Operations Research – Shared Course Opportunity, Fall 2019

chess

Shared LACOL Course: Operations Research
Instructor: Professor Steven J. Miller, Williams College
Enrollment Info for Students: http://bit.ly/ops-research
Syllabus & Course Website: https://web.williams.edu/Mathematics/sjmiller/public_html/317Fa19
Course Flyer: Operations Research Fall 2019 PDF
Topics and Objectives:

  1. The real world is complicated, requiring mathematicians to approximate solutions and even the statement of real world problems!
  2. While the chess scenario pictured above might appear to be a make-work problem, the efficient solution illustrates one of the most powerful ideas in mathematics, and allows us to tell in many cases how close we are to the optimal solution (even if we cannot find the optimal solution.)
  3. In this class, you will learn powerful methods from classical algorithms to advanced linear algebra and their applications to the real world, specifically linear programming and random matrix theory.
Video - S. Miller, Williams College
Click to Watch Video – S. Miller, Williams College

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Data Science in the Liberal Arts Workshop (June 2019)

Heyer

Event: Data Science in the Liberal Arts
Date & Location: June 6-7, 2019 at Washington and Lee University
Workshop Goals:

  • Agenda & Program (Background and Purpose)
  • Establishing a Think Tank on Data Science in the Liberal Arts
  • Taking hands on approaches to curating, developing, and sharing liberal arts pedagogies and teaching materials for data science that broadly engage and support our students across the disciplines.

Attendees: members and friends of the LACOL DS+ working group

Scroll down for workshop resources, slides, and video gallery

Keynote Talk:

https://www.stthomas.edu/cisc/faculty/amelia-mcnamara.htmlData Journalism as a Liberal Art
Prof. Amelia McNamara
Department of Computer & Information Sciences
University of St. Thomas

One of the main ways the general public encounters products of data analysis is through journalism. Data journalists strive to explain complex stories using visualization, statistics, and heavy use of contextualization. As we incorporate data science into the liberal arts, data journalism provides a case study as a field in which the sciences and the humanities are consciously linked. In this talk, I’ll discuss the history of data journalism, how I see it fitting into a liberal arts framework, and experiences from a class I taught on data journalism.

A. McNamara SLIDES

More Workshop Talks and Resources:

1. R. DeVeaux – Data Science for All? 

2. L. Heyer – Starting a Data Science Minor

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Introduction to Data Science (shared course)

In Summer 2019 …

Introduction to Data Science (co-taught course, shared digitally)

Syllabus and FAQ: See course gateway

Learning Objectives:

  1. Familiarity and expertise in basic coding (R/RStudio).
  2. Understanding of theory and application of basic concepts in statistics.
  3. Ability to write and present technical material to diverse audiences.

Course Sequence:

  • Intensive 8-week course with data lab component (fully digital)
  • Student centered learning design including pre-recorded lectures, real-time lectures, and laboratory/supported work time
  • Course co-taught by instructors from LACOL schools 
  • Delivery is fully online with some scheduled and some asynchronous events.

Course Team: see course gateway

Lightning Talk – Learn about this project in just 6.5 minutes!


Presented May 22, 2019 at the Bryn Mawr Blended Learning Conference

Course Topics Include: (more…)

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Bryn Mawr’s Blended Learning in the Liberal Arts Conference, May 2019

cropped-blendlac_logo_resized-2CALL FOR PROPOSALS: Blended Learning in the Liberal Arts Conference at Bryn Mawr College May 22-23, 2019.

Submissions are now open for the Blended Learning in the Liberal Arts Conference, to be held on May 22-23, 2019 at Bryn Mawr College. We are open to all topics related to blended learning in the liberal arts. Possible themes include:

  • Digital Competencies: efforts to build digital literacy and digital citizenship; programmatic frameworks, theories, and methods
  • Student Collaborations: digital fellowship and scholarship programs, internships, project work, and other experiential learning opportunities for students
  • Digital Identity: discussions of domains programs, website projects, social media, and new ways that online identities are crafted in educational settings
  • Emerging Technology and Methods: particularly makerspaces, audio/visual production, and critical making

Submit by Feb. 25, 2019 at brynmawr.edu/blendedlearning/conference. Contact Jennifer Spohrer at blendedlearning@brynmawr.edu with questions.

 

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Sensemaker Team Data Review – April 4 at Amherst College

sensemaker data review

Event: Exploring Complexity through Student Micro-Narratives with Sensemaker
Host: Sensemaker Team Leads (Kristen Eshleman, Brent Maher, Annie Sadler, Paul Youngman)
Date: April 4
Time: 1:00pm-5:00pm (optional group lunch at 12:00pm; details tba)
Location: The Powerhouse, Amherst College
Attendees: Sensemaker Teams (Davidson, Hamilton, Haverford, Washington & Lee)
Sensemaker: http://lacol.net/category/collaborations/projects/inclusive-pedagogies
Project Website: http://emergentedu.org

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For Our Students: Digitally Shared Course Offerings (2018/2020)

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Sharing courses as a consortium enhances curricular opportunities and provides a forum for our faculty and students to explore digitally-enhanced, collaborative modes for teaching and learning in the liberal arts. Browse below for the latest classes available to students in the LACOL network.

Faculty take note!  LACOL’s Advisory Councils have issued a Call for Proposals inviting your ideas for novel shared course opportunities.

Data Science, Mathematics &Statistics

Introduction to Data Science (Summer 2019)
Team taught, fully online course

Operations Research (Fall 2019)
Prof. Steven J. Miller, Williams College

Bayesian Statistics (Fall 2019)
Prof. Monika Hu, Vassar College

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Bayesian Statistics – Shared Course Opportunity, Fall 2019

bayesia no words wordpreess
Jingchen (Monika) Hu, Assistant Professor of Statistics at Vassar College
Prof. Monika Hu, Vassar College

Shared LACOL Course: Bayesian Statistics
Instructor: Professor Jingchen (Monika) Hu, Vassar College
Syllabus & Enrollment Info: http://bit.ly/bayesian-stats
Course Flyer: Bayesian Statistics PDF
Topics and Objectives:

  1. Understanding of basic concepts in Bayesian statistics and ability to apply Bayesian inference approaches to solve scientific research problems and real-word problems.
  2. Ability and skills to use statistical programming software (R/RStudio and JAGS) to realize Bayesian analysis.
  3. Practice of reading, discussing, and critiquing statistics research journal papers.

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Measuring Complex Domains for the Liberal Arts

Session: Measuring Complex Domains for the Liberal Arts (Inclusive Pedagogies) with Sensemaker
Resources:
Project site: https://emergentedu.org
About Sensemaker: http://cognitive-edge.com/sensemaker/#sensemaker-about
Leads:
Kristen Eshleman, Director of Digital Innovation, Davidson College
Brent Maher, Director of Academic Assessment, Davidson College
Annie Sadler, Instructional Design Fellow, Davidson College
Paul Youngman, Prof. of German, Chair, Digital Humanities, Washington & Lee University

WATCH!  Intro video (15 min)

Innovations in assessment can directly address a key challenge for our institutions – demonstrating our value in a time of increasing skepticism about the liberal arts.

On April 27, Davidson College and Washington & Lee University hosted a LACOL workshop to explore an assessment tool and method called  Sensemaker that has the potential to manage and account for the complex domains of learning.  Pursuing a research design as a network of allied liberal arts institutions provides evidence at scale while building capacity for experimentation and innovation at each of our institutions.  (more…)

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