Parents, Students Want Computer Science Education in School

WASHINGTON, D.C. -- Parents of seventh- to 12^th-graders in the U.S. place a high value on computer science education in schools, according to a recent Gallup and Google study. Nine in 10 parents say offering opportunities to learn computer science is a good use of resources at their child's school, and about as many (91%) want their child to learn more computer science in the future.

These findings are from a 2014 study by Gallup and Google with random, nationally representative samples of seventh- to 12^th-grade students in the U.S., parents of seventh- to 12^th-grade students and teachers of students in first to 12^th grades. Gallup also surveyed a non-representative, but comprehensive sample of K-12 principals and superintendents.

Computer Science Just as Important as the Three R's

As technology continues to rapidly advance and computer science becomes rooted in more aspects of society -- the U.S. Bureau of Labor Statistics estimates that 1.3 million jobs in computer and mathematical occupations will be created by 2022 -- many parents and educators see offering computer science educational opportunities to students as essential.

Most parents say computer science learning is at least as important to a student's future success as required courses such as math, science, history and English. About one in five parents say offering opportunities to learn computer science is "more important" than these required courses and 64% think it is "just as important."

Teachers, principals and superintendents also place a high value on computer science learning, although less than parents do. More than six in 10 teachers, principals and superintendents surveyed say computer science learning opportunities are just as important as or more important than required courses.

Students Expect to Learn Computer Science and Use It in Future Careers

Further, most students in grades 7-12 expect to have opportunities to learn computer science in the future. More than eight in 10 students say they are either "very likely" (27%) or "somewhat likely" (56%) to learn computer science in the years to come.

Students who have the opportunity to gain foundational computer science skills during their K-12 years may continue to build on these skills in college and take advantage of the growing number of professions that rely on them. Both students and parents anticipate that computer science skills will be necessary for jobs students will hold in the future. Most students (90%) say they are at least somewhat likely to have a job someday where they will need to know computer science, and most parents (85%) say the same about their child's future career.

Principals, Superintendents May Underestimate Demand for Computer Science

Despite this high level of interest, many school and district administrators do not perceive a high level of demand for computer science education among students and parents in their schools. Less than 10% of principals and superintendents say demand for computer science is high among parents in their school or district, and less than 20% say demand is high among students.

Bottom Line

All groups -- parents, students, teachers and administrators -- agree that computer science learning is important. However, principals and superintendents may be underestimating how high the demand is for these studies among students and parents. Students and parents may need to actively communicate their desires and expectations to administrators if they strongly desire to see additional computer science learning opportunities in their schools. School and district administrators often face difficult decisions about where to place their resources given the competing educational priorities; however, majorities of the principals and superintendents surveyed see computer science as just as important to a student's future success as other required and elective courses, indicating they place a high value on these opportunities.

For more insights about demand for and access to computer science education in U.S. schools, read the full Google-Gallup report, Searching for Computer Science: Access and Barriers in U.S. K-12 Education.

Survey Methods

This article includes results from five surveys conducted by Gallup on behalf of Google.

Results for the Searching for Computer Science: Access and Barriers in U.S. K-12 Education report are based on surveys conducted with parents, students, teachers, principals and superintendents.

Telephone interviews were conducted for students, parents and teachers currently living in all 50 states and the District of Columbia using a combination of two sample sources: the Gallup Panel and the Gallup Daily tracking survey. The Gallup Panel is a proprietary, probability-based panel of U.S. adults selected using random-digit-dial (RDD) and address-based sampling methods. The Gallup Panel is not an opt-in panel. The Gallup Daily tracking survey sample includes national adults with a minimum quota of 50% cellphone respondents and 50% landline respondents, with additional minimum quotas by time zone within region. Landline and cellular telephone numbers are selected using RDD methods. Landline respondents are chosen at random within each household based on which member had the most recent birthday. Eligible Gallup Daily tracking respondents who previously agreed to future contact were contacted to participate in this study. Parent and student interviews were conducted in English and Spanish. Teacher interviews were conducted in English only.

Student interviews were conducted Nov. 19-Dec. 17, 2014, with a sample of 1,673 students in grades seven to 12.

Parent interviews were conducted Nov. 19-Dec. 8, 2014, with a sample of 1,685 parents with at least one child in grades seven to 12.

Teacher interviews were conducted Nov. 25-Dec. 14, 2014, with a sample of 1,013 first- to 12^th-grade teachers.

Student and parent samples are weighted to correct for unequal selection probability and nonresponse. Parent data are weighted to match national demographics of age, gender, education, race, ethnicity and region. Student data are weighted to match national demographics of age, gender, race, ethnicity and region. Demographic weighting targets are based on the most recent Current Population Survey.

Teacher samples are weighted to correct for unequal selection probability and nonresponse. The data are weighted to match demographics of age, gender, education, race, ethnicity and region. Demographic weighting targets are based on Gallup Daily tracking information.

Parent and student samples are weighted to correct for unequal selection probability and nonresponse. Parent data are weighted to match national demographics of age, gender, education, race, ethnicity and region. Student data are weighted to match national demographics of age, gender, race, ethnicity and region. Demographic weighting targets are based on the most recent Current Population Survey.

All reported margins of sampling error include the computed design effects for weighting.

For results based on the total sample of students, the margin of sampling error is ±3.4 percentage points at the 95% confidence level.

For results based on the total sample of parents, the margin of sampling error is ±3.5 percentage points at the 95% confidence level.

For results based on the total sample of teachers, the margin of sampling error is ±4.0 percentage points at the 95% confidence level.

Web surveys were completed by principals and superintendents contacted using sample provided by established education sample providers. The sample sources are comprehensive but not representative of all principals and superintendents currently in the U.S. Interviews were conducted in English only.

Principal surveys were completed Nov. 11-Dec. 10, 2014, with a sample of 9,693 principals at the elementary, middle and high school levels.

Superintendent surveys were conducted Nov. 12-Dec. 19, 2014, with a sample of 1,865 school district superintendents.

In addition to sampling error, question wording and practical difficulties in conducting surveys can introduce error or bias into the findings of public opinion polls. It should also be noted that differences between telephone respondents and Web respondents are not perfectly comparable both because of modal differences and the representativeness of the samples.