During a global survey of students conducted in mid-2024, it was found that a whopping 86 percent said they were using artificial intelligence tools in their schoolwork. Almost a fourth of them used it on a daily basis.

The data here is from the report entitled Trends in Enrollment, Credit Attainment, and Remediation at Connecticut Public Universities and Community Colleges: Results from P20WIN for the High School Graduating Classes of 2010 through 2016.

The report answers three questions: 1. Enrollment: What percentage of the graduating class enrolled in a Connecticut public university or community college (UCONN, the four Connecticut State Universities, and 12 Connecticut community colleges) within 16 months of graduation? 2. Credit Attainment: What percentage of those who enrolled in a Connecticut public university or community college within 16 months of graduation earned at least one year’s worth of credits (24 or more) within two years of enrollment? 3. Remediation: What percentage of those who enrolled in one of the four Connecticut State Universities or one of the 12 community colleges within 16 months of graduation took a remedial course within two years of enrollment?

Notes on the data: School Credit: % Earning 24 Credits is a subset of the % Enrolled in 16 Months. School Remediation: % Enrolled in Remediation is a subset of the % Enrolled in 16 Months.

Course Success rate is the percent of students obtaining grades A‐C and P out of the total number of students enrolled at the beginning of the term. Course success is the building block toward student program completion. Without successful completion of courses, City Colleges of Chicago students will not be able to earn credits toward a degree or certificate, nor will they progress from remedial to college-level coursework.

This measure reports the percentage of offenders who are currently living in residential facilities supervised by Iowa Community Based Corrections who have or are working towards a post-secondary education degree. It includes offenders where the highest level of education completed is one of the following: In College, Freshman level college, Sophomore level college, Junior level college, Vocational/Technical Student, Technical Training Completion, Vocational Program/Technical Certificate, Associate's Degree, Bachelor's Degree, Master's Degree, or Doctorate.

Analysis of ‘College Basketball Dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/andrewsundberg/college-basketball-dataset on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Content

Data from the 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, and 2021 Division I college basketball seasons.

cbb.csv has seasons 2013-2019 combined

The 2020 season's data set is kept separate from the other seasons, because there was no postseason due to the Coronavirus.

The 2021 data is from 3/15/2021 and will be updated and added to cbb.csv after the tournament

Variables

RK (Only in cbb20): The ranking of the team at the end of the regular season according to barttorvik

TEAM: The Division I college basketball school

CONF: The Athletic Conference in which the school participates in (A10 = Atlantic 10, ACC = Atlantic Coast Conference, AE = America East, Amer = American, ASun = ASUN, B10 = Big Ten, B12 = Big 12, BE = Big East, BSky = Big Sky, BSth = Big South, BW = Big West, CAA = Colonial Athletic Association, CUSA = Conference USA, Horz = Horizon League, Ivy = Ivy League, MAAC = Metro Atlantic Athletic Conference, MAC = Mid-American Conference, MEAC = Mid-Eastern Athletic Conference, MVC = Missouri Valley Conference, MWC = Mountain West, NEC = Northeast Conference, OVC = Ohio Valley Conference, P12 = Pac-12, Pat = Patriot League, SB = Sun Belt, SC = Southern Conference, SEC = South Eastern Conference, Slnd = Southland Conference, Sum = Summit League, SWAC = Southwestern Athletic Conference, WAC = Western Athletic Conference, WCC = West Coast Conference)

G: Number of games played

W: Number of games won

ADJOE: Adjusted Offensive Efficiency (An estimate of the offensive efficiency (points scored per 100 possessions) a team would have against the average Division I defense)

ADJDE: Adjusted Defensive Efficiency (An estimate of the defensive efficiency (points allowed per 100 possessions) a team would have against the average Division I offense)

BARTHAG: Power Rating (Chance of beating an average Division I team)

EFG_O: Effective Field Goal Percentage Shot

EFG_D: Effective Field Goal Percentage Allowed

TOR: Turnover Percentage Allowed (Turnover Rate)

TORD: Turnover Percentage Committed (Steal Rate)

ORB: Offensive Rebound Rate

DRB: Offensive Rebound Rate Allowed

FTR : Free Throw Rate (How often the given team shoots Free Throws)

FTRD: Free Throw Rate Allowed

2P_O: Two-Point Shooting Percentage

2P_D: Two-Point Shooting Percentage Allowed

3P_O: Three-Point Shooting Percentage

3P_D: Three-Point Shooting Percentage Allowed

ADJ_T: Adjusted Tempo (An estimate of the tempo (possessions per 40 minutes) a team would have against the team that wants to play at an average Division I tempo)

WAB: Wins Above Bubble (The bubble refers to the cut off between making the NCAA March Madness Tournament and not making it)

POSTSEASON: Round where the given team was eliminated or where their season ended (R68 = First Four, R64 = Round of 64, R32 = Round of 32, S16 = Sweet Sixteen, E8 = Elite Eight, F4 = Final Four, 2ND = Runner-up, Champion = Winner of the NCAA March Madness Tournament for that given year)

SEED: Seed in the NCAA March Madness Tournament

YEAR: Season

Acknowledgements

This data was scraped from from http://barttorvik.com/trank.php#. I cleaned the data set and added the POSTSEASON, SEED, and YEAR columns

--- Original source retains full ownership of the source dataset ---

The social environment represents the external conditions under which people engage in social activity within their community. It includes aspects of social opportunity, leisure and recreation, education, access to health services, health status and participation in democratic processes. Fourteen indicators have been used to assess aspects of quality of the social environment.

This table contains data on the percent of population age 25 and up with a four-year college degree or higher for California, its regions, counties, county subdivisions, cities, towns, and census tracts. Greater educational attainment has been associated with health-promoting behaviors including consumption of fruits and vegetables and other aspects of healthy eating, engaging in regular physical activity, and refraining from excessive consumption of alcohol and from smoking. Completion of formal education (e.g., high school) is a key pathway to employment and access to healthier and higher paying jobs that can provide food, housing, transportation, health insurance, and other basic necessities for a healthy life. Education is linked with social and psychological factors, including sense of control, social standing and social support. These factors can improve health through reducing stress, influencing health-related behaviors and providing practical and emotional support. More information on the data table and a data dictionary can be found in the Data and Resources section. The educational attainment table is part of a series of indicators in the Healthy Communities Data and Indicators Project (HCI) of the Office of Health Equity. The goal of HCI is to enhance public health by providing data, a standardized set of statistical measures, and tools that a broad array of sectors can use for planning healthy communities and evaluating the impact of plans, projects, policy, and environmental changes on community health. The creation of healthy social, economic, and physical environments that promote healthy behaviors and healthy outcomes requires coordination and collaboration across multiple sectors, including transportation, housing, education, agriculture and others. Statistical metrics, or indicators, are needed to help local, regional, and state public health and partner agencies assess community environments and plan for healthy communities that optimize public health. More information on HCI can be found here: https://www.cdph.ca.gov/Programs/OHE/CDPH%20Document%20Library/Accessible%202%20CDPH_Healthy_Community_Indicators1pager5-16-12.pdf

The format of the educational attainment table is based on the standardized data format for all HCI indicators. As a result, this data table contains certain variables used in the HCI project (e.g., indicator ID, and indicator definition). Some of these variables may contain the same value for all observations.

Decrease the percentage of students enrolled in remedial coursework in college from 39.38% in 2014 to 35% by 2018.

KOKLU Murat (a), UNLERSEN M. Fahri (b), OZKAN Ilker Ali (a), ASLAN M. Fatih(c), SABANCI Kadir (c) (a) Department of Computer Engineering, Selcuk University, Turkey, Konya, Turkey (b) Department of Electrical and Electronics Engineering, Necmettin Erbakan University, Konya, Turkey (c) Department of Electrical-Electronic Engineering, Karamanoglu Mehmetbey University, Karaman, Turkey DATASET: https://www.muratkoklu.com/datasets/ Citation Request : Koklu, M., Unlersen, M. F., Ozkan, I. A., Aslan, M. F., & Sabanci, K. (2022). A CNN-SVM study based on selected deep features for grapevine leaves classification. Measurement, 188, 110425. Doi:https://doi.org/10.1016/j.measurement.2021.110425 Link: https://doi.org/10.1016/j.measurement.2021.110425 DATASET: https://www.muratkoklu.com/datasets/

Highlights • Classification of five classes of grapevine leaves by MobileNetv2 CNN Model. • Classification of features using SVMs with different kernel functions. • Implementing a feature selection algorithm for high classification percentage. • Classification with highest accuracy using CNN-SVM Cubic model.

Abstract: The main product of grapevines is grapes that are consumed fresh or processed. In addition, grapevine leaves are harvested once a year as a by-product. The species of grapevine leaves are important in terms of price and taste. In this study, deep learning-based classification is conducted by using images of grapevine leaves. For this purpose, images of 500 vine leaves belonging to 5 species were taken with a special self-illuminating system. Later, this number was increased to 2500 with data augmentation methods. The classification was conducted with a state-of-art CNN model fine-tuned MobileNetv2. As the second approach, features were extracted from pre-trained MobileNetv2′s Logits layer and classification was made using various SVM kernels. As the third approach, 1000 features extracted from MobileNetv2′s Logits layer were selected by the Chi-Squares method and reduced to 250. Then, classification was made with various SVM kernels using the selected features. The most successful method was obtained by extracting features from the Logits layer and reducing the feature with the Chi-Squares method. The most successful SVM kernel was Cubic. The classification success of the system has been determined as 97.60%. It was observed that feature selection increased the classification success although the number of features used in classification decreased. Keywords: Deep learning, Transfer learning, SVM, Grapevine leaves, Leaf identification

This table contains 7586 series, with data for years 1992 - 2008 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (15 items: Canada; Newfoundland and Labrador; Prince Edward Island; Nova Scotia ...), Registration status (3 items: Total; registration status; Full-time student; Part-time student ...), Program level (10 items: Total; program level; College certificate or diploma and other college level; College postsecondary program; College post-diploma program ...), Classification of Instructional Programs, Primary Grouping (CIP_PG) (14 items: Total; instructional programs; Personal improvement and leisure; Education; Visual and performing arts and communications technologies ...), Sex (3 items: Both sexes; Males; Females ...).

Statistics on student debt, including the average debt at graduation, the percentage of graduates who owed large debt at graduation and the percentage of graduates with debt who had paid it off at the time of the interview, are presented by the province of study and the level of study. Estimates are available at five-year intervals.

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.

Analysis of ‘COVID-19 Vaccinations by Town and Age Group’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/8dfeaa75-9a32-4b7a-b441-a7a9df2b864e on 13 February 2022.

--- Dataset description provided by original source is as follows ---

This table shows the number and percent of residents of each CT town that have initiated COVID-19 vaccination, are fully vaccinated and who have received an additional dose by age group.

All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected.

A person who has received at least one dose of any vaccine is considered to have initiated vaccination. A person is considered fully vaccinated if they have completed a primary series by receiving 2 doses of the Pfizer or Moderna vaccines or 1 dose of the Johnson & Johnson vaccine. The fully vaccinated are a subset of the number who have received at least one dose.

A person is considered to have receive an additional dose if he/she completed a Pfizer, Moderna or Johnson & Johnson primary series and then had an additional dose of COVID-19 vaccine. The additional dose may be Pfizer, Modern or Johnson & Johnson and may be a different type from the primary series. For people who had a primary Pfizer or Moderna series, additional doses were counted starting August 18th, 2021. For people with a Johnson & Johnson primary series additional doses were counted starting October 22nd, 2021. For most people, the additional dose is a booster. However, for people who are moderately or severely immunosuppressed, an additional dose may represent as an addition to a primary series.

The percent with at least one dose many be over-estimated, and the percent fully vaccinated and with an additional dose may be under-estimated because of vaccine administration records for individuals that cannot be linked because of differences in how names or date of birth are reported.

Town of residence is verified by geocoding the reported address and then mapping it a town using municipal boundaries. If an address cannot be geocoded, the reported town is used. Out-of-state residents vaccinated by CT providers are excluded from the table.

The population denominators for these town- and age-specific coverage estimates are based on 2014 census estimates. This is the most recent year for which reliable town- and age-specific estimates are available. (https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Town-Population-with-Demographics). This census data is grouped in 5-year age bands. For vaccine coverage age groupings not consistent with a standard 5-year age band, each age was assumed to be 20% of the total within a 5-year age band. However, given the large deviation from this assumption for Mansfield because of the presence of the University of Connecticut, the age distribution observed in the 2010 census for the age bands 15 to 19 and 20 to 24 was used to estimate the population denominators.

Town-level coverage estimates have been capped at 100%. Observed coverage may be greater than 100% for multiple reasons, including census denominator data not including all individuals that currently reside in the town (e.g., part time residents, change in population size since the census), errors in address data or other reporting errors.

Caution should be used when interpreting coverage estimates for towns with large college/university populations since coverage may be underestimated. In the census, college/university students who live on or just off campus would be counted in the college/university town. However, if a student was vaccinated while studying remotely in his/her hometown, the student may be counted as a vaccine recipient in that town.

Connecticut COVID-19 Vaccine Program providers are required to report information on all COVID-19 vaccine doses administered to CT WiZ, the Connecticut Immunization Information System. Data on doses administered to CT residents out-of-state are being added to CT WiZ jurisdiction-by-jurisdiction. Doses administered by some Federal entities (including Department of Defense, Department of Correction, Department of Veteran’s Affairs, Indian Health Service) a

--- Original source retains full ownership of the source dataset ---

This table contains 156 series, with data for years 1999 - 31-MAR-03 not all combinations necessarily have data for all years), and was last released on 2009-09-02. This table contains data described by the following dimensions (Not all combinations are available): Geography (15 items: Canada;Newfoundland and Labrador;Prince Edward Island;Nova Scotia ...), Expenditures (12 items: Expenditures of universities and colleges; Financial Management System (FMS) basis;Deduct: adjustment to report expenditures on a net basis;Add: principal portion of debt repayments;Add: institutions embedded in the public accounts or financial statements ...).

Postsecondary enrolments, by detailed field of study, institution, institution type, registration status, program type, credential type, status of student in Canada and gender.

College Affordability and Transparency List Explanation Form 2014-15 (CATEF 2014-15) is a cross-sectional data collection that collects information on the major areas of institutions' budgets with the greatest cost increases, the explanations for these increases, and the steps institutions have been or will be taking towards reducing these costs. The data collection is conducted on the subset of institutions that appear on the tuition and fees and/or net price increase lists for being in the five percent of institutions in their institutional sector that have the highest increases, expressed as a percentage change, over the three-year time period. This data collection is mandatory and expects a 100 percent response rate. Key statistics produced from CATEF 2014-15 are a description of the major areas in the institution's budget with the greatest cost increases; an explanation of the cost increases; a description of the steps the institution will take toward the goal of reducing costs in the areas described; an explanation of the extent to which the institution participates in determining such cost increase; the identification of the agency or instrumentality of state government responsible for determining such cost increase; and any other information the institution considers relevant to the report.

University expenditures, by type of expenditure, Canada and provinces. This table is included in Section B: Financing education systems: Public and private expenditure on education of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.

Statistics on postsecondary graduates, including the number of graduates, the percentage of female graduates and age at graduation, are presented by the province of study and the level of study. Estimates are available at five-year intervals.

The number and proportion of full-time teaching staff at Canadian universities by academic rank, gender and academic year.

This service shows the percentage of population aged 25 to 64 years in private households with a postsecondary certificate, diploma or degree by census subdivision, 2016. The data is from the Census Profile, Statistics Canada Catalogue no. 98-316-X2016001.

This data pertains to the population aged 25 to 64 years in private households by the highest level of education that a person has successfully completed. Persons with a post-secondary certificate, diploma or degree includes those with an apprenticeship or trades certificate or diploma; a college, CEGEP or other non-university certificate or diploma; a university certificate or diploma below bachelor level or a university certificate, diploma or degree at bachelor level or above. For additional information refer to the 2016 Census Dictionary for ' Highest certificate, diploma or degree'.

For additional information refer to the 2016 Census Dictionary for ' Highest certificate, diploma or degree'.

To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census subdivision” web service, accessible in the data resources section below.