3 questions: Mix computer science with other disciplines at MIT | MIT News

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The demand for computer related training is at an all time high. At MIT, there has been a remarkable wave of interest in computer science programs, with many enrollments from students studying everything from economics to life sciences, eager to learn how computational techniques and methodologies can be used and applied in their main field.

Launched in 2020, the Common Ground for Computing Education was created by MIT Stephen A. Schwarzman College of Computing to address the growing need for improved programs that link computing and artificial intelligence across different fields. In order to advance this mission, Common Ground brings together experts from MIT and facilitates collaborations between several departments to develop new classes and approaches that blend computer science topics with other disciplines.

Dan Huttenlocher, Dean of MIT Schwarzman College of Computing, and Chairs of the Common Ground Standing Committee – Jeff Grossman, Head of the Department of Materials Science and Engineering and Morton and Claire Goulder and Family Professor of Environmental Systems; and Asu Ozdaglar, Associate Dean of Academics at MIT Schwarzman College of Computing, Head of the Department of Electrical Engineering and Computer Science, and MathWorks Professor of Electrical Engineering and Computer Science – here discuss Common Ground goals, pilot topics that are underway and how they engage faculty in creating new curricula for the MIT “Computer Bilingual” class.

Question: What are the objectives of the Common Ground and how does it fit into the mission of MIT Schwarzman College of Computing?

Huttenlocher: One of the essential components of the college’s mission is to train students who master both the “language” of computer science and that of other disciplines. Machine learning courses, for example, attract many students outside of Electrical and Computer Engineering (EECS) majors. These students are interested in machine learning for modeling in the context of their areas of interest, rather than the inner workings of machine learning itself as taught in Course 6. So we need new approaches to develop computer science programs in order to provide students with an in-depth computer science knowledge that matches their interests, not only to enable them to use computer tools, but also to conceptually understand how they can be developed and applied in their main field, be it science, engineering, humanities, business or design.

Common Ground’s primary goals are to infuse computer science education throughout MIT in a coordinated fashion, as well as to serve as a platform for cross-departmental collaborations. All courses and programs developed through Common Ground are intended to be jointly created and offered by multiple academic departments to meet “common” needs. We bring the forefront of the rapidly evolving fields of computing and artificial intelligence along with the problems and methods of other disciplines, so the process must be collaborative. As much as computer science changes thinking in disciplines, so many disciplines change the way people develop new approaches to computing. It cannot be a stand-alone effort, otherwise it will not work.

Question: How does Common Ground facilitate collaborations and engage MIT professors in developing new programs?

Disgusting man: The Common Ground Standing Committee was formed to oversee Common Ground activities and is responsible for assessing how best to support and advance the objectives of the program. The committee has 29 members – all are faculty experts in various IT fields and represent 18 academic departments across MIT’s five schools and the college. The structure of the committee is very much aligned with the mission of Common Ground in that it draws on all parts of the Institute. Members are organized into sub-committees currently focused on three main areas of interest: fundamentals of computer science and engineering; fundamentals of computer programming / thinking; and machine learning, data science and algorithms. The subcommittees, with many contributions from departments, have developed prototypes for what Common Ground topics would look like in each area, and a number of classes have already been tested to date.

It was wonderful to work with colleagues from different departments. The level of commitment that all of the committee members have put into this effort has truly been amazing to see, and I share their enthusiasm for pursuing opportunities in computer science education.

Question: Can you tell us more about the topics already in progress?

Ozdaglar: So far, we have four offerings for students to choose from: in the fall there is Linear Algebra and Optimization with the Department of Mathematics and EECS, and Programming and Computational Thinking Skills in context with the experimental study group and EECS; Modeling with Machine Learning: from algorithms to spring applications, with disciplinary modules developed by several engineering departments and MIT Supply Chain Management; and Introduction to Computational Science and Engineering over the two semesters, which is a collaboration between the Department of Aeronautics and Astronautics and the Department of Mathematics.

We have taken these courses to students from a variety of disciplines, including mechanical engineering, physics, chemical engineering, economics, and management, among others. The response has been very positive. It is very exciting to see MIT students having access to these unique offers. Our goal is to enable them to frame disciplinary issues using a rich IT framework, which is one of the goals of the Common Ground.

We plan to expand Common Ground’s offerings in the coming years and welcome ideas for new topics. Some ideas that we currently have in the work include courses in causal inference, creative programming, and data visualization with communication. In addition, this fall, we launched a call for proposals to develop new topics. We invited instructors from across campus to submit ideas for pilot computer science courses that are useful in various fields and support the educational mission of different departments. Selected proposals will receive seed funding from the Common Ground to assist in the design, development and staffing of new broadly applicable IT topics and the revision of existing topics in line with Common Ground objectives. We explicitly seek to facilitate opportunities in which multiple departments would benefit from coordinated instruction.


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