Student-level demographic data

Student-level demographic information for approximately 98,000 degree-seeking undergraduate students, keyed by student ID. Data at the "student-level" refers to information collected by undergraduate institutions about individual students, for example, age, sex, and race/ethnicity at matriculation.

Usage

data(student)

Format

A data.frame and data.table with 13 variables and 97,555 observations of unique students occupying 18 MB of memory:

mcid

Character, anonymized student identifier, e.g., MCID3111142225.

institution

Character, de-identified institution name, e.g., Institution A, Institution B, etc.

transfer

Character, transfer status, possible values are First-Time in College, First-Time Transfer.

hours_transfer

Numeric, number of credit hours transferred (or NA).

race

Character, race/ethnicity as self-reported by the student, e.g., Asian, Black, Hispanic, etc.

sex

Character, sex as self-reported by the student, possible values are Female, Male, and Unknown.

age_desc

Character, age group, possible values are 25 and Older, Under 25.

us_citizen

Character, US citizenship, possible values are No, Yes.

home_zip

Character, home ZIP code (or NA), e.g., 02056, 20170, 51301, 80129, etc.

high_school

Character, code for the last high school attended before admission (or NA), e.g., 060075, 210512, 431800, 502195, etc.

sat_math

Numeric, SAT mathematics test score (or NA).

sat_verbal

Numeric, SAT reading test score (or NA).

act_comp

Numeric, ACT composite test score (or NA).

Source

2022 MIDFIELD database

Details

Student data are structured in row-record form, that is, information associated with a particular ID occupies a single row—one record per student.

The data in midfielddata are a proportionate stratified sample of the MIDFIELD database, but are not suitable for drawing inferences about program attributes or student experiences—midfielddata provides practice data, not research data.

See also

Package midfieldr for tools and methods for working with MIDFIELD data in R.

Other datasets: course, degree, term

Examples

if (FALSE) { # \dontrun{

# Load data
data(student)

# Select specific rows and columns
rows_we_want <- student$mcid == MCID3112192438
cols_we_want <- c(mcid, institution, transfer, race, sex, age_desc)

# View observations for this ID 
student[rows_we_want, cols_we_want]

} # }