The partners of the Liberal Arts Collaborative for Digital Innovation represent the highest standard of student-centered education. Through our collaborations, we are exploring the future of teaching and learning in a networked world to support our mission as residential liberal arts institutions.
What are some of the biggest rewards of learning a second language? As a student, what do you know now that you wish you had known as you began learning your language at college? As faculty, what one piece of advice would you give to students as they are about to start their language learning at college? What are models or maps that integrate all aspects of language learning?
Over the past year, faculty and language learning experts from across LACOL have been collaborating to develop the CHIANTI concept and prototype. For students, an initial set of videos are posted that feature LACOL language instructors and students reflecting on the college-level language-learning experience. For language teachers, a self-curated online digital library of shareable tips and teaching resources is developing.
As an ongoing initiatve of the LACOL Language Instruction Working Group, the Chianti site and team invites contributions from LACOL language instructors in the areas of: General tips for college-level language learning, including research on adult second-language (L2) acquisition. 2) English grammar for L2 learners including models or maps that integrate all aspects of language, 3) Phonology, and 4) An interactive glossary of grammatical and linguistic terms from which instructors can draw for their own pedagogical purposes and to which they can contribute their own definitions and examples.
In Summer 2019, LACOL offered an 8-week, intensive online course, Introduction to Data Science. The following reports describe the course design, project execution, outcomes and lessons learned:
— Summer Data Science Reports —
Executive Summary: LACOL Summer Data Science 2019 – Executive Summary
Share this page: https://lacol.net/ds-report
by Liz Evans
A new book, Small Teaching Online: Applying Learning Science in Online Classes, by F. Darby and J. Lang (Wiley 2019) caught my eye last June, initially via this IHE author interview. The timing of this discovery was perfect for me, since I was helping to support LACOL’s first fully online summer data science class. So many nuggets from this book prove to be right on target for LACOL’s various pedogogical explorations, I choose it as something to share with my awesome colleagues on the Haverford College Instructional Technology team as part of their summer 2019 Learn and Share discussion group. This short review highlights some of the authors’ ideas I found most thought provoking and potentially useful to anyone teaching in the classroom, online … or both!
Many faculty and designers may be familiar already with the phrase “small teaching” which was made famous in Prof. James Lang’s 2016 book, Small Teaching: Everyday Lessons From the Science of Learning. In a nutshell, Lang demonstrates how small, easily-managed teaching modifications – based on the neuroscience of how people learn – can have a positive impact for students. That is, small adjustments can make good teaching great.
Online professor and instructional designer Flower Darby worked with Lang to bring the small teaching concept into the online realm. The opportunities for discovery are rich because, as Darby notes, online learning is in its infancy.
The book recommendation is excellent – a lot of useful suggestions which would take years to figure out.
-Dr. Natalia Toporikova, Professor of Biology at Washington and Lee University; online instructor, summer 2019
The gerrymandering controversy in American politics offers an ideal subject for a blended learning class that draws upon racial justice, electoral behavior, electoral reform, law, political science, data analysis, and the use of geographic information systems technology. We combined each of these themes into a class that entailed the practical application of GIS and data analysis skills to a contemporary public policy issue that animated the news as the U.S. Supreme Court prepared to issue its second gerrymandering decision in as many terms.
Mark your calendars!
LACOL and the team at Williams College are excited to announce that the summer 2020 consortium-wide LACOL workshop will be held on Williams’ campus, June 24-26, 2020.
All member campuses are invited to send teams of faculty, technologists, librarians, academic support specialists, and others to the summer gathering. It is certain to be a great forum for meeting great LACOL colleagues (old friends and new), sharing experiments and innovations from your home campus, catching up on the latest news and results from LACOL projects, and forging further collaboration into the future of teaching and learning in the liberal arts. (more…)
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:
- The real world is complicated, requiring mathematicians to approximate solutions and even the statement of real world problems!
- 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.)
- 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.
LACOL has been awarded an IUSE grant from National Science Foundation for a project titled, “Online modules for quantitative skill building: Exploring adaption and adoption across a consortium”. This three-year project will research the adaption and adoption of face-to-face and online pedagogies for teaching quantitative skills (QS) with the aim of improving understanding of best practices for the development of online modules to support students’ QS development.
The project proposal was developed by Melissa Eblen-Zayas and Janet Russell of Carleton College and Laura Muller and Jonathan Leamon of Williams College based lessons learned from the QLAB pilot project.
Additional information about the project, including details about the project advisory board, a needs assessment survey for faculty, and opportunities for faculty and staff to get involved, will be be shared later this summer and into the fall through the QS Working Group Forum.
CLICK HERE TO SUBSCRIBE for ongoing news!
Event: Data Science in the Liberal Arts
Date & Location: June 6-7, 2019 at Washington and Lee University
- 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|
Data 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.
More Workshop Talks and Resources:
1. R. DeVeaux – Data Science for All?
2. L. Heyer – Starting a Data Science Minor
In Summer 2019 …
Introduction to Data Science (co-taught course, shared digitally)
Syllabus and FAQ: See course gateway
- Familiarity and expertise in basic coding (R/RStudio).
- Understanding of theory and application of basic concepts in statistics.
- Ability to write and present technical material to diverse audiences.
- 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…)
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
Mini-Conference: Cultivating Student Leadership to Foster a More Inclusive Liberal Arts Classroom
Location: Amherst College Center for Teaching and Learning (Frost Library)
Date: April 5, 2019
Agenda: Student Leadership – April 5 Agenda
Invited Speaker: Bryan Dewsbury, University of Rhode Island
Host: Amherst College Center for Teaching and Learning in partnership with Being Human in STEM and the Office of Diversity and Inclusion (more…)
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)
Project Website: http://emergentedu.org
Event: Language Instruction Jam
Location: Bryn Mawr College, Canaday Library
Date: March 23-24
Agenda: Language Jam Agenda
Attendees: Language Instruction working group and project teams
Full agenda & highlights:
- CHIANTI: Ample time devoted to collaborative workshopping on CHIANTI, the shared teaching resource for college-level language instruction; participants will explore the resources that have been gathered so far (including student and faculty reflection videos on liberal arts language learning), brainstorm on ideas for the emerging platform, and work on building additional content.
- SKILLS DASHBOARD: Demonstration and brainstorming on the language skills question bank and dashboard prototype – initially developed for French last year, with future possibilities for other languages.
- DIGITAL TOOLS for LANGUAGE LEARNING: Colleagues across LACOL shared experiences with digital pedagogies and tools for language instruction.
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
The ASIANetwork Exchange recently published a special issue titled Digital Asia which expands upon the pedagogical research presented at the 25th Annual ASIANetwork Conference, “Digital and Beyond: Ways of Knowing Asia.” Co-edited by Prof. Erin Schoneveld (Haverford College), several articles in this volume explore the productive relationship between digital technology and Universal Design for Learning (UDL.)
ASIANetwork’s theme of “Digital Asia” highlights a wide range of approaches used to represent and examine rapid economic, social, political, and environmental changes and their impacts on Asian cultures. These methods are comprised of both traditional academic disciplines as well as digital technologies that simultaneously allow for the preservation of existing information as well as the creation and sharing of new data, texts, and images resulting in original ways of analyzing and constructing Asia. Within this context, these articles also examine the productive relationship between digital technology and Universal Design for Learning (UDL). UDL offers strategies for faculty to design curricula that stimulate interest in differentiating the ways students are able express what they know.
Prof. Schoneveld’s article, Japanese Modernism Across Media, examines the pedagogical benefits of implementing a semester-long digital curation project using the open-source web-publishing platform Omeka Classic. This digital curation project was supported by Haverford College Library and Mike Zarafonetis, Coordinator of Digital Scholarship and Research Services. Schoneveld’s colleagues Prof. Shiamin Kwa and Anna-Alexandra Fodde-Reguer, Research and Instruction Librarian, in the Haverford and Bryn Mawr (Bi-College) East Asian Languages and Culture Department contributed the article, The Chinese Poster Project: EALC Pedagogy and Digital Media, which highlights Haverford College Library’s fantastic collection of Chinese political posters held in Special Collections.
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:
- Understanding of basic concepts in Bayesian statistics and ability to apply Bayesian inference approaches to solve scientific research problems and real-word problems.
- Ability and skills to use statistical programming software (R/RStudio and JAGS) to realize Bayesian analysis.
- Practice of reading, discussing, and critiquing statistics research journal papers.