100+ datasets found
  1. U.S. graduate business students' interest in online/hybrid programs 2023

    • statista.com
    Updated Nov 26, 2024
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    Statista (2024). U.S. graduate business students' interest in online/hybrid programs 2023 [Dataset]. https://www.statista.com/statistics/1448135/north-america-interest-in-online-hybrid-business-school-programs/
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    Dataset updated
    Nov 26, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    North America, United States
    Description

    In 2023, 24 percent of prospective graduate business students in the United States were interested in hybrid programs, an increase from 16 percent in 2019. However, the overall preference in 2023 was for in-person business school programs, at 60 percent.

  2. Opinions of online college students on quality of online education U.S. 2022...

    • statista.com
    Updated Aug 9, 2024
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    Statista (2024). Opinions of online college students on quality of online education U.S. 2022 [Dataset]. https://www.statista.com/statistics/956123/opinions-online-college-students-quality-online-education/
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    Dataset updated
    Aug 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    United States
    Description

    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.

  3. d

    Dataset with determinants or factors influencing graduate economics student...

    • search.dataone.org
    • data.niaid.nih.gov
    • +1more
    Updated Nov 3, 2023
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    Zurika Robinson; Thea Uys (2023). Dataset with determinants or factors influencing graduate economics student preparation and success in an online environment [Dataset]. http://doi.org/10.5061/dryad.bvq83bkgd
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    Dataset updated
    Nov 3, 2023
    Dataset provided by
    Dryad Digital Repository
    Authors
    Zurika Robinson; Thea Uys
    Time period covered
    Jan 1, 2023
    Description

    The data relates to the paper that analyses the determinants or factors that best explain student research skills and success in the honours research report module during the COVID-19 pandemic in 2021. The data used have been gathered through an online survey created on the Qualtrics software package. The research questions were developed from demographic factors and subject knowledge including assignments to supervisor influence and other factors in terms of experience or belonging that played a role (see anonymous link at https://unisa.qualtrics.com/jfe/form/SV_86OZZOdyA5sBurY. An SMS was sent to all students of the 2021 module group to make them aware of the survey. They were under no obligation to complete it and all information was regarded as anonymous. We received 39 responses. The raw data from the survey was processed through the SPSS statistical, software package. The data file contains the demographics, frequencies, descriptives, and open questions processed.     The study...

  4. Online Data Science Training Programs Market Analysis, Size, and Forecast...

    • technavio.com
    Updated Feb 15, 2025
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    Technavio (2025). Online Data Science Training Programs Market Analysis, Size, and Forecast 2025-2029: North America (Mexico), Europe (France, Germany, Italy, and UK), Middle East and Africa (UAE), APAC (Australia, China, India, Japan, and South Korea), South America (Brazil), and Rest of World (ROW) [Dataset]. https://www.technavio.com/report/online-data-science-training-programs-market-industry-analysis
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    Dataset updated
    Feb 15, 2025
    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    Global
    Description

    Snapshot img

    Online Data Science Training Programs Market Size 2025-2029

    The online data science training programs market size is forecast to increase by USD 8.67 billion, at a CAGR of 35.8% between 2024 and 2029.

    The market is experiencing significant growth due to the increasing demand for data science professionals in various industries. The job market offers lucrative opportunities for individuals with data science skills, making online training programs an attractive option for those seeking to upskill or reskill. Another key driver in the market is the adoption of microlearning and gamification techniques in data science training. These approaches make learning more engaging and accessible, allowing individuals to acquire new skills at their own pace. Furthermore, the availability of open-source learning materials has democratized access to data science education, enabling a larger pool of learners to enter the field. However, the market also faces challenges, including the need for continuous updates to keep up with the rapidly evolving data science landscape and the lack of standardization in online training programs, which can make it difficult for employers to assess the quality of graduates. Companies seeking to capitalize on market opportunities should focus on offering up-to-date, high-quality training programs that incorporate microlearning and gamification techniques, while also addressing the challenges of continuous updates and standardization. By doing so, they can differentiate themselves in a competitive market and meet the evolving needs of learners and employers alike.

    What will be the Size of the Online Data Science Training Programs Market during the forecast period?

    Request Free SampleThe online data science training market continues to evolve, driven by the increasing demand for data-driven insights and innovations across various sectors. Data science applications, from computer vision and deep learning to natural language processing and predictive analytics, are revolutionizing industries and transforming business operations. Industry case studies showcase the impact of data science in action, with big data and machine learning driving advancements in healthcare, finance, and retail. Virtual labs enable learners to gain hands-on experience, while data scientist salaries remain competitive and attractive. Cloud computing and data science platforms facilitate interactive learning and collaborative research, fostering a vibrant data science community. Data privacy and security concerns are addressed through advanced data governance and ethical frameworks. Data science libraries, such as TensorFlow and Scikit-Learn, streamline the development process, while data storytelling tools help communicate complex insights effectively. Data mining and predictive analytics enable organizations to uncover hidden trends and patterns, driving innovation and growth. The future of data science is bright, with ongoing research and development in areas like data ethics, data governance, and artificial intelligence. Data science conferences and education programs provide opportunities for professionals to expand their knowledge and expertise, ensuring they remain at the forefront of this dynamic field.

    How is this Online Data Science Training Programs Industry segmented?

    The online data science training programs 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. TypeProfessional degree coursesCertification coursesApplicationStudentsWorking professionalsLanguageR programmingPythonBig MLSASOthersMethodLive streamingRecordedProgram TypeBootcampsCertificatesDegree ProgramsGeographyNorth AmericaUSMexicoEuropeFranceGermanyItalyUKMiddle East and AfricaUAEAPACAustraliaChinaIndiaJapanSouth KoreaSouth AmericaBrazilRest of World (ROW)

    By Type Insights

    The professional degree courses segment is estimated to witness significant growth during the forecast period.The market encompasses various segments catering to diverse learning needs. The professional degree course segment holds a significant position, offering comprehensive and in-depth training in data science. This segment's curriculum covers essential aspects such as statistical analysis, machine learning, data visualization, and data engineering. Delivered by industry professionals and academic experts, these courses ensure a high-quality education experience. Interactive learning environments, including live lectures, webinars, and group discussions, foster a collaborative and engaging experience. Data science applications, including deep learning, computer vision, and natural language processing, are integral to the market's growth. Data analysis, a crucial application, is gaining traction due to the increasing demand

  5. Bachelor's students graduated from Italian online universities 2013-2024

    • statista.com
    • ai-chatbox.pro
    Updated May 16, 2025
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    Statista (2025). Bachelor's students graduated from Italian online universities 2013-2024 [Dataset]. https://www.statista.com/statistics/1088192/graduate-students-at-an-online-university-in-italy/
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    Dataset updated
    May 16, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Italy
    Description

    Between 2015 and 2024, the number of bachelor's students who graduated from online universities in Italy steadily increased. In 2015, less than ***** people obtained their bachelor's from an online university. After nine years, the number of students more than doubled, reaching ****** graduates. In Italy, bachelor's students represented the largest group of e-learning university students, ******* people.

  6. Data from: College Completion Dataset

    • kaggle.com
    Updated Dec 6, 2022
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    The Devastator (2022). College Completion Dataset [Dataset]. https://www.kaggle.com/datasets/thedevastator/boost-student-success-with-college-completion-da
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 6, 2022
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    The Devastator
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    College Completion Dataset

    Graduation Rates, Race, Efficiency Measures and More

    By Jonathan Ortiz [source]

    About this dataset

    This College Completion dataset provides an invaluable insight into the success and progress of college students in the United States. It contains graduation rates, race and other data to offer a comprehensive view of college completion in America. The data is sourced from two primary sources – the National Center for Education Statistics (NCES)’ Integrated Postsecondary Education System (IPEDS) and Voluntary System of Accountability’s Student Success and Progress rate.

    At four-year institutions, the graduation figures come from IPEDS for first-time, full-time degree seeking students at the undergraduate level, who entered college six years earlier at four-year institutions or three years earlier at two-year institutions. Furthermore, colleges report how many students completed their program within 100 percent and 150 percent of normal time which corresponds with graduation within four years or six year respectively. Students reported as being of two or more races are included in totals but not shown separately

    When analyzing race and ethnicity data NCES have classified student demographics since 2009 into seven categories; White non-Hispanic; Black non Hispanic; American Indian/ Alaskan native ; Asian/ Pacific Islander ; Unknown race or ethnicity ; Non resident with two new categorize Native Hawaiian or Other Pacific Islander combined with Asian plus students belonging to several races. Also worth noting is that different classifications for graduate data stemming from 2008 could be due to variations in time frame examined & groupings used by particular colleges – those who can’t be identified from National Student Clearinghouse records won’t be subjected to penalty by these locations .

    When it comes down to efficiency measures parameters like “Awards per 100 Full Time Undergraduate Students which includes all undergraduate completions reported by a particular institution including associate degrees & certificates less than 4 year programme will assist us here while we also take into consideration measures like expenditure categories , Pell grant percentage , endowment values , average student aid amounts & full time faculty members contributing outstandingly towards instructional research / public service initiatives .

    When trying to quantify outcomes back up Median Estimated SAT score metric helps us when it is derived either on 25th percentile basis / 75th percentile basis with all these factors further qualified by identifying required criteria meeting 90% threshold when incoming students are considered for relevance . Last but not least , Average Student Aid equalizes amount granted by institution dividing same over total sum received against what was allotted that particular year .

    All this analysis gives an opportunity get a holistic overview about performance , potential deficits &

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    How to use the dataset

    This dataset contains data on student success, graduation rates, race and gender demographics, an efficiency measure to compare colleges across states and more. It is a great source of information to help you better understand college completion and student success in the United States.

    In this guide we’ll explain how to use the data so that you can find out the best colleges for students with certain characteristics or focus on your target completion rate. We’ll also provide some useful tips for getting the most out of this dataset when seeking guidance on which institutions offer the highest graduation rates or have a good reputation for success in terms of completing programs within normal timeframes.

    Before getting into specifics about interpreting this dataset, it is important that you understand that each row represents information about a particular institution – such as its state affiliation, level (two-year vs four-year), control (public vs private), name and website. Each column contains various demographic information such as rate of awarding degrees compared to other institutions in its sector; race/ethnicity Makeup; full-time faculty percentage; median SAT score among first-time students; awards/grants comparison versus national average/state average - all applicable depending on institution location — and more!

    When using this dataset, our suggestion is that you begin by forming a hypothesis or research question concerning student completion at a given school based upon observable characteristics like financ...

  7. Graduate outcomes (LEO): 2015 to 2016

    • gov.uk
    Updated Mar 25, 2021
    + more versions
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    Graduate outcomes (LEO): 2015 to 2016 [Dataset]. https://www.gov.uk/government/statistics/graduate-outcomes-2015-to-2016
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    Dataset updated
    Mar 25, 2021
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Education
    Description

    There are errors in this release due to a coding error. Please do not use figures reported in this publication for these countries:

    • Germany is incorrectly labelled as Denmark
    • Greece is incorrectly labelled as Germany

    We have correct data in the graduate outcomes (LEO): 2018 to 2019 publication and corrected the outcomes and earnings data for all previously reported tax years and graduating cohorts.

    The longitudinal education outcomes (LEO) data includes:

    • information from the Department for Education (DfE)
    • information from the Department for Work and Pensions (DWP) and Her Majesty’s Revenue and Customs (HMRC)

    This experimental release uses LEO data to look at employment and earnings outcomes of higher education graduates 1, 2, 5 and 10 years after graduation in the tax years 2014 to 2015 and 2015 to 2016.

    The outcomes update previously published figures by including data for the 2015 to 2016 tax year. This publication also includes outcomes for EU and overseas students for the first time and extends the coverage to include those that studied first degrees in further education colleges.

    Higher education statistics team (LEO)

    Matthew Bridge
    Department for Education
    2 St. Paul's Place
    125 Norfolk Street
    Sheffield
    S1 2FJ

    Email mailto:he.leo@education.gov.uk">he.leo@education.gov.uk

    Phone 07384 456648

  8. o

    International STEM Graduate Student in the United States Survey 2015

    • openicpsr.org
    delimited
    Updated Aug 10, 2015
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    Xueying Han; Richard Appelbaum; Galen Stocking; Matthew Gebbie (2015). International STEM Graduate Student in the United States Survey 2015 [Dataset]. http://doi.org/10.3886/E100084V1
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    delimitedAvailable download formats
    Dataset updated
    Aug 10, 2015
    Dataset provided by
    University of California Santa Barbara
    Pew Research
    Authors
    Xueying Han; Richard Appelbaum; Galen Stocking; Matthew Gebbie
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 5, 2015 - Apr 30, 2015
    Area covered
    United States
    Description

    The International STEM Graduate Student Survey assesses why international students are coming to the United States for their graduate studies, the challenges they have faced while studying in the US, their future career plans, and whether they wish to stay or leave the US upon graduation. According to the Survey of Earned Doctorates by the National Science Foundation and the National Center for Science and Engineering Statistics, international students accounted for over 40% of all US doctoral graduates in STEM in 2013. The factors that influence international students' decisions to study in the US and whether they will stay or leave are important to US economic competitiveness. We contacted graduate students (both domestic and international) in STEM disciplines from the top 10 universities ranked by the total number of enrolled international students. We estimate that we contacted approximately 15,990 students. Individuals were asked to taken an online survey regarding their background, reasons for studying in the US, and whether they plan to stay or leave the US upon graduation. We received a total of 2,322 completed surveys, giving us a response rate of 14.5%. 1,535 of the completed were from domestic students and 787 of which were from international students. Raw survey data are presented here.Survey participants were contacted via Qualtrics to participate in this survey. The Universe of this survey data set pertains to all graduate students (Master's and PhD) in STEM disciplines from the following universities: Columbia University, University of Illinois-Urbana Champaign, Michigan State University, Northeastern University, Purdue University, University of Southern California, Arizona State University, University of California at Los Angeles, New York University, University of Washington at Seattle. Data are broken into 2 subsets: one for international STEM graduate students and one for domestic STEM graduate students, please see respective files.

  9. Share of students studying online in the U.S., by ethnicity and education...

    • statista.com
    Updated Apr 15, 2025
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    Statista (2025). Share of students studying online in the U.S., by ethnicity and education level 2023 [Dataset]. https://www.statista.com/statistics/956166/share-students-studying-online-ethnicity-education-level/
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    Dataset updated
    Apr 15, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    According to a 2023 survey, 70 percent of undergraduate students who were studying online in the United States were White while 23 percent were Black or African-American. In comparison, 69 percent of graduate students studying online in the United States in that year were White while 24 percent were Black or African American.

  10. p

    Odyssey Online Learning

    • publicschoolreview.com
    json, xml
    Updated Oct 14, 2020
    + more versions
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    Public School Review (2020). Odyssey Online Learning [Dataset]. https://www.publicschoolreview.com/odyssey-online-learning-profile
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    json, xmlAvailable download formats
    Dataset updated
    Oct 14, 2020
    Dataset authored and provided by
    Public School Review
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2019 - Dec 31, 2025
    Description

    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)

  11. m

    WHM Graduate Outcomes Online Survey 2018-2023

    • data.mendeley.com
    • researchdata.edu.au
    Updated Apr 12, 2024
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    Philippa Martyr (2024). WHM Graduate Outcomes Online Survey 2018-2023 [Dataset]. http://doi.org/10.17632/wyy889n8w7.1
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    Dataset updated
    Apr 12, 2024
    Authors
    Philippa Martyr
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This deidentified Excel qualitative data set contains graduate outcomes and graduates' views on the skills they acquired while completing the Women's Health Minor (WHM) at the University of Western Australia (UWA) between 2018 and 2023. Data showed that this self-selected sample of graduates (N=38) had acquired new and diverse skills while completing the WHM.

  12. Recent College Graduates Survey, 1985-1986: [United States]

    • icpsr.umich.edu
    ascii, sas, spss
    Updated Aug 6, 2001
    + more versions
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    Recent College Graduates Survey, 1985-1986: [United States] [Dataset]. https://www.icpsr.umich.edu/web/ICPSR/studies/6380
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    sas, spss, asciiAvailable download formats
    Dataset updated
    Aug 6, 2001
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    United States Department of Education. National Center for Education Statistics
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/6380/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/6380/terms

    Time period covered
    1985 - 1986
    Area covered
    United States
    Description

    The Recent College Graduates (RCG) survey estimates the potential supply of newly qualified teachers in the United States and explores the immediate post-degree employment and education experiences of individuals obtaining bachelor's or master's degrees from American colleges and universities. The RCG survey, which focuses heavily, but not exclusively, on those graduates qualified to teach at the elementary and secondary levels, is designed to meet the following objectives: (1) to determine how many graduates become eligible or qualified to teach for the first time and how many are employed as teachers in the year following graduation, by teaching field, (2) to examine the relationship between courses taken, student achievement, and occupational outcomes, and (3) to monitor unemployment rates and average salaries of graduates by field of study. The RCG survey collects information on education and employment of all graduates (date of graduation, field of study, whether newly qualified to teach, further enrollment, financial aid, employment status, and teacher employment characteristics), as well as standard demographic characteristics such as earnings, age, marital status, sex, and race/ethnicity.

  13. TONS (Training Online Nomination System) Training Master File

    • catalog.data.gov
    Updated May 22, 2025
    + more versions
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    Social Security Administration (2025). TONS (Training Online Nomination System) Training Master File [Dataset]. https://catalog.data.gov/dataset/tons-training-online-nomination-system-training-master-file
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    Dataset updated
    May 22, 2025
    Dataset provided by
    Social Security Administrationhttp://www.ssa.gov/
    Description

    A file that holds the master records for all online training courses nominated for reimbursement.

  14. o

    Online Credit Recovery Study: Effects on High School Students' Proximal and...

    • openicpsr.org
    Updated May 6, 2024
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    Jordan Rickles; Sarah Peko-Spicer; Kyle Neering (2024). Online Credit Recovery Study: Effects on High School Students' Proximal and Distal Outcomes [Dataset]. http://doi.org/10.3886/E202181V1
    Explore at:
    Dataset updated
    May 6, 2024
    Dataset provided by
    American Institutes for Research
    Authors
    Jordan Rickles; Sarah Peko-Spicer; Kyle Neering
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    California, Los Angeles
    Description

    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

  15. p

    Karval Online Education

    • publicschoolreview.com
    json, xml
    Updated Dec 2, 2022
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    Public School Review (2022). Karval Online Education [Dataset]. https://www.publicschoolreview.com/karval-online-education-profile
    Explore at:
    json, xmlAvailable download formats
    Dataset updated
    Dec 2, 2022
    Dataset authored and provided by
    Public School Review
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2005 - Dec 31, 2025
    Area covered
    Karval
    Description

    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)

  16. p

    Michigan Online School

    • publicschoolreview.com
    json, xml
    Updated Jun 13, 2024
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    Public School Review (2024). Michigan Online School [Dataset]. https://www.publicschoolreview.com/michigan-online-school-profile
    Explore at:
    xml, jsonAvailable download formats
    Dataset updated
    Jun 13, 2024
    Dataset authored and provided by
    Public School Review
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2018 - Dec 31, 2025
    Area covered
    Michigan
    Description

    Historical Dataset of Michigan Online School 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 (2019-2023),American Indian Student Percentage Comparison Over Years (2019-2023),Asian Student Percentage Comparison Over Years (2019-2023),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 (2021-2023),Diversity Score Comparison Over Years (2019-2023),Free Lunch Eligibility Comparison Over Years (2019-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2019-2022),Reading and Language Arts Proficiency Comparison Over Years (2018-2022),Math Proficiency Comparison Over Years (2018-2022),Science Proficiency Comparison Over Years (2021-2022),Overall School Rank Trends Over Years (2018-2022),Graduation Rate Comparison Over Years (2019-2022)

  17. o

    Bridging the gap: students' responses to online materials to equip graduate...

    • ordo.open.ac.uk
    • search.datacite.org
    docx
    Updated May 30, 2023
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    Stephanie Pywell (2023). Bridging the gap: students' responses to online materials to equip graduate entrants to a law degree with essential subject knowledge and skills [Dataset]. http://doi.org/10.21954/ou.rd.5368810.v1
    Explore at:
    docxAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    The Open University
    Authors
    Stephanie Pywell
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This file set is the basis of a project in which Stephanie Pywell from The Open University Law School created and evaluated some online teaching materials – Fundamentals of Law (FoLs) – to fill a gap in the knowledge of graduate entrants to the Bachelor of Laws (LLB) programme. These students are granted exemption from the Level 1 law modules, from which they would normally acquire the basic knowledge of legal principles and methods that is essential to success in higher-level study. The materials consisted of 12 sessions of learning, each covering one key topic from a Level 1 law module.The dataset includes a Word document that consists of the text of a five-question, multiple-choice Moodle poll, together with the coding for each response option.The rest of the dataset consists of spreadsheets and outputs from SPSS and Excel showing the analyses that were conducted on the cleaned and anonymised data to ascertain students' use of, and views on, the teaching materials, and to explore any statistical association between students' studying of the materials and their academic success on Level 2 law modules, W202 and W203.Students were asked to complete the Moodle poll at the end of every session of study, of which there were 1,013. Only one answer from each of the 240 respondents was retained for Questions 3, 4 and 5, to avoid skewing the data. Some data are presented as percentages of the number of sessions studied; some are presented as percentages of the number of respondents, and some are presented as percentage of the number of respondents who meet specific criteria.Student identifiers, which have been removed to ensure anonymity, are as follows: Open University Computer User code (OUCU) and Personal Identifier (PI). These were used to collate the output from the Moodle poll with students' Level 2 module results.

  18. p

    Great Lakes Online Education

    • publicschoolreview.com
    json, xml
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    Public School Review, Great Lakes Online Education [Dataset]. https://www.publicschoolreview.com/great-lakes-online-education-profile
    Explore at:
    xml, jsonAvailable download formats
    Dataset authored and provided by
    Public School Review
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2015 - Dec 31, 2025
    Description

    Historical Dataset of Great Lakes Online Education is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2015-2023),Total Classroom Teachers Trends Over Years (2015-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2015-2023),American Indian Student Percentage Comparison Over Years (2015-2023),Asian Student Percentage Comparison Over Years (2015-2023),Hispanic Student Percentage Comparison Over Years (2016-2023),Black Student Percentage Comparison Over Years (2015-2020),White Student Percentage Comparison Over Years (2015-2023),Two or More Races Student Percentage Comparison Over Years (2019-2023),Diversity Score Comparison Over Years (2015-2023),Free Lunch Eligibility Comparison Over Years (2015-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2015-2023),Reading and Language Arts Proficiency Comparison Over Years (2015-2022),Math Proficiency Comparison Over Years (2015-2022),Science Proficiency Comparison Over Years (2021-2022),Overall School Rank Trends Over Years (2015-2022),Graduation Rate Comparison Over Years (2016-2022)

  19. p

    Gwinnett Online Campus

    • publicschoolreview.com
    json, xml
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    Public School Review, Gwinnett Online Campus [Dataset]. https://www.publicschoolreview.com/gwinnett-online-campus-profile
    Explore at:
    json, xmlAvailable download formats
    Dataset authored and provided by
    Public School Review
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2012 - Dec 31, 2025
    Area covered
    Gwinnett County
    Description

    Historical Dataset of Gwinnett Online Campus 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 (2013-2023),Hispanic Student Percentage Comparison Over Years (2013-2023),Black Student Percentage Comparison Over Years (2013-2023),White Student Percentage Comparison Over Years (2013-2023),Two or More Races 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 (2012-2022),Math Proficiency Comparison Over Years (2012-2022),Science Proficiency Comparison Over Years (2021-2022),Overall School Rank Trends Over Years (2012-2022),Graduation Rate Comparison Over Years (2012-2022)

  20. d

    Data from: Faculty Perspectives on a Collaborative, Multi-Institutional...

    • search.dataone.org
    • beta.hydroshare.org
    • +1more
    Updated Dec 30, 2023
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    Anne J Jefferson; Deanna H. McCay; Steven Loheide (2023). Faculty Perspectives on a Collaborative, Multi-Institutional Online Hydrology Graduate Student Training Program [Dataset]. http://doi.org/10.4211/hs.2372f0c0a90d4061ae7f50a7f2a01cbd
    Explore at:
    Dataset updated
    Dec 30, 2023
    Dataset provided by
    Hydroshare
    Authors
    Anne J Jefferson; Deanna H. McCay; Steven Loheide
    Time period covered
    Dec 1, 2021 - May 31, 2022
    Description

    This resource contains the survey questions, compiled results, and code for Fisher's exact test, as associated with the following manuscript:

    "Faculty Perspectives on a Collaborative, Multi-Institutional Online Hydrology Graduate Student Training Program" by Anne J. Jefferson, Steven P. Loheide, and Deanna H. McCay. Submitted to Frontiers in Water, in the research topic: “Innovations in Remote and Online Education by Hydrologic Scientists", May 2022

    Abstract: The CUAHSI Virtual University is an interinstitutional graduate training framework that was developed to increase access to specialized hydrology courses for graduate students from participating institutions. The program was designed to capitalize on the benefits of collaborative teaching, allowing students to differentiate their learning and access subject matter experts at multiple institutions, while enrolled in a single course at their home institution, through a framework of reciprocity. Although the CUAHSI Virtual University was developed prior to the covid-19 pandemic, the resilience of its online education model to such disruptions to classroom teaching increases the urgency of understanding how effective such an approach is at achieving its goals and what challenges multi-institutional graduate training faces for sustainability and expansion within the water sciences or in other disciplines. To gain faculty perspectives on the program, we surveyed water science faculty who had served as instructors in the program, as well as water science faculty who had not participated and departmental chairs of participating instructors. Our data show widespread agreement across respondent types that the program is positive for students, diversifying their educational opportunities and increasing access to subject matter experts. Concerns and factors limiting faculty participation revolved around faculty workload and administrative barriers, including low enrollment at individual institutions. If these barriers can be surmounted, the CUAHSI Virtual University has the potential for wider participation within hydrology and adoption in other STEM disciplines.

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Statista (2024). U.S. graduate business students' interest in online/hybrid programs 2023 [Dataset]. https://www.statista.com/statistics/1448135/north-america-interest-in-online-hybrid-business-school-programs/
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U.S. graduate business students' interest in online/hybrid programs 2023

Explore at:
Dataset updated
Nov 26, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
North America, United States
Description

In 2023, 24 percent of prospective graduate business students in the United States were interested in hybrid programs, an increase from 16 percent in 2019. However, the overall preference in 2023 was for in-person business school programs, at 60 percent.

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