The overall level of satisfaction of students with higher education in India had decreased significantly after the COVID-19 pandemic in 2020. About 78 percent of the students stated that peer learning was a major challenge with online teaching methods in the country during the pandemic that year.

According to a survey conducted in February 2021 on the effects of online classes in South Korea, roughly 83 percent of respondents stated that they worried about the weakening of relationships with friends and the sense of community after having online classes for one year due to the coronavirus situation. The same amount of respondents also worried about the alienation of socially and economically disadvantaged pupils, and the increasing burden of home support and care. In March 2020, the South Korean government decided that schools would start again in April via online classes to prevent the spread of COVID-19.

2022

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 outbreak of COVID -19 forced most universities into distance education. Three didacticians and researchers from the University of Maribor, Slovenia: Kosta Dolenc, Mateja Ploj Virtič and Andrej Šorgo formed a self-initiated initiative project group during the COVID -19 epidemic and started the first project with the working title: The Side Effects of Forced Online Distance Education (FODE).

The aim of the second study, conducted during the first wave of the epidemic in March 2020, was to investigate the response of university students to the new situation. The project documentation provided for the Forced Online Distance Learning (FODL) consists of:

• abstract,
• instrument,
• copy of the descriptive statistics,
• and SPSS dataset.

In 2020, ** percent of respondents to a survey of parents in India were concerned with their children developing health issues due to increased screen-time in the wake of the shift to online learning during the coronavirus pandemic. Similarly, parents were concerned about technical challenges, less face-to-face learning with teachers leading to uncertainty and the absence from school or friends affecting the child's mental well being. Less than *** percent of parents stated that they have no concerns about their child learning online.

{"references": ["Ploj Virti\u010d, M., Dolenc, K., & \u0160orgo, A. (2021). Changes in online distance learning behaviour of university students during the Coronavirus disease 2019 outbreak, and development of the model of forced distance online learning preferences. European Journal of Educational Research, 10(1), 393-411. https://doi.org/10.12973/eu-jer.10.1.393", "\u0160orgo, A., Ploj Virti\u010d, M., Dolenc, K. (2021). Differences in personal innovativeness in the domain of information technology among university students and teachers [submitted manuscript]", "Dolenc, K., \u0160orgo, A., Ploj Virti\u010d, M. (2021). The difference in views of educators and students on Forced Online Distance Education can lead to unintentional side effects. Education and Information Technologies [accepted manuscript], https://www.10.1007/s10639-021-10558-4", "Ploj Virti\u010d, M., Dolenc, K., \u0160orgo, A. (2020). \u0160tudij na daljavo na Univerzi v Mariboru v \u010dasu izbruha CoVID-19 in napovedni model \u0161tudija na daljavo za \u010das po ponovnem odprtju univerze. V: Inovativna uporaba IKT v visokem \u0161olstvu: izzivi in prilo\u017enosti: konferenca IKTVVIS, online, 24. - 25. september 2020. Ljubljana: IKTVVIS. 2020, http://iktvvis.si/SekcijaCC12.html#povzetek50", "\u0160orgo, A., Ploj Virti\u010d, M., Dolenc, K. (2020). Razlike med univerzitetnimi u\u010ditelji in \u0161tudenti v osebni inovativnosti na podro\u010dju informacijskih tehnologij. V: Inovativna uporaba IKT v visokem \u0161olstvu: izzivi in prilo\u017enosti: konferenca IKTVVIS, online, 24. - 25. september 2020. Ljubljana: IKTVVIS. 2020, http://iktvvis.si/SekcijaC21.html#povzetek10"]} The outbreak of COVID -19 forced most universities into distance education. Three didacticians and researchers from the University of Maribor, Slovenia: Kosta Dolenc, Mateja Ploj Virti�� and Andrej ��orgo formed a self-initiated initiative project group during the COVID -19 epidemic and started the first project with the working title: The Side Effects of Forced Online Distance Education (FODE). The aim of the second study, conducted during the first wave of the epidemic in March 2020, was to investigate the response of university students to the new situation. The project documentation provided for the Forced Online Distance Learning (FODL) consists of: abstract, instrument, copy of the descriptive statistics, and SPSS dataset. This work was supported by the Slovenian Research Agency under the core projects: "Information systems", grant no. P2-0057 (��orgo Andrej) and "Computationally intensive complex systems", grant no. P1-0403 (Ploj Virti�� Mateja). The authors declared that there were no conflicts of interest and that the opinions expressed were those of the authors. For the English translation of the instrument, see the articles cited in the Introduction (see Appendix).

LearnPlatform is a technology platform in the kindergarten-12th grade (K-12) market providing a broadly interoperable platform to the breadth of educational technology (edtech) solutions in the United States K-12 field. A key component of edtech effectiveness is integrated reporting on tool usage and, where applicable, evidence of efficacy. With COVID closures, LearnPlatform is a resource to measure whether students are accessing digital resources within distance learning constraints. This platform provides a source of data to understand if students are accessing digital resources, and where resources have disparate usage and impact. This study includes educational technology usage across over 8,000 tools used in the education field in 2020.

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.

We investigate the impacts of school-based internet access on second graders' test scores, using over 2 million student observations from a panel of Peruvian public primary schools. We identify effects up to 6+ years after installation on different cohorts of second-grade students, exploiting variation in the timing of internet access induced by the rollout of a national program. We find positive but modest short-run impacts, but importantly, these effects grow for subsequent cohorts. Indeed, short-run estimates alone would have led to different conclusions. These dynamics underscore the value of extended evaluation windows to allow benefits of educational technology to materialize

The American Institutes for Research conducted a multisite randomized study that tested an online learning model for credit recovery at 24 high schools in Los Angeles, California in 2018 and 2019. The study focused on first-year high school students who failed Algebra 1 or English 9 (their ninth-grade English course) and retook the course during the summer before their second year of high school. Within each participating school, we used a lottery to determine whether each student was placed in either the school’s typical teacher-directed class (business-as-usual control condition) or a class that used an online learning model (treatment condition). For the online learning model, an online provider supplied the main course content, and the school provided a subject-appropriate, credentialed in-class teacher who could supplement the digital content with additional instruction.The study compared outcomes of students assigned to the treatment condition to outcomes of students assigned to the control condition. Analyses focused both on proximal outcomes (ex: student course experiences, content knowledge, and credit recovery rates) and distal outcomes (ex: on-time graduation and cumulative credits earned by the end of the 4th year of high school). We estimated average treatment effects for the intent-to-treat sample using regression models that control for student characteristics and randomization blocks. We conducted separate analyses for students who failed Algebra 1 and students who failed at least one semester of their English 9 course.This ICPSR data deposit includes our final analytical dataset and three supplemental files. Data come from three sources: (1) extant district data on student information and academic outcomes, (2) end-of-course surveys of students’ and teachers’ experiences, and (3) end-of-course test of students’ content knowledge. Data fields include:Sample information: term, school (anonymized), teacher (anonymized), course, randomization block, student cohort, treatment statusDemographics: sex, race/ethnicity, National School Lunch Program status, inclusion in the Gifted/Talented program, Special Education status, and English language learner statusPre-treatment information (treatment group only): 9th grade GPA, 9th grade attendance rate, number of 9th grade courses failed, 8th grade test scoresOnline course engagement information: percentage of online course completed, average score on online activities, minutes spent in online platformStudent survey data: responses a survey administered at the end of the course for treatment and control students. Questions cover degree of student engagement with the course, perceptions of teacher support and course difficulty, and clarity of course expectations.End-of-course test data: answers and scores on an end-of-course assessment administered to treatment and control students to evaluate content knowledge (Algebra 1 or English 9). The test did not count towards the final course grade and included 17-20 multiple choice questions.Academic outcomes: grade in credit recovery course, credits attempted/earned in each year of high school, GPA in each year of high school, credits/GPA in math and ELA in each year of high school, indicator for on-time high school graduation, 10th grade PSAT scoresTeacher survey and logs: teacher-reported logs on the use of different instructional activities and responses to surveys about course pacing, content, goals, and degree of student support

The COVID-19 pandemic caused unprecedented changes to educational institutions, forcing their closure and a subsequent shift to online education to cater to student learning requirements. However, successful online learning depends on several factors and may also vary between countries. As such, this cross-sectional study sought to investigate how engagement of university students, a major driver of online learning, was influenced by course content, online interaction, student acceptance, and satisfaction with online learning, as well as self-efficacy across nine countries (China, India, Iran, Italy, Malaysia, Portugal, Serbia, Turkey, and the United Arab Emirates) during the COVID-19 pandemic. Using a questionnaire-based approach, data collected from 6,489 university students showed that student engagement was strongly linked to perception of the quality of the course content and online interactions (p < .001). The current study also indicated that online interactions are a major determinant of academic efficacy but only if mediated by engagement within the online learning context. A negative correlation between student engagement and satisfaction with online learning was found, demonstrating the importance of students being engaged behaviorally, emotionally, and cognitively to feel satisfied with learning. Academic efficacy and student satisfaction were explained by course content, online interaction, and online learning acceptance, being mediated by student engagement. Student satisfaction and, to a lesser degree academic efficacy, were also associated with online learning acceptance. Overall, the structural equation model was a good fit for the data collected from all nine countries (CFI = .947, TLI = .943; RMSEA = .068; SRMR = .048), despite differences in the percentage variations explained by each factor (no invariance), likely due to differences in levels of technology use, learning management systems, and the preparedness of teachers to migrate to full online instruction. Despite limitations, the results of this study highlight the most important factors affecting online learning, providing insight into potential approaches for improving student experiences in online learning environments.

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 IMPROVE database was developed to assess the impact of mobile phone usage on learners engaged in online education in a 30-minutes learning session. It evaluates not only academic performance and learner feedback but also captures biometric, behavioral, and physiological signals, enabling a thorough analysis of how mobile phone use affects learning. Data were collected from 120 learners, categorized into three groups based on their levels of mobile phone interaction. A variety of sensors were utilized to gather data, including electroencephalography (EEG) waves, RGB videos, eye tracking, and heart rate, all of which have been shown in cutting-edge research to be effective indicators of learner behavior and cognition. The database also features metadata derived from processed videos, such as face bounding boxes, facial landmarks, and Euler angles for head pose estimation. Additionally, it contains performance data and self-reported questionnaires from the learners. Phone usage events were labeled, encompassing both supervisor-triggered and uncontrolled instances.

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.

This systematic review of ten years of research on scaffolding in online learning aims to explore the influence of scaffolding on online learning.

Following the COVID-19 pandemic, higher education institutions in Denmark switched to online learning programs 2020 and 2021. According to respondents, this had a negative effect on the learning profit of the students. In March 2021, a total of 70 percent of the students claimed that they learned a little less or a lot less than before the lockdown of universities. Moreover, the share of students who felt lonely increased during the pandemic.

Higher education professors in Russian universities were rather pessimistic about the impact of the distant learning caused by the COVID-19 outbreak on the future of university schooling. Only 14.5 percent of survey respondents believed that the educational system would benefit from distance learning and that higher education would improve, while almost 43 percent strongly disagreed with that, stating that the quality of higher education would worsen as a consequence of the pandemic.

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?

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 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

As a result of the COVID-19 outbreak, many schools switched to distance learning in the United States. Consequently, it is estimated that Black K-12 students lost **** months of learning.

Implications of keeping schools open

School districts across the country have had to make tough decision to switch to online learning. As of February 2021, about a third of schools across the country were teaching virtually. There have been several arguments for keeping schools open, which are centered on the social, mental, and educational development of children. However, many argue that the physical health of children and their families take priority during this unprecedented time. Opponents of opening schools urge the government to find strategies that mitigate the disease and find a solution that fits the needs of all students.

Implications of keeping schools closed

If schools were to remain closed during the pandemic, there would be also other negative side effects. Because of the switch to online learning, it is estimated that if in-classroom instruction resumes by fall 2021, students will have lost about **** months of learning. Furthermore, as of February 2021, nearly a third of parents thought their child was behind where they should be when it came to their reading and writing skills.