Quantitative Analysis Center

Digital and Computational Knowledge Initiative (DaCKI)

(adapted from a May 28, 2013 draft by DG Shaw)

A series of changes in the way we assemble data or facts, recognize knowledge, and formulate both new questions and compelling conclusions suggests we’re in the midst of a revolution in research and scholarship. Digital knowledge is both a cause and an effect in this worldwide transformation. New products, markets, and social and cultural fields bring great possibilities for productivity and creativity, even as they transform the ethical and legal landscape. The computationally-driven digital revolution changes what it means to learn, to teach, to discover, and to act.

Wesleyan faculty, students, and staff are of course part of this revolution and it’s now necessary to assist the campus community in maximizing our ability to exploit these changes, many of which are anchored in the explosion of units and systems of digital information, what we might call knowledge’s new digital clothing. Wesleyan is committed to infuse digital and computational understanding across the curriculum.

No area of learning, scholarship, or research is untouched and the opportunities are exciting. Wesleyan’s Digital and Computational Knowledge Initiative will help us to stimulate and transform on campus learning, enabling faculty to learn more, collaborate more, and share more with students, colleagues and the wider world.

The initiative will emphasize the contribution that computational thinking and analysis can make to a wide variety of subjects. Some understanding of computer programming, how data is gathered, stored and queried, model building, and big data analysis will be part and parcel of 21st century learning, and Wesleyan plans to be at the forefront in providing students with enriched courses and curricular pathways in these areas that broaden general education and complement majors in disciplines that intersect with computational thinking. These computational competencies will combine in the curriculum in an ever-enhanced digital learning environment, where sensitivity to the concepts and methods that enable such data analysis are taught and developed. The education of faculty is a cornerstone of the initiative.

Sharing our knowledge across disciplinary boundaries and teaching students to think and work effectively in the digital age is the ultimate goal of the Digital and Computational Learning Initiative. It aims to accelerate the acquisition of the concepts, methods, and skills for constructing digital knowledge and analyzing and even querying its value and revolutionary potential.

There are several pillars of the initiative:

  • Basic and advanced computational education, expanding beyond its foundation in computer science to link in an interdisciplinary way with the entire campus
  • Computational Modelling, a key resource for imagining the world in order to anticipate developments of all sorts
  • Big data analysis and subsequent text mining: their cultivation and use links the computational with:
  • Practical pattern application and analysis through advanced digital literacy, employing such tools as network analysis, diverse visualization techniques, and geographic information systems (GIS)
  • Learning new forms of digital and electronic scholarly communication to learn and share the knowledge we construct

 The mechanisms for delivering these goals will include:

  • New computational course modules, ready for integration into other discipline-specific courses, enriching non computer courses with the tools and insights of computation;
  • New introductory computational basics courses, often team-taught or team-informed, whose aim is to provide students with the tools needed to begin understanding the necessary computational ideas and techniques as well as bringing them to practical subject research in a variety of disciplines;
  • Smaller, advanced courses, some within disciplines and others interdisciplinary to allow students to acquire true technical and conceptual expertise in new digital and computational fields
  • Providing small grants to allow faculty to experiment with adopting modules, new problematics, and new technologies to expose themselves and students to the latest forms of analysis;
  • Faculty and student education through seminar series and workshops highlighting innovative practices from elsewhere and our own campus and introductions to new digital fields and methods;
  • Seeking of grants from public and private sources such as the NSF, Mellon, and NEH that include components of faculty training and skills development.