Core Program Lab Science (CPLS)

The purpose of the Core Program Lab Science (CPLS) requirement is to engage students in the empirical study of phenomena, to support or falsify a hypothesis using a scientific approach of structured observations or experimentation, data analysis, and use of evidence.

The course experience should simulate or replicate the methods of exploration and discovery used by analysts and experts working on problems or exploring hypotheses through hands-on data collection in a field or laboratory setting.

Designation Criteria

Courses that meet the Core Program Lab Science (CPLS) requirement include hands-on data collection through observation or experimentation in the field or laboratory; the use of numerical methods such as data analysis and modeling; and emphasize and demonstrate fundamental concepts of scientific inquiry (such as falsifiability and reproducibility, recognition of error, uncertainty, and bias).

CPLS courses are regularly scheduled classes typically held on a weekly basis, and are usually, composed of class meetings where some mixture of instructor-led explanation occurs (“lecture” sessions) coupled with practical sessions (“labs”). Labs are supplementary class meetings where students apply, experience, or practice what they have learned in “lecture” by building or running simulations, making observations, taking measurements, doing hypothesis-driven data collection and analysis, conducting experiments, and/or interpreting the results of these empirical experiences.

NOTE: Neither independent studies nor directed research projects with individual faculty members can fulfill the CPLS requirement


Through completion of the CPLS requirement all students will achieve all of the following learning outcomes listed below:

  1. Learn and practice disciplinary-specific scientific tools and strategies in a laboratory or field setting, such as observing phenomena, designing experiments, and gathering or collecting primary data.

  2. Learn appropriate technical vocabulary and create relevant scientific communication data products (such as graphs, summary tables of results, laboratory reports, etc.).

  3. Apply the fundamental concepts in, and prior knowledge of, the discipline to guide what questions are asked, and which discipline-specific methods should be used to answer those questions

  4. Consider the nature, scope, limitations, and broader impacts of empirical scientific investigation (i.e. data analysis, controlled experiments, statistics, applied mathematical modelling, etc.).