders, maki

During a 2023 survey, Coursera ranked as the most well known Massive Open Online Courses (MOOC) platform in Mexico, followed by Canvas Network and Udemy.

The global massive open online course (MOOC) market size is calculated to advance at a CAGR of 32% through 2034, which is set to increase its market value from US$ 13.2 billion in 2024 to US$ 212.7 billion by the end of 2034.

Report Attribute	Detail
MOOC Market Size (2024E)	US$ 13.2 Billion
Projected Market Value (2034F)	US$ 212.7 Billion
Global Market Growth Rate (2024 to 2034)	32% CAGR
China Market Value (2034F)	US$ 23.3 Billion
Japan Market Growth Rate (2024 to 2034)	32.6% CAGR
North America Market Share (2024E)	23.9%
East Asia Market Value (2034F)	US$ 49.1 Billion
Key Companies Profiled	Alison; Coursera Inc; edX Inc; Federica.EU; FutureLearn; Instructure; Intellipaat; iverity; Jigsaw Academy; Kadenze.

Country Wise Insights

Attribute	United States
Market Value (2024E)	US$ 1.4 Billion
Growth Rate (2024 to 2034)	32.5% CAGR
Projected Value (2034F)	US$ 23.6 Billion

Attribute	China
Market Value (2024E)	US$ 1.5 Billion
Growth Rate (2024 to 2034)	32% CAGR
Projected Value (2034F)	US$ 23.3 Billion

Category-wise Insights

Attribute	xMOOC
Segment Value (2024E)	US$ 9.3 Billion
Growth Rate (2024 to 2034)	30.8% CAGR
Projected Value (2034F)	US$ 136.1 Billion

Attribute	Degree & Master Programs
Segment Value (2024E)	US$ 6.4 Billion
Growth Rate (2024 to 2034)	30.2% CAGR
Projected Value (2034F)	US$ 89.3 Billion

This statistic presents the share of U.S. online population who have taken or heard of a massive open online course (MOOC) as of January 2014, sorted by internet use in hours per week. During the survey period it was found that only 5 percent of the respondents who were using internet for more than 22 hours had taken a MOOC whereas 18 percent had heard of it.

Online education has become more prevalent in the 21st century, especially after the COVID-19 pandemic. One of the major trends is the learning via Massive Open Online Courses (MOOCs), which is increasingly present at many universities around the world these days. In these courses, learners interact with the pre-designed materials and study everything mostly by themselves. Therefore, gaining insights into their satisfaction of such courses is vitally important to improve their learning experiences and performances. However, previous studies primarily focused on factors that affected learners’ satisfaction, not on how and what the satisfaction was. Moreover, past research mainly employed the narrative reviews posted on MOOC platforms; very few utilized survey and interview data obtained directly from MOOC users. The present study aims to fill in such gaps by employing a mixed-methods approach including a survey design and semi-structured interviews with the participation of 120 students, who were taking academic writing courses on Coursera (one of the world-leading MOOC platforms), at a private university in Vietnam. Results from both quantitative and qualitative data showed that the overall satisfaction of courses on Coursera was relatively low. Furthermore, most learners were not satisfied with their learning experience on the platform, primarily due to inappropriate assessment, lack of support, and interaction with teachers as well as improper plagiarism check. In addition, there were moderate correlations between students’ satisfaction and their perceived usefulness of Coursera courses. Pedagogically, teachers’ feedback and grading, faster support from course designers as well as easier-to-use plagiarism checking tools are needed to secure learners’ satisfaction of MOOCs.

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MOOCs Market Size 2025-2029

The MOOCs market size is forecast to increase by USD 160.74 billion, at a CAGR of 63.3% between 2024 and 2029.

The Massive Open Online Courses (MOOCs) market is experiencing significant growth, driven by the increasing adoption of MOOCs in corporate training programs. This trend is particularly prominent in regions where there is a strong focus on workforce development and skills enhancement. The extensive application of MOOCs in corporate training is transforming the way businesses approach employee development, enabling them to offer flexible, cost-effective, and accessible learning opportunities. However, the market faces challenges in ensuring completion rates for MOOCs.
To capitalize on the market opportunities and navigate these challenges effectively, companies can explore strategies such as offering incentives, providing personalized learning experiences, and leveraging social learning to enhance learner engagement and completion rates. By addressing these challenges and continuing to innovate in the field, the market is poised to significantly impact the future of education and corporate training. Data analytics and learning analytics provide valuable insights into student performance, enabling instructors to offer personalized feedback and course adjustments. Despite the convenience and flexibility that MOOCs offer, learners often face difficulties in completing the courses due to various reasons such as time constraints, lack of motivation, and competing priorities.

What will be the Size of the MOOCs 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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The market continues to evolve, with dynamic market activities shaping its landscape. Learning pathways and open source platforms are increasingly being utilized to deliver educational content, enabling access to a vast array of courses. Automated grading and content licensing facilitate skill development, while blended learning and subscription models cater to diverse learning preferences. Student success is a key focus, with course content optimized for knowledge retention through video lectures, interactive simulations, and adaptive learning. Platform integration and collaboration tools foster social learning, enabling students to engage in discussions and learn from one another.

Mobile responsiveness and user experience (UX) enhance accessibility, allowing learners to engage with courses on-the-go. API integration and course authoring tools enable customization and scalability, while accessibility features cater to diverse learners. Career advancement opportunities and performance measurement are increasingly important, with freemium models offering flexible pricing options. Marketing and outreach efforts continue to expand, reaching learners across various sectors, including K-12 education and higher education. Continuous innovation in educational technology, such as AI-powered tutoring and interactive exercises, is driving growth in the market. The ongoing evolution of this market is transforming the way we learn, offering new opportunities for personalized and effective education.

How is this MOOCs Industry segmented?

The MOOCs industry 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.

Type

  xMOOCs
  cMOOCs


Subjects

  Technology
  Science
  Business and management
  Arts and humanities
  Others


End-user

  Students
  Professionals
  Corporates


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    Australia
    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Type Insights

The xMOOCs segment is estimated to witness significant growth during the forecast period. The xMOOCs market, a segment of Massive Open Online Courses (MOOCs) based on traditional university courses, is experiencing consistent growth. While cMOOCs initially spearheaded the MOOC revolution, the majority of providers now offer xMOOCs. Companies like Coursera and Udacity lead the market, catering to learners seeking higher education and corporate training. The xMOOCs model, which prioritizes personalized feedback, progress tracking, and course delivery through educational technology, is gaining popularity due to its effectiveness. Social learning, knowledge retention, and interactive simulations are integral components, fostering student engagement and skill development. Course completion certificates and video lectures add credibility, while intellectual property rights ensure content protection.

Adaptive learning and collaborative tools facilitate a more effective

Massive Online Open Courses (MOOCs) present the potential to deliver high quality education to a large number of students. But they suffer from low completion rates. This paper identifies disorganization as a factor behind failure to complete a MOOC. Students who enroll one day late are 17 percentage points less likely to earn a certificate than students who enroll exactly on time. This reflects selection, but it does seem to be related to demographic characteristics, motivation to complete the course, or ability. This suggests that building in even more structure in the MOOC could be a factor in improving performance.

The size of the MOOC Industry market was valued at USD XXX Million in 2023 and is projected to reach USD XXX Million by 2032, with an expected CAGR of 39.20% during the forecast period.Massive Open Online Courses (MOOCs) - open courses available for public enrollment, offering free mass participation through the Internet-accessible variety of resources. Examples include lectures, study material, videos, and assignments usually available in a traditional class situation. MOOCs also entail interactive user forums where interaction can be established with your peers, professors, as well as teaching assistants to give a sense of the community.MOOCs provide a great number of benefits, such as accessibility, affordability, flexibility, and wide course options. They allow people to learn new skills, advance in their careers, and even follow personal interests. Besides, MOOCs can be added to traditional education as a diversification of learning. Recent developments include: November 2022 : Riverside Extension (UCRX), The University of California, and edX, one of the leading global online learning platforms from 2U, Inc., announced a collaboration to develop UCRX's first Massive Open Online Courses (MOOCs) on the edX platform. The courses, featuring content in well-being, mental health, and world languages, will be free-to-audit for edX learners., September 2022 : The London School of Economics and Political Science (LSE) and edX, one of the leading global online learning platforms from 2U, Inc., launched LSE's first two MicroBachelors programs in Statistics Fundamentals and Mathematics and statistics Fundamentals and An Introduction to Pre-University Mathematics, its first MOOC. LSE is the first university to expand its degree partnership with the 2U to launch a series of edX micro-credentials that offers learners a flexible, stackable pathway toward pursuing an entirely online undergraduate education.. Key drivers for this market are: Demand for Cost Effective Education Platforms, Increasing Requirement of Global Training. Potential restraints include: Low Course Completion Rate, Poor Discussion Forum and Mentoring. Notable trends are: Technology Subject is expected to hold Major Share.

This is a a dataset containing Integrated Development Environment (IDE) logs from an introductory programming MOOC. The dataset contains information on when actions in the IDE were performed in relation to deadlines over the different parts of the course. One exceptional aspect of the dataset is that part of the logs have been gathered at the keystroke level, allowing for fine-grained insight into the learning process. In addition to the IDE logs themselves, the dataset has information on whether students included in the data passed the course. This can facilitate further research that analyzes how time-related behavior relates to performance in introductory programming courses.

The Massive Open Online Course (MOOC) Platforms market has experienced exponential growth in recent years, transforming the landscape of education and professional development. With the surge in demand for accessible, flexible, and affordable learning solutions, MOOC platforms have emerged as pivotal tools for milli

Nearly 16 percent of online courses offered by Russian universities were published on the National Open Education Platform (NOEP) as of October 2021. That platform was developed by several higher institutions of the country. Furthermore, 13 percent of the educational programs were available on the platform Stepik.

These files contain the anonymized data and analysis files used to create the tables found in "A Randomized Experiment Testing the Efficacy of a Scheduling Nudge in a Massive Open Online Course (MOOC)".The abstract for the paper is found below:An increasing number of students are taking classes offered online through open access platforms; however, the vast majority of students who start these classes do not finish. The incongruence of student intentions and subsequent engagement suggests that self-control is a major contributor to this stark lack of persistence. This study presents the results of a large-scale field experiment (n=18,043) that examines the effects of a self-directed scheduling nudge designed to promote student persistence in a Massive Open Online Course (MOOC). We find that random assignment to treatment had no effects on near-term engagement and weakly significant negative effects on longer-term course engagement, persistence, and performance. Interestingly, these negative effects are highly concentrated in two groups of students: those who registered close to the first day of class and those with .edu email addresses. We consider several explanations for these findings and conclude that theoretically motivated interventions may interact with the diverse motivations of individual students in possibly unintended ways.

This dataset is comprised of word embeddings and document topic distribution vectors generated from transcripts of 12032 video lectures from 200 courses that were collected from Coursera learning platform. Two well-known natural language processing techniques, namely Word2Vec and Latent Dirichlet Allocation (LDA) implemented in the Gensim package in Python are used to generate word embeddings and topic vectors, respectively.

Data Sets from EJC.

• N/A, not applicable.Overall statistics of the students.

According to Cognitive Market Research, the global MOOC market size will be USD 39.20 billion in 2024 and will expand at a compound annual growth rate (CAGR) of 39.1% from 2024 to 2031. Market Dynamics of MOOC Market

Key Drivers for MOOC Market

Growing Technological Advancements - One of the main reasons the MOOC market growth is propelled by advancements in technology, including improved video streaming, interactive learning tools, and artificial intelligence for personalized learning experiences. These technologies enhance engagement, facilitate real-time feedback, and enable adaptive learning paths, making MOOCs more effective and appealing to learners and educational institutions alike. The integration of virtual reality and augmented reality further enriches the learning experience, driving the expansion of MOOCs into new educational domains and enhancing their effectiveness in skills development and knowledge acquisition.
The broad internet penetration expands access to Massive Open Online Courses (MOOCs) is anticipated to drive the MOOC market's expansion in the years ahead.

Key Restraints for MOOC Market

Ensuring course quality and credibility hampers MOOC scalability in the MOOC industry growth.
Limited recognition and accreditation challenge MOOC adoption and trust to data security and privacy impact market growth.

Introduction of the MOOC Market

MOOC is driven by increasing global internet penetration, and accessibility to digital devices has democratized education, making quality learning resources available to a broader audience. Secondly, the rising demand for lifelong learning and upskilling in a rapidly evolving job market fuels the adoption of MOOCs as flexible and affordable educational options. Thirdly, partnerships between educational institutions and tech companies expand course offerings and enhance the credibility of online certifications. Lastly, the COVID-19 pandemic has accelerated the acceptance and integration of online learning platforms, reinforcing the convenience and effectiveness of MOOCs in delivering education remotely. These drivers collectively propel the growth of MOOCs as a pivotal component of modern education delivery worldwide.

Descriptive statistics of the crawled MOOC review data.

Description

We collected EEG signal data from 10 college students while they watched MOOC video clips. We extracted online education videos that are assumed not to be confusing for college students, such as videos of the introduction of basic algebra or geometry. We also prepare videos that are expected to confuse a typical college student if a student is not familiar with the video topics like Quantum Mechanics, and Stem Cell Research. We prepared 20 videos, 10 in each category. Each video was about 2 minutes long. We chopped the two-minute clip in the middle of a topic to make the videos more confusing. The students wore a single-channel wireless MindSet that measured activity over the frontal lobe. The MindSet measures the voltage between an electrode resting on the forehead and two electrodes (one ground and one reference) each in contact with an ear. After each session, the student rated his/her confusion level on a scale of 1-7, where one corresponded to the least confusing and seven corresponded to the most confusing. These labels if further normalized into labels of whether the students are confused or not. This label is offered as self-labelled confusion in addition to our predefined label of confusion.

Data information:

-----data.csv

1. Column 1: Subject ID
2. Column 2: Video ID
3. Column 3: Attention (Proprietary measure of mental focus)
4. Column 4: Mediation (Proprietary measure of calmness)
5. Column 5: Raw (Raw EEG signal)
6. Column 6: Delta (1-3 Hz of power spectrum)
7. Column 7: Theta (4-7 Hz of power spectrum)
8. Column 8: Alpha 1 (Lower 8-11 Hz of power spectrum)
9. Column 9: Alpha 2 (Higher 8-11 Hz of power spectrum)
10. Column 10: Beta 1 (Lower 12-29 Hz of power spectrum)
11. Column 11: Beta 2 (Higher 12-29 Hz of power spectrum)
12. Column 12: Gamma 1 (Lower 30-100 Hz of power spectrum)
13. Column 13: Gamma 2 (Higher 30-100 Hz of power spectrum)
14. Column 14: predefined label (whether the subject is expected to be confused)
15. Column 15: user-defined label (whether the subject is actually confused)

-----subject demographic

1. Column 1: Subject ID
2. Column 2: Age
3. Column 3: Ethnicity (Categorized according to https://en.wikipedia.org/wiki/List_of_contemporary_ethnic_groups)
4. Column 4: Gender

-----video data

Each video lasts roughly two-minute long, we remove the first 30 seconds and last 30 seconds, only collect the EEG data during the middle 1 minute.

Format

These data are collected from ten students, each watching ten videos.

Therefore, it can be seen as only 100 data points for these 12000+ rows. If you look at this way, then each data point consists of 120+ rows, which is sampled every 0.5 seconds (so each data point is a one minute video). Signals with higher frequency are reported as the mean value during each 0.5 second.

Reference:

Wang, H., Li, Y., Hu, X., Yang, Y., Meng, Z., & Chang, K. M. (2013, June). Using EEG to Improve Massive Open Online Courses Feedback Interaction. In AIED Workshops.

Inspiration

• This dataset is an extremely challenging data set to perform binary classification. 65% of prediction accuracy is quite decent according to our experience.

• It is an interesting data set to carry out the variable selection (causal inference) task that may help further research. Past research has indicated that Theta signal is correlated with confusion level.

• It is also an interesting data set for confounding factors correction model because we offer two labels (subject id and video id) that could profoundly confound the results.

Contact

haohanw@cs.cmu.edu

This dataset release is comprised of de-identified data from March 2014 - September 2015 of Canvas Network open courses, along with related documentation. In balancing data utility with thorough de-identification, this dataset favors utility; therefore, access and usage of this dataset is restricted as described in the Canvas Network Data Usage Agreement. These data use a star schema to organize various course, activity, and person records using dimensions and facts. The structure of this dataset is based on the Canvas Data star schema as described in https://portal.inshosteddata.com/docs. The first release of this dataset is the Canvas Network Courses, Activities, and Users (4/2014 - 9/2015) Dataset, version 1.0, created on March 3, 2016. The data set is split into multiple files for convenience: CNCAU_1403-1509_R_v1_03-03-2016.tgz contains the facts and dimensions representing the breadth of the dataset CNCAU_1403-1509_R_v1_03-03-2016_requests-01.gz - ...08.gz contain user page view requests The resulting files are plain text, with tab-separated values.