In a recent article by ASEE PRISM, the Boston University College of Engineering curriculum and approach to data science was touted. Here are excerpts from the article:
New Core Values: As the data revolution transforms industry and society, engineering schools are rethinking the basics.
By Mary Lord
The world is awash with information. Each second, a vast array of increasingly intelligent devices pours binary tidbits into the metaverse, conveying details from the mundane (email, texts, Facebook posts) to the vital (medical scans, tornado alerts, aircraft malfunctions). This decade-long deluge, dubbed “the golden era of data” by Harvard Business Review, has transformed society and made data skills essential at every level in virtually every organization.
That includes higher education, where the data revolution is driving discoveries in areas from archeology to vaccine development. The impact and opportunities have been particularly profound in the STEM arena, as evidenced by the gleaming, multidisciplinary computer, data science, and engineering complexes springing up on US campuses. Industry’s surging need for graduates who can effectively and ethically winnow insightful kernels from the chaff of enormous data sets propelled the National Academies of Sciences, Engineering, and Medicine to recommend in 2018 that academic institutions embrace data science as a “vital new field” and create majors, minors, and other undergraduate pathways to foster “data acumen.”
Fresh Foundations
Few programs have retooled their undergraduate curricula for the digital economy as dramatically as Boston University’s College of Engineering. Four years ago, the school began embedding data science concepts in required courses for all majors, putting statistics, probability, and basic machine-learning concepts on par with calculus among fundamental competencies. An expanded core sequence now is poised to debut, with upper-level classes in data analytics, artificial intelligence, and other subjects. The goal: graduate innovators who understand and can apply large-scale computing techniques to global challenges from improving medical care to designing sustainable cities.
“Solving complex problems for society requires intersectional thinking,” explains BU’s engineering dean, Kenneth Lutchen, who spearheaded the initiative as part of the school’s trademark mission to educate the Societal Engineer. Students “still are card-carrying mechanicals” and other majors, he assures, but “every single engineering discipline needs engineers who know something about data science.” Given the profession’s code of ethics, he adds, engineers have “an extra obligation” to “look at the data and say something isn’t right.”
BU’s big-data shift builds on a decade of curricular transformation, such as infusing makerspace and design experiences throughout the undergraduate engineering program. It also responds to the “data science wave” that the dean’s leadership advisory board saw reshaping their businesses. The shared top need of biotech labs and retail giants alike: engineering graduates with exposure to data analysis tools and techniques. The “shock” that further validated the school’s data science commitment came when Lutchen was interviewing potential hires this past year and realized how deeply data science “is impacting every one of our faculty.” Of ten recent candidates, for example, two explicitly worked at the intersection of data science and medicine. The rest (like dozens of previous applicants) used machine learning and artificial intelligence to advance research in such traditional engineering areas as materials design and energy.