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.

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.

In 2024, about **** percent of all students who chose online degree programs in the United States said they did so because COVID-19 made it the only option available to them, a slight decrease from ** percent in the previous year. In both 2023 and 2024, however, the most commonly cited reason for students to choose online degree programs was due to existing commitments, such as work and family, preventing their attendance in campus-based courses.

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 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

Online college courses are a rapidly expanding feature of higher education, yet little research identifies their effects relative to traditional in-person classes. Using an instrumental variables approach, we find that taking a course online, instead of in-person, reduces student success and progress in college. Grades are lower both for the course taken online and in future courses. Students are less likely to remain enrolled at the university. These estimates are local average treatment effects for students with access to both online and in-person options; for other students, online classes may be the only option for accessing college-level courses.

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ABSTRACT: This research, characterized as a qualitative research that adopts an ethnographic perspective, aims to investigate student-student feedback in discussion forums of an online extension university course. The study is based on the discussion about student-student interaction in online courses and different types of feedback. The results, achieved by means of three different tools - analysis of the forum messages, questionnaire and interview -, allowed us to categorize the types of student-student feedback according to their content, indicating the reasons that lead students to provide feedback to their peers and the students' perception on the feedback received.

According to a 2023 survey, ** percent of undergraduate students who were studying online in the United States were White, while ** percent were Black or African-American. In comparison, ** percent of graduate students studying online in the United States in that year were White, while ** percent were Black or African American.

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)

Introduction

E-Learning Statistics: In today’s fast-moving digital world, e-learning has become a key tool for businesses and people who want to keep improving and growing. E-learning is convenient, easy to access, and flexible, making it a game-changer for traditional education. It’s now an essential resource for staying competitive and adaptable in various industries.

Before the global COVID-19 pandemic, online learning was already starting to show up in schools, from elementary through university, as well as in corporate training. Both students and teachers liked the flexibility it offered to everyone taking part in the lessons.

Don't worry; we've put together a list of important E-Learning Statistics for 2024, bringing together the most useful insights in one handy place.

Historical Dataset of Delta Online Learning Academy is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2022-2023),Total Classroom Teachers Trends Over Years (2022-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2022-2023),Hispanic Student Percentage Comparison Over Years (2022-2023),White Student Percentage Comparison Over Years (2022-2023),Diversity Score Comparison Over Years (2022-2023)

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

Historical Dataset of Odyssey Online Learning is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2019-2023),Total Classroom Teachers Trends Over Years (2019-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2019-2020),Asian Student Percentage Comparison Over Years (2022-2023),Hispanic Student Percentage Comparison Over Years (2019-2023),Black Student Percentage Comparison Over Years (2019-2023),White Student Percentage Comparison Over Years (2019-2023),Two or More Races Student Percentage Comparison Over Years (2019-2023),Diversity Score Comparison Over Years (2019-2023),Free Lunch Eligibility Comparison Over Years (2019-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2019-2023),Reading and Language Arts Proficiency Comparison Over Years (2019-2022),Math Proficiency Comparison Over Years (2019-2022),Science Proficiency Comparison Over Years (2021-2022),Overall School Rank Trends Over Years (2019-2022),Graduation Rate Comparison Over Years (2019-2022)

Historical Dataset of Kansas Online Learning Program is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2022-2023),Distribution of Students By Grade Trends,American Indian Student Percentage Comparison Over Years (2022-2023),Asian Student Percentage Comparison Over Years (2022-2023),Hispanic Student Percentage Comparison Over Years (2022-2023),Black Student Percentage Comparison Over Years (2022-2023),White Student Percentage Comparison Over Years (2022-2023),Diversity Score Comparison Over Years (2022-2023)

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 Twinsburg 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,Asian Student Percentage Comparison Over Years (2022-2023),Hispanic Student Percentage Comparison Over Years (2022-2023),Black 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 Fowlerville Online Learning Academy is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2013-2023),Total Classroom Teachers Trends Over Years (2019-2023),Distribution of Students By Grade Trends,American Indian Student Percentage Comparison Over Years (2013-2023),Asian Student Percentage Comparison Over Years (2019-2020),Hispanic Student Percentage Comparison Over Years (2012-2023),Black Student Percentage Comparison Over Years (2012-2022),White Student Percentage Comparison Over Years (2013-2023),Two or More Races Student Percentage Comparison Over Years (2012-2021),Diversity Score Comparison Over Years (2013-2023),Free Lunch Eligibility Comparison Over Years (2013-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2012-2020),Reading and Language Arts Proficiency Comparison Over Years (2012-2022),Math Proficiency Comparison Over Years (2012-2022),Overall School Rank Trends Over Years (2012-2022),Graduation Rate Comparison Over Years (2012-2022)

This dataset has responses from medical students' perceptions of online teaching during the Covid-19 pandemic. A validated questionnaire was used to collect responses from medical students and a focused group discussion(FGD)guide was used for conducting the FGDs. The qualitative dataset includes transcripts of four focused group discussions conducted with medical students regarding their feedback on online learning during the COVID-19 pandemic. The student's perceptions towards online live lectures and recorded lectures are recorded in these discussions.