Learn More About How We Rank Our Computer Science Programs

Driven by the latest industry data, ComputerScience.org school rankings underscore our commitment to students seeking excellence in higher education. We adhere to a stringent selection process to choose only the highest-performing schools, offering clear, comprehensive rankings for aspiring computer scientists.

Our ranking methodology for computer science degrees applies uniquely to the specific needs of students in this major, accounting for the latest developments in computer science education that help students land jobs.

We understand the stress that comes with comparing computer science degrees. In an effort to simplify the process of ranking computer science programs, we analyze program data using four key criteria: academics, affordability, reputation, and program availability.

Our rankings help students eliminate the guesswork in finding the nation’s most affordable, academically excellent programs. Our methodology is free of outside influence; schools cannot pay for a spot in our rankings. Our site does include advertising partners, but we do not consider those relationships when compiling rankings.

Ultimately, students must make their own decisions about which school to attend, but our computer science rankings can help applicants identify high-quality programs and make sound choices based on reliable data.

We cite the National Center for Education Statistics (NCES), a federal agency tasked with collecting, analyzing, and publishing national education statistics, as our primary data source. As the nation’s definitive source for education-based data, NCES satisfies a Congressional mandate to collect, analyze, and document research about educational institutions.

The following explains more in-depth our sources and criteria.

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About the Data We Use

ComputerScience.org compiles its rankings based on data derived from NCES — more specifically, NCES’s Integrated Postsecondary Education Data System (IPEDS).

IPEDS gathers aggregate survey data from postsecondary institutions. This data comes from verifiable, accountable sources — institutional departments, not students. ComputerScience.org considers many of the same criteria as IPEDS survey components, including graduation rates, outcome measures, and student financial aid. Our methodology requires our quality assurance team to exclude schools that do not yield enough IPEDS data.

The U.S. Department of Education’s Institute of Education Sciences (IES) operates NCES. IES is an independent, nonpartisan data source that offers accurate, accessible education statistics. IES performs at the highest level of effectiveness granted by the U.S. Office of Management and Budget.

ComputerScience.org typically updates our rankings annually, or according to the significant release of fresh data for a major program. With each update, our rankings undergo an entire reranking process — our 2021 lists have been recalibrated using the most recent data available. They are not rebrandings of old rankings for a new year.

As of Nov. 3, 2020, IPEDS has released only a portion of its updated school data for 2020. Our rankings on this site use the most current data available at the time of publication.

A Breakdown of Our Rankings Methodology

ComputerScience.org begins the process of ranking computer science programs by carefully selecting its methodology factors. We choose factors directly connected to return-on-investment (ROI) and assess the impact of such factors on different levels and types of degrees.

Our rankings evaluate a program’s academic performance, affordability, reputation, and availability through documented NCES and IPEDS statistics. Online program rankings reflect both full-time and part-time enrollees.

The following pie charts illustrate our primary online and on-campus program ranking methodology.

About Our Ranking Factors

Within the weighted factor categories above, several subfactors prove critical to the ranking process. We determine affordability by considering subfactors such as financial aid rates, alumni loan default rates, and comparisons of aid received to average cost. Similarly, we account for academic performance subfactors like class size, retention and graduation rates, and the number of programs available.

  • Subfactors for Academics

    • Retention Rate: A school’s retention rate indicates the percentage of students who continue their enrollment in a particular program from one year to the next. Generally, a high retention rate demonstrates a high-quality, high-performing program that supports student success. IPEDS measures the percentage of students who remain enrolled from one fall semester to the next fall semester to determine a school’s retention rate. We use IPEDS’s full-time retention rates for 2018 in our methodology.
    • Graduation Rate: Graduation rate includes the percentage of students who complete their degree within a set window of time. IPEDS measures the graduation rates of first-time students, full-time students, and degree- and certificate-seeking students. A high graduation rate, like a high retention rate, can indicate that students’ academic success is supported by faculty and other institutional resources. For our rankings, we use IPEDS’s 2018 150% graduation rate data, which measures the percentage of students who graduate within 1.5 times the normal period of time allotted for degree completion.
    • Robust Faculty: IPEDS uses the Standard Occupational Classification (SOC) system to organize staffing data collected from postsecondary institutions. Data points include full- and part-time employees, full-time instructional staff, and full-time faculty. Within the full-time faculty category, SOC data examines gender, race/ethnicity, length of employment, salary, and rank. A diverse faculty can contribute to a school’s positive reputation. We use IPEDS’s 2018 data about full-time faculty and student-to-faculty ratios in ranking computer science programs.

  • Subfactors for Affordability

    • Price for Students With Grants or Scholarships: The cost of higher education is a primary concern for most college-bound students. IPEDS collects data on the overall cost of tuition and fees at public, private, two-year, and four-year institutions for undergraduate and graduate students. To further help students select an affordable program, our rankings use IPEDS’s 2017-18 data about the average net tuition cost for students with grant or scholarship aid.
    • Students Getting Financial Aid: IPEDS data also examines how much merit-based financial aid, including grants and scholarships, schools award. For our 2021 computer science program rankings, we incorporated the 2017-18 IPEDS financial aid data, paying attention to several key metrics: the percentage of full-time and first-time undergraduate students awarded aid, how much financial aid these students received, and the average amount of grant and scholarship aid awarded across all schools.
    • Students Getting Federal Aid: When determining program affordability, we also take federal financial aid into account. IPEDS collects data on grant aid and Title IV federal aid awarded to undergraduate students. We use 2017-18 IPEDS data — the percentage of undergraduate students awarded federal student loans as well as the average amount of federal student loans awarded to undergraduates — to rank the most affordable computer science programs.
    • Post-Graduation Student Debt: Though most students pursue several forms of financial aid, they still often accrue debt upon graduation. However, some programs strive toward debt-free learning within a set period of time or develop initiatives to minimize post-graduation student debt, as evidenced by low figures in this subfactor category. ComputerScience.org uses IPEDS’s average loan default rate for 2016 and its 2018 data about the median debt for students who have completed their degree (six years after matriculation) to compile our 2021 rankings.

  • Subfactors for Reputation

    • Percentage of Applicants Admitted: IPEDS collects data to determine a program’s acceptance rate by comparing the number of students who apply to the number of applicants granted admission. Most schools aim to strike a balance between discerning and inclusive enrollment policies, as demonstrated by many of the highly reputable schools on our list. IPEDS does not survey open-admissions institutions. Based on IPEDS’s admissions rate data for 2018, we ranked schools attracting a high number of first-time degree- or certificate-seeking undergraduate students.
    • Admissions Yield: Admissions yield is the number of students admitted to the program who enrolled in classes. A high admissions yield signifies that an institution’s programs and resources can attract new students because they are designed to foster student success. We use IPEDS’s enrollment rate data from 2018 to inform our 2021 computer science program rankings.
    • Return-on-Investment: ROI factors prominently into any higher education considerations, especially for aspiring computer scientists looking to land a lucrative career post-graduation. Programs with significant positive ROI can tout this accomplishment as a selling point for students. ComputerScience.org’s rankings use IPEDS’s 2018 data about the average earnings of students who have begun working six years after matriculation to determine programs with the highest ROI.

  • Subfactors for Program Availability and Online Flexibility

    • Percentage of Online Students Enrolled: For our rankings of online programs, we take into account the availability of online programs at online-only and traditional institutions of higher education. To help direct students toward accessible, flexible online programs in their major, we use IPEDS data about the percentage of students enrolled in online computer science programs, as well as the percentage of students enrolled online overall. This subfactor only affects online-specific rankings.
    • Percentage of Relevant Degree Level Offered: IPEDS also compiles data regarding the volume and availability of degrees an institution offers. ComputerScience.org may, for example, use IPEDS data on a school’s total number of bachelor’s programs offered to determine the institution’s inclusion in our rankings — if our ranking is a list of bachelor’s programs, we check how many total bachelor’s programs each school offers. Offering a variety of programs can indicate that a school dedicates its resources to ensuring quality education at that degree level. We use this IPEDS data to inform our rankings of certificate/diploma, associate, bachelor’s, master’s, and doctoral programs.

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