Shared LACOL Course: Bayesian Statistics Instructor: Professor Jingchen (Monika) Hu, Vassar College Syllabus & Enrollment Info:http://bit.ly/bayesian-stats 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.
Shared LACOL Course: Data Confidentiality (MATH 301) Instructor: Professor Jingchen (Monika) Hu, Vassar College Topics and Objectives: Statistical agencies are under legal obligation to protect survey respondents’ privacy when releasing respondent-level data to the public. Statistical models could facilitate such release by introducing perturbation to the original, confidential data. How to develop suitable statistical models, and how to evaluate the privacy protection they produce, are the focus of this intensive.
Shared LACOL Course: Bayesian Inference with Python (MATH 399) Instructor: Professor Jingchen (Monika) Hu, Vassar College Topics and Objectives: We will focus on computational techniques using Python programming language to estimate various Bayesian models. In the end, students propose and complete a data analysis project of their interests and present it to the group.
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.
Click to Watch Video – S. Miller, Williams College
As one possible avenue to expanding curricular offerings for math and stats majors at small liberal arts institutions, partner schools of LACOL have been exploring ways to remotely share classes using hybrid/online delivery modes. Professors Steven J. Miller (Williams College, pictured above) and Jingchen Monika Hu (Vassar College, at left), two faculty members at the forefront of this collaboration, will describe their experiences in designing hybrid courses and teaching with a mix of digital pedagogies. We will emphasize how connections were made between students and faculty, how well local and remote students were able to engage the material, and the various challenges in coordinating course delivery across several campuses.
For students of advanced mathematics and statistics, the liberal arts model offers a deep level of engagement in learning with faculty and peers; however, due to practical limitations, small colleges cannot always offer the breadth of course subjects available at larger institutions with graduate programs. To explore collaborative models that may help to enrich curricular offerings, faculty and technologists from several leading liberal arts colleges are experimenting with a consortial online/hybrid course sharing model. In this talk, the professors will share results from three recent course pilots: Steven Miller’s Spring 2017 Problem Solving course from WIlliams College (involving students at Williams, Swarthmore and Amherst Colleges), Monika Hu’s Bayesian Statistics course from Vassar College, and Stephan Garcia’s Advanced Real Analysis course from Pomona College (Fall 2017). Read More
As one possible avenue to expanding curricular offerings for math and stats majors, partner schools of LACOL have been exploring ways to remotely share classes using hybrid/online delivery modes.
Math/Stats Pilots: In Spring and Fall of 2017, several LACOL colleges collaborated to pilot three shared course offerings for advanced mathematics and statistics:
Putnam Problem Solving, Spring ‘17 (Prof. S. Miller, WIlliams College)
Advanced Real Analysis, Fall ‘17 (Prof. S. Garcia, Pomona College)
Bayesian Statistics, Fall ‘17 (Prof. M. Hu, Vassar College)
The goal of this exploration is increase the wealth and frequency of the advanced classes our students need, both for graduate study and to delve deeply in the subject.
Learning Design: For these shared courses, each professor opened their course to students across LACOL, sharing lectures, assignments and other class activities through both asynchronous (e.g. recorded lectures and screencasts) and synchronous (e. g. online problem solving sessions and office hours) means.
In these pilots, students reported positive experiences and some adjustments to learning through digital modes:
Before I took Professor Miller’s class, I was already very interested in problem-solving and participating in math competitions […] I was really excited to hear that there was a professor at Williams who was teaching a class on Putnam. I wanted to improve my problem solving skills systematically. The biggest advantage was that I could watch the videos whenever I wanted, and take classes that I otherwise could not fit in my schedule at Swarthmore. I also watched Professor Miller’s other videos, including the ones on number theory or complex analysis, to fill in gaps of my knowledge.
LACOL 2017 Session 7 Speaker: Steven J. Miller, Assoc. Professor of Mathematics, Williams College Date & Location: June 16, Vassar College Related Links:
As small institutions cannot always offer the classes our students need at the time they need them, several people at various LACOL schools have been exploring how to remotely share classes. While there many not be enough demand at any one place for a certain topic, by combining students from several schools we can have a course. There are many challenges, especially keeping the small liberal arts feel and having all students engaged. We report on the beta test, Miller’s Problem Solving class at Williams. We’ll discuss the technology used, emphasizing how the content was delivered and connections were made between students and faculty, and the challenges in coordinating a course across several campuses.
Jingchen (Monika) Hu, Assist. Prof. of Statistics, Vassar College
In connection with LACOL’s Upper Level Math collaboration, Assistant Professor Jingchen (Monika) Hu at Vassar College is opening her Fall 2017 Bayesian Statistics course to students from across the consortium. As the course unfolds, Prof. Hu plans to share bi-weekly lectures and screencasts with the class and engage with remote students via video conferencing and online office hours. On each participating campus, a local faculty liaison will be on hand to guide students as needed. Technical support will be provided in partnership with instructional technology/academic computing groups on each campus. In exploring the opportunity for the pilot experiment, Hu said:
To me, this shared/hybrid model can be a great way to get students on our campuses the access to upper level statistics courses. After collecting some data, I am very amazed at how rich the upper level statistics offering [across LACOL] could be if we can share the resources in some way.
S. Garcia, Assoc. Prof. of Mathematics, Pomona College
The Bayesian Statistics pilot will complement another hybrid/shared offering in Real Analysis from Associate Professor Stephan Garcia at Pomona College. Because sharing Garcia’s course lectures will require capture of his mathematical notations on several blackboards, he is testing a robotic camera rig that can be positioned to record high definition video all around the classroom.
Assoc. Prof. Stephan Garcia, Pomona College, co-lead of the LACOL ‘Upper Level Math’ project (with Assoc. Prof. Steven Miller of Williams College, pictured above)
In September 2016, a team of mathematics faculty, technologists and instructional designers from six leading liberal arts colleges (LACOL member schools Amherst, Haverford, Pomona, Swarthmore, Vassar and Williams) are launching a new collaboration to explore blended course sharing for select topics in advanced mathematics. The goal of the project is to experiment with models for shared course delivery which can supplement residential classroom learning and expand curricular offerings for math majors. Inspired by some independent experimentation and brainstorming between faculty team leads, Assoc. Prof. Steven Miller at Williams College (pictured above) and Assoc. Prof. Stephan Ramon Garcia (pictured at right), a group of six mathematicians from across LACOL began talking about possibilities for a multi-campus collaboration in early 2016. These conversations eventually led to a full project proposal which gained strong support from LACOL’s Faculty and Administrative Advisory Councils. The project was officially approved in July 2016 as a two-phased initiative. In the first phase (academic year 2016/2017), a feasibility study is planned which will execute several experiments and “proofs of concept” involving online/blended course elements such as lecture capture, online coaching and problem solving sessions (synchronous and asynchronous) and peer mentoring. With support from the multi-campus project team, these efforts will be spearheaded by Miller at Williams College in connection with his Spring 2017 ‘Problem Solving’ course. In phase two (academic year 2017/2018), findings from phase one will be brought to bear in a pilot course offering, ‘Real and Functional Analysis’, taught by Garcia. In a fully realized vision, the course would be offered both face to face at Pomona, and also opened virtually to interested students at all LACOL campuses. Local faculty and support contacts at each campus would help ensure students experience the best aspects of on-campus and on-line liberal arts learning.
Since mathematics faculty at all LACOL schools already teach a variety of advanced topics, this project will investigate how online/blended sharing may expand access to a richer array of options to meet student interests. Miller notes:
While liberal arts colleges excel in engaged faculty and personal interactions with students, we do not always have the course offerings available at larger institutions with graduate programs. Though often our students are ready for such classes, at each institution there are practical limits to offering them every year. Our goal is to increase the wealth and frequency of the advanced classes our students need, both for graduate study and to delve deeply in the subject.
Launch of the ‘Upper Level Math’ project has stirred excitement across the Consortium. The math team’s work is seen as an opportunity to collaboratively experiment with emerging online/blended pedagogies that might be useful in a variety of disciplines. It is also a chance for the schools to explore related policy issues of faculty and student credit in the context of online/blended course delivery and consortial partnerships. In considering these issues, the team will draw on experiences from peer institutions and other consortia who have been investigating these new models in a variety of ways. Swarthmore College Professor of Cell Biology Liz Vallen, who evaluated the project in-depth as a member of LACOL’s Faculty Advisory Council, commented:
This [project] seems exactly aligned with LACOL’s goals as it is leveraging the consortium to increase course offerings and availability at partner institutions. The other big benefit of this work is that it is a concrete example that will be a great pilot experiment to see if this is something feasible and beneficial within the LACOL framework.
