The 4 Pillars of CCT

The four pillars of the Center for Computational Thinking (CCT) represent the strategic priorities and areas of focus for the center. Developed by the CCT Steering Committee, in consultation with executive leadership and faculty members, the pillars provide a roadmap for initiatives and new development.

CCT Pillar I: Innovate Computing Majors and Minors

Every student in computing majors/minors can pursue flexible, personalized pathways through an interdisciplinary curriculum marrying computing, liberal arts, and societal grand challenges that emphasizes experiential and team learning.

Exemplars and highlights of Pillar 1 include:

The Cultural Competence in Computing (3C) Fellows Program is a five-month, cohort-based professional development program at Duke where teams of faculty, postdoctoral researchers, and graduate students across the country work to develop/improve cultural competence – a set of congruent behaviors, attitudes, and policies that enable professionals to work effectively in cross-cultural situations – as well as utilize these competencies to affect their home institutions.

Read more about the successful first cohort in “Diversifying Computer Science, One Cohort at a Time.”

Innovations are also happening across our computing classes. To sample a few:

Interdisciplinary Introduction to Computer Science and Foundations of Data Science take interdisciplinary approaches to introducing students to computational thinking.

Race, Gender, Class & Computing explores the diversity challenges in computing and their effects on technology and society at large.

Algorithms in the Real World and Data Science Competition emphasize experiential and team learning and let students apply computational thinking to practical problems.

Meredith Brown, a third-year undergraduate student at Duke studying computer science and statistics, has spent time at Duke solving real-world issues with data science.

Read more about her journey.

CCT Pillar II: Infuse Computational Thinking Across Programs of Study

 Every major, minor, and certificate program can explore pedagogical innovation arising from the infusion of computational thinking into its curriculum.

Exemplars and highlights of Pillar 2 include:

The Digital Intelligence certificate, a new track within the Science & Society undergraduate certificate program, is designed to provide foundational understanding of contemporary and emerging computational thinking, such as artificial intelligence, machine learning, web technologies, cybersecurity, databases, software engineering, and network protocols. This training is coupled with a focus in ethical, legal, social, and policy frameworks needed to understand the complexities of technology’s impact on our world.

This certificate has great pertinence to Pillar I’s innovation of computing majors and minors as well.

Learn more about the certificate in Digital Intelligence.

Students across disciplines can take the advantage of one of our new Interdepartmental Majors (IDMs) between Computer Science and other disciplines, including Linguistics + CS; Visual & Media Studies + CS; and the Data Science IDMs for Statistics + CS and Mathematics + CS.

CCT supports Duke faculty members by offering training modules on computational topics such as exploratory data analysis, data visualization, and machine learning that complement their courses.

CCT Pillar III: Enrich Co-Curricular Opportunities

Any student can explore a range of computational topics via co-curricular opportunities ranging from bite-sized courses and workshops to summer programs and internships.

Exemplars and highlights of Pillar 3 include:

Group photograph of the DTech Scholars in 2019

The Duke Technology Scholars Program (DTech) is a comprehensive effort to empower the next generation of diverse leaders who will bring increased innovation to the tech industry.  The program centers on the idea that relationships, mentorship and hands-on experience make the difference in recruiting and retaining such individuals in technology fields.

DTech is a partnership between Duke’s Office of Information Technology, Trinity College of Arts & Sciences and Pratt School of Engineering.

The Innovation Co-Lab is a creativity incubator, focused on exploring how new and emerging technologies can fundamentally reshape the research, academic, and service missions of the university. Through its Roots series, the Co-Lab offers classes in a variety of tech topics, from web design to programming to arts and fabrication.

In fall 2021, the Co-Lab Roots Program will offer 88+ workshops (with more coming).

The Co-Lab Roots classes are also very pertinent to Pillar IV’s aim to bring computational literacy to all.

The Center for Data and Visualization Sciences (CDVS) partners with researchers and students on data science projects, research, and instruction across the research lifecycle. Through consultations, partnerships, and an expansive series of co-curricular data workshops, CDVS seeks to expand the data community and accelerate data driven discovery at Duke and and beyond. CDVS offers workshops in data science, data management and curation, data visualization, and mapping and GIS (geographic information systems) tools and techniques.

CDVS workshops are also very pertinent to Pillar IV’s aim to bring computational literacy to all.

The Data+, Code+, and CS+ undergraduate summer programs held an online expo on August 6, 2021.

Student teams — comprised of more than 150 students — presented projects leveraging big data, mobile app and web development, and computer science. Each 10-week co-curricular summer program provides students with invaluable experience working with professionals in their industries and Duke faculty and staff to produce results or products that address a question or solve an issue relevant to the Duke community and beyond.

Data+ team projects can be browsed at the Rhodes Information Initiative at Duke website.

Presentations and descriptions of CS+ projects can be browsed at the Department of Computer Science website.

Videos of the Code+ presentations are available on YouTube. Read more about the projects at the Code+ website.

CCT Pillar IV: Bring Computational Literacy to All

Every student gains the computational literacy that enables them to understand the impact of technology, to harness its power in their life, and to be a responsible citizen in our the digital society.

Exemplars and highlights of Pillar 4 include:

The 2021 Machine Learning Virtual Summer School (MLvSS), held in a live, virtual format June 14-17, 2021, attracted 170 participants from across the world, both students and professionals, representing 43 universities, institutes, and corporations.

This event, which was the ninth machine learning school held since 2017, was sold out more than a month in advance and completely filled a 100-person waitlist.

Read more at “Duke Machine Learning School Successfully Concludes Summer 2021 Virtual Offering.”

Duke’s Winter Breakaway (January 4-15, 2021) offered undergraduate, graduate, and professional students learning opportunities between semesters. More than 1,000 Duke students participated in 13 different programs.

The AI for Everyone program was the largest, attracting more than 300 student participants. “With heavy student interest in the program, faculty said they saw the value of learning that was accessible to a broad audience. David Carlson, an instructor in Winter Breakaway’s AI for Everyone and an assistant professor in the departments of Civil and Environmental Engineering and Biostatistics and Bioinformatics said the AI for Everyone sessions aligned ‘with our goal to infuse computational thinking across all programs of study.'”

Read the full story at Duke Today, “Students Find Interdisciplinary Exploration and Connection in Winter Breakaway Courses.”

Listing of the COVID+DS webinar series for summer 2020

The COVID + Data Science Virtual Seminar Series took place across 8 weeks during the summer, from late June through late August 2020. The virtual sessions covered a wide breadth of topics, reflecting the diversity of COVID-related research and activity at Duke.

The series of 12 lectures attracted more than 1,500 virtual attendances, with many participants joining across multiple weeks and topics. It provided the opportunity for audiences both within Duke and beyond to hear directly from experts on topics spanning data analysis and visualization, deep learning, statistical methods, natural language processing, molecular methodology, and more.

Read the full story about the COVID + Data Science summer series.

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