Study Group on Algorithmic Reasoning and Computational Thinking for MIT Undergraduates


For many years, various MIT faculty members have asked whether—and if so, how—MIT should ensure that all its undergraduates learn algorithmic reasoning and computational thinking. In May 2016, Chair of the Faculty Prof. Krishna Rajagopal and then-Dean for Undergraduate Education Dennis Freeman created a Computation Study Group, composed of a several faculty members, to conduct an in-depth study of this topic.

The study group was tasked with asking, as a starting point, what the phrases “algorithmic reasoning” and “computational thinking” mean in the context of the education of MIT’s undergraduates across all five schools. The members of the Computation Study Group included Professors Eric Grimson (EECS; chair of the study group), Deepto Chakrabarty (Physics), Michael Cuthbert (Music and Theater Arts), Peko Hosoi (Mechanical Engineering), Caitlin Mueller (Architecture), Jim Orlin (Sloan) and Troy van Voorhis (Chemistry).


The Charge

Professor Rajagopal and Dean Freeman issued a charge to the study group that provided examples of several kinds of potentially actionable next steps that the study group could consider, after they finished the analysis prompted by the seven questions in the charge. The answers provided by this in-depth study, together with any subsequent curriculum development that it prompts, will serve as valuable input to any future discussion of our GIRs and, more broadly, in subsequent advances in how MIT students are educated.


Final Report of the Study Group

In September 2016, the study group released a draft report of their findings. Professor Rajagopal and Dean Freeman invited all students and faculty to review the draft report and share their input via email to Responses were considered by the study group as they prepared their final report, which was released in January 2017.



A key recommendation of the final report is to explore ways to connect algorithmic reasoning and computational thinking to domain-specific contexts across different intellectual disciplines. The working group envisions that some elements of computational thinking could best be taught in subjects that are designed for a major, or designated as suitable for a major, enabling students to understand computation in a disciplinary context, thereby increasing the utility of what they learn.

To advance this recommendation, grant funding has been made available to develop subjects that use and teach computational thinking in domain-specific contexts.