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Harnessing Big Data

Planning for Collaborative Courses in Data Science

Harnessing Big Data: Planning for Collaborative Courses in Data Science

  • June 6, 2015
  • Hosted by Luther College, Decorah, IA

Faculty from seven ACM colleges (Beloit, Coe, Grinnell, Lawrence, Luther, Macalester, and Ripon) participated in this workshop to discuss how resources might be pooled across the consortium to provide opportunities in curricula relatedd to data science.

Recapping the ACM Harnessing Big Data Workshop — Blog post by Adam Loy (Assistant Professor of Statistics, Lawrence University), a participant in the workshop, with highlights from the workshop.


Note: Content below is adapted from the project proposal.


Understanding the modern world is increasingly done by analyzing large amounts of data. Smaller liberal arts colleges struggle to offer the variety of courses that are available at larger universities. Pooling resources is one way to overcome this challenge. Many larger universities are creating programs in data science, and in order to bring students to ACM colleges we need to have comparable programs available.

This project will engage multiple ACM colleges, and this is an opportunity to creatively address the challenge of limited faculty and student populations at small schools. By allowing students from across the ACM to access shared courses, we would increase the number of courses available to students. Each individual college could determine how these courses count for credit towards a particular major, minor or concentration.

Currently, there are many impediments to developing shared courses across the ACM such as varying academic schedules, revenue-sharing issues, faculty compensation, and technical assistance requirements. We will discuss these issues and try to determine a reasonable course of action. This will be valuable for future course-sharing endeavors in the ACM. By design, this meeting is a collaborative enterprise among several ACM schools, and the intention is to make resources available to students at all ACM schools. One of the outcomes of the meeting will be a formal plan for how to move forward in sharing courses in data analysis.


The goal of this project is to have representatives from ACM colleges meet and create a plan that would allow faculty at ACM colleges to share expertise in data analysis. The participants will explore ways in which we might share resources. For example, we will discuss sharing of courses across campuses, opportunities for cross-campus student research, and the possible creation of an ACM-wide major or concentration in data analysis. We will also discuss ways in which we can make this program sustainable in the long-term.

The three participating members from Ripon College are junior faculty members whose goal is to give students access to resources to students that are currently not available to them. We are interested in learning about data analysis from more experienced colleagues at partner institutions in the ACM. We intend to share the innovative teaching techniques that we use at Ripon as well as our technological acumen.

The participant from Macalester College is part of a group of statisticians, mathematicians, and computer scientists who are exploring ways to make data science available to our students. We already have one course in place, Data & Computing Fundamentals (COMP 110 — a 1-credit hour course), and will offer another starting in Fall 2015: Statistical Computing and Machine Learning (MATH 253). The workshop will help us learn about techniques for sharing such courses across colleges and identify ways we can contribute to a multi-college curriculum.

Participants from Grinnell College will look to develop additional opportunities for our students to learn about their growing interests in data science. Currently Shonda Kuiper has taught a research based course in multivariate statistical modeling on-line for two semesters. We will share successes and challenges of this online course and collaborate with other ACM schools in expanding the use of online technologies to enhance student learning.

The participant from Coe College would like to assist students with their increasing interest in data science. He has worked individually with students on data science projects and had students present their research at a sports analytics conference. Coe at this time does not have the resources to offer a data science major but there is interest within both the Mathematical Sciences Department and the Business Administration & Economics Department to work with our ACM colleagues in this endeavor. The workshop will help us share curriculum ideas, teaching techniques, and technological abilities. It will foster faculty development and closer interaction between the ACM member schools.


We would like to hold a planning meeting at Luther College with interested members of the ACM schools. In addition to faculty members, we would like to invite deans and instructional technologists. At this meeting, we will discuss how to share existing online courses, such as those at Grinnell College and Luther College. We will consider the feasibility of creating a series of ACM courses that would allow our students to develop skills in data analysis. We will create a plan of implementation and will devise strategies for involving as many ACM schools as possible. This meeting will achieve the project goals by providing us a framework to share resources in data analysis.

Sessions will include discussions on the following:

  • Logistics
  • Materials available
  • Materials to develop
  • Writing larger grant proposal
  • Writing a plan of implementation to distribute to the ACM

Presentations will be given by ACM faculty who have had successfully taught courses or distributed content on-line.

Dissemination Strategies

We intend to produce a list of courses that are ready to start sharing. We will also discuss the logistics involved with sharing an online course during the regular school year. We will write a plan of implementation to distribute to the ACM colleges for their consideration.

We also intend to start a more detailed grant proposal (possibly to NSF or HHMI) that would involve creating a list of courses to work on developing for future use. This proposal may also include opportunities for outreach via collaboration with community colleges or other schools.

Additionally, there is not sufficient staffing at all of the ACM colleges to allow for a major in data analytics. Sharing resources across campuses would allow students to take courses that are not offered at their home institutions. It is possible that some training could be provided to participating faculty members, perhaps in the form of taking one or more of the online courses. Gaining expertise in the growing field of data analytics would be beneficial to individual faculty members. It would also allow the ACM program to grow, as more faculty would be able to teach courses and/or contribute course materials.

One of the sessions at the meeting will be devoted to developing a strategy for implementing a shared data analytics program at ACM campuses. For example, this could take the form of a pilot program where in one currently available course is shared across several campuses.

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