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.

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 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.

This statistic shows the distribution of target populations of online education programs in the United States in 2019. In 2019, 79 percent of respondents stated that their online education programs were aimed at adult students returning to school after an absence.

In 2024, Southern New Hampshire University was ranked as the best distance learning institution in the United States, with 96 percent of its students enrolled online. University of Florida, Florida International University, University of Minnesota-Twin Cities, and University of Utah rounded out the top five.

Please cite the following paper when using this dataset:N. Thakur, “A Large-Scale Dataset of Twitter Chatter about Online Learning during the Current COVID-19 Omicron Wave,” Journal of Data, vol. 7, no. 8, p. 109, Aug. 2022, doi: 10.3390/data7080109AbstractThe COVID-19 Omicron variant, reported to be the most immune evasive variant of COVID-19, is resulting in a surge of COVID-19 cases globally. This has caused schools, colleges, and universities in different parts of the world to transition to online learning. As a result, social media platforms such as Twitter are seeing an increase in conversations, centered around information seeking and sharing, related to online learning. Mining such conversations, such as Tweets, to develop a dataset can serve as a data resource for interdisciplinary research related to the analysis of interest, views, opinions, perspectives, attitudes, and feedback towards online learning during the current surge of COVID-19 cases caused by the Omicron variant. Therefore this work presents a large-scale public Twitter dataset of conversations about online learning since the first detected case of the COVID-19 Omicron variant in November 2021. The dataset is compliant with the privacy policy, developer agreement, and guidelines for content redistribution of Twitter and the FAIR principles (Findability, Accessibility, Interoperability, and Reusability) principles for scientific data management.Data DescriptionThe dataset comprises a total of 52,984 Tweet IDs (that correspond to the same number of Tweets) about online learning that were posted on Twitter from 9th November 2021 to 13th July 2022. The earliest date was selected as 9th November 2021, as the Omicron variant was detected for the first time in a sample that was collected on this date. 13th July 2022 was the most recent date as per the time of data collection and publication of this dataset.The dataset consists of 9 .txt files. An overview of these dataset files along with the number of Tweet IDs and the date range of the associated tweets is as follows. Filename: TweetIDs_November_2021.txt (No. of Tweet IDs: 1283, Date Range of the associated Tweet IDs: November 1, 2021 to November 30, 2021)Filename: TweetIDs_December_2021.txt (No. of Tweet IDs: 10545, Date Range of the associated Tweet IDs: December 1, 2021 to December 31, 2021)Filename: TweetIDs_January_2022.txt (No. of Tweet IDs: 23078, Date Range of the associated Tweet IDs: January 1, 2022 to January 31, 2022)Filename: TweetIDs_February_2022.txt (No. of Tweet IDs: 4751, Date Range of the associated Tweet IDs: February 1, 2022 to February 28, 2022)Filename: TweetIDs_March_2022.txt (No. of Tweet IDs: 3434, Date Range of the associated Tweet IDs: March 1, 2022 to March 31, 2022)Filename: TweetIDs_April_2022.txt (No. of Tweet IDs: 3355, Date Range of the associated Tweet IDs: April 1, 2022 to April 30, 2022)Filename: TweetIDs_May_2022.txt (No. of Tweet IDs: 3120, Date Range of the associated Tweet IDs: May 1, 2022 to May 31, 2022)Filename: TweetIDs_June_2022.txt (No. of Tweet IDs: 2361, Date Range of the associated Tweet IDs: June 1, 2022 to June 30, 2022)Filename: TweetIDs_July_2022.txt (No. of Tweet IDs: 1057, Date Range of the associated Tweet IDs: July 1, 2022 to July 13, 2022)The dataset contains only Tweet IDs in compliance with the terms and conditions mentioned in the privacy policy, developer agreement, and guidelines for content redistribution of Twitter. The Tweet IDs need to be hydrated to be used. For hydrating this dataset the Hydrator application (link to download and a step-by-step tutorial on how to use Hydrator) may be used.The list of all the synonyms or terms that were used for the dataset development is as follows:COVID-19: Omicron, COVID, COVID19, coronavirus, coronaviruspandemic, COVID-19, corona, coronaoutbreak, omicron variant, SARS CoV-2, corona virusonline learning: online education, online learning, remote education, remote learning, e-learning, elearning, distance learning, distance education, virtual learning, virtual education, online teaching, remote teaching, virtual teaching, online class, online classes, remote class, remote classes, distance class, distance classes, virtual class, virtual classes, online course, online courses, remote course, remote courses, distance course, distance courses, virtual course, virtual courses, online school, virtual school, remote school, online college, online university, virtual college, virtual university, remote college, remote university, online lecture, virtual lecture, remote lecture, online lectures, virtual lectures, remote lectures

Percentage of Canadians' use of selected online activities, during the past three months.

During a 2023 survey, 25 percent of responding internet users who were studying online say they do so because they want a more complete curriculum, or they want to keep up to date.

Duolingo was the most popular online education mobile app by downloads in Poland in 2024, which amounted to 1.9 million on iPhone and iPad App Store and Google Play. Knowunity followed with approximately 699 thousand downloads.

As of May 2023, around 152,000 students were enrolled at an online bachelor's program in Italy. In addition, 47,000 individuals chose e-learning for their master's studies. Among the largest Italian universities, the Pegaso online University ranks at the second place, nationwide. In the academic year 2022/2023, the e-learning institute had more than 95,000 enrolled students.

In 2023, the most common advice offered by alumni of online higher education programs in the United States, suggested by 30 percent of alumni, was to do more research about cost and financial aid. A further 22 percent of alumni of online programs said to compare more programs when researching schools.

According to a survey conducted in 2024, 29 percent of current, prospective, and former online students in the United States expressed some concern about balancing education with work, family, and household obligations. A further 16 percent of respondents were concerned about the quality of online instruction and academic support.

According to a survey conducted in 2024, seven percent of college students reported studying Arts and Humanities online in the United States, compared to 23 percent who studied business online.

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

This chart provides a detailed overview of the number of Jobs & Education online retailers by Number of Employee. Most Jobs & Education stores' Number of Employee are Less than 10, there are 20.46K stores, which is 81.05% of total. In second place, 920 stores' Number of Employee are 20 to 50, which is 3.65% of total. Meanwhile, 810 stores' Number of Employee are 10 to 20, which is 3.21% of total. This breakdown reveals insights into Jobs & Education stores distribution, providing a comprehensive picture of the performance and efficient of online retailer.

Learning Management System online courses for USAID staff to access.

Dual Enrollment Programs and Courses for High School Students, 2002-03 (PEQIS 14), is a study that is part of the Postsecondary Education Quick Information System (PEQIS) program; program data is available since 1997 at . PEQIS 14 (https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2009045) is a cross-sectional survey that collected information on the topic of dual enrollment of high school students at postsecondary institutions. 1,600 Title IV degree-granting postsecondary institutions in the 50 United States and the District of Columbia were sampled. The study was conducted using online or paper surveys. The overall response rates were 92 percent weighted and 91 percent unweighted. Key statistics produced from PEQIS 14 were information on the prevalence of college course-taking by high school students at their institutions during the 2002-03 12-month academic year, both within and outside of dual enrollment programs. Among institutions with dual enrollment programs, additional information was obtained on the characteristics of programs, including course location and type of instructors, program and course curriculum, academic eligibility requirements, and funding.

The dataset contains quantitative information concerning university students' usage of online discussion areas and the impact of the students' participation on their final results.The data includes the following categories of information:• student age (whole years at the end of semester);• student gender (male or female);• student normal mode of study (on-campus or off-campus);• student course of study (BTech, BE or other);• student prior general academic performance (measured at Deakin University by the weighted average mark [WAM]);• the total number of discussion messages read (or at least opened) by the student;• the total number of new/initial discussion postings made by the student;• the total number of follow-up/reply discussion postings made by the student; and• the final unit mark obtained by the student.

Reliability statistics for factors that determine online courses teaching.

The Open University (OU) dataset is an open database containing student demographic and click-stream interaction with the virtual learning platform. The available data are structured in different CSV files. You can find more information about the original dataset at the following link: https://analyse.kmi.open.ac.uk/open_dataset.

We extracted a subset of the original dataset that focuses on student information. 25,819 records were collected referring to a specific student, course and semester. Each record is described by the following 20 attributes: code_module, code_presentation, gender, highest_education, imd_band, age_band, num_of_prev_attempts, studies_credits, disability, resource, homepage, forum, glossary, outcontent, subpage, url, outcollaborate, quiz, AvgScore, count.

Two target classes were considered, namely Fail and Pass, combining the original four classes (Fail and Withdrawn and Pass and Distinction, respectively). The final_result attribute contains the target values.

All features have been converted to numbers for automatic processing.

Below is the mapping used to convert categorical values to numeric:

• code_module: 'AAA'=0, 'BBB'=1, 'CCC'=2, 'DDD'=3, 'EEE'=4, 'FFF'=5, 'GGG'=6
• code_presentation: '2013B'=0, '2013J'=1, '2014B'=2, '2014J'=3
• gender: 'F'=0, 'M'=1
• highest_education: 'No_Formal_quals'=0, 'Post_Graduate_Qualification'=1, 'HE_Qualification'=2, 'Lower_Than_A_Level'=3, 'A_level_or_Equivalent'=4
• IMBD_band: 'unknown'=0, 'between_0_and_10_percent'=1, 'between_10_and_20_percent'=2, 'between_20_and_30_percent'=3, 'between_30_and_40_percent'=4, 'between_40_and_50_percent'=5, 'between_50_and_60_percent'=6, 'between_60_and_70_percent'=7, 'between_70_and_80_percent'=8, 'between_80_and_90_percent'=9, 'between_90_and_100_percent'=10
• age_band: 'between_0_and_35'=0, 'between_35_and_55'=1, 'higher_than_55'=2
• disability: 'N'=0, 'Y'=1
• student's outcome: 'Fail'=0, 'Pass'=1

For more detailed information, please refer to:

Casalino G., Castellano G., Vessio G. (2021) Exploiting Time in Adaptive Learning from Educational Data. In: Agrati L.S. et al. (eds) Bridges and Mediation in Higher Distance Education. HELMeTO 2020. Communications in Computer and Information Science, vol 1344. Springer, Cham. https://doi.org/10.1007/978-3-030-67435-9_1