Characteristic | Data collection | Responses |
---|---|---|
Age | Open-ended | 85% between 18 and 23, range—17–46 |
Gender | Male, female, other | 67% male, 31% female, 2% other |
Race | Caucasian, Latinx, Asian, Black, other, mixed | 73% Caucasian, 5% Latinx, 8% Asian, 3% Black, 11% other or mixed |
Primary language | English, not English | 90% English |
Family SES | < $25k, 25–50k, 50–100k, 100–200k, > 200k | 27% below $50k, 69% $50–200k, 4% above $200k |
Major | Computing, engineering, other | 43% computing, 40% engineering |
Status | Full-time, part-time | 92% full-time |
High school GPA | Open-ended | Average—3.56/4.0 |
College GPA | Open-ended | Average—3.42/4.0 |
Year in school | 1st, 2nd, 3rd, 4th, 5th, other | 47% 1st, 25% 2nd, 16% 3rd, 12% higher |
Expected grade | A, B, C, D, F | 64% A, 28% B, 8% C |
Expected difficulty | Likert type 1—very difficult to 5—not at all difficult | Average—2.97 |
Level of interest in course | Likert type 1—not at all interested to 5—very interested | Average—3.84 |
Reason for taking course (select all that apply) | Advised to, required for major, interested in topic, relevant to career path | 31% advised to, 92% required for major, 57% interested in topic, 56% relevant to career path |
Prior experience with programming (select all that apply) | Matrix that crossed K-5, 6–8, and 9–12 grades with informal, formal, or self-guided learning | 34% had no prior experience; 31% had experience in K-5, 25% in 6–8, and 61% in 9–12; 18% had informal experience, 50% had formal, and 29% had self-guided |