Tag

education

Apr 25
0

NASEM Webinar: Data Science for Undergraduates – Opportunities & Options

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Data Science for Undergraduates: Report Release Webinar

As our economy, society, and daily life become increasingly dependent on data, new college graduates entering the workforce need to have the skills to analyze data effectively. At the request of the National Science Foundation, the National Academies of Sciences, Engineering, and Medicine organized a study to explore what data science skills are essential for undergraduates and how academic institutions should structure their data science education programs. We invite you to join us for a report release webinar on May 2, 2018 at 11am ET. During this webinar, study co-chairs Laura Haas and Alfred Hero will discuss the report’s findings and recommendations, followed by a question and answer session with webinar participants.

Learn more about the study, download the interim and final reports, and watch past webinars on the study webpage at nas.edu/EnvisioningDS.

Register for the Webinar.

WEBINAR INSTRUCTIONS

Click here to join the webinar

Password: data

Apr 26
0

NASEM Webinar: Data Science for Undergraduates – Opportunities & Options

By | Al Hero, Educational, News

As our economy, society, and daily life become increasingly dependent on data, new college graduates entering the workforce need to have the skills to analyze data effectively.

At the request of the National Science Foundation, the National Academies of Sciences, Engineering, and Medicine organized a study to explore what data science skills are essential for undergraduates and how academic institutions should structure their data science education programs.

We invite you to join us for a report release webinar on May 2, 2018 at 11am ET.

During this webinar, study co-chairs Laura Haas and Alfred Hero will discuss the report’s findings and recommendations, followed by a question and answer session with webinar participants.

Register

Mar 07
0

IOE 899 Seminar Series: Stanley Hamstra, PhD, Milestones Research & Evaluation Accreditation Council for Graduate Medical Education

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Stanley J. Hamstra, PhD

VP, Milestones Research and Evaluation Accreditation Council for Graduate Medical Education

 

“Learning Analytics in Graduate Medical Education: Realizing the Promise of CBME with Milestones Achievement Data”

Abstract: In 2012, the Accreditation Council for Graduate Medical Education (ACGME) introduced the Next Accreditation System (NAS) for improving postgraduate medical education. An important component of the NAS is a shift towards competency-based medical education (CBME), involving milestones as markers of achievement during training. Since 2015, the ACGME has been collecting milestones achievement data (competency ratings) on all resident and fellow physicians in accredited training programs in the USA (n > 110,000 residents and fellows per year). A critical assumption in CBME is that assessment data regarding any learner (in any form) contains some degree of uncertainty. At the same time, program directors must make finite/binary decisions about learners at the time of graduation, and indeed throughout training. The availability of milestones data, in the context of national trends, gives the program director an additional tool for making the best decisions regarding learner progression (and ultimately graduation). I will briefly review tools we have developed to help program directors make use of milestones data to enhance the quality of their decisions regarding resident progression and graduation. In addition, I will outline an approach to using the data for enhancing national curricula within a specialty.

Bio: Dr. Hamstra is responsible for oversight and leadership regarding research in Milestones and assessment systems that inform decisions around resident physician progression and board eligibility. Dr. Hamstra works with medical subspecialty societies, program director organizations, the American Board of Medical Specialties, and specialty certification boards. His research addresses medical education broadly, including competency assessment for residency training programs, and developing administrative support for educational scholarship within academic health settings. Prior to joining the ACGME, Dr. Hamstra was at the University of Michigan, the University of Ottawa, and the University of Toronto Department of Surgery. He has also worked closely with the Royal College of Physicians and Surgeons of Canada on developing policies regarding competency-based medical education for graduate medical education. Dr. Hamstra received his PhD in sensory neuroscience from York University in Toronto in 1994.

Feb 14
0

MIDAS Working Group: Teaching Data Science

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The Michigan Institute for Data Science (MIDAS) continues to convene a working group on teaching data science. As we incorporate data science into almost every level of teaching, many issues need to be thoroughly thought out: How do we teach data science to students with various levels of preparation, from those with little quantitative training to STEM students? How do we build data science modules to incorporate into existing domain science courses? How do we raise awareness of ethics and social responsibility in data science teaching? How do we teach data science to independent researchers, including faculty, who want to build data science into their research? What teaching resources are available at UM? Our working group welcomes anyone interested in these topics. We are developing an interdisciplinary team to foster new ideas and collaborations in the development of data science teaching methods and materials.

Please RSVP.  

The agenda for the meeting includes:

  • Introduction
  • Short presentations
    • Kerby Shedden (Professor, Statistics, and CSCAR director) will share insight from his experience teaching “capstone” style courses for undergraduate and MS students, based around case studies and focus on methods, formulating good questions, and writing.
    • Heather Mayes (Assistant Professor, Chemical Engineering) will talk about the design of a Data Science ramp-up course for engineering students and how to integrate it with existing course offerings.
    • Aaron Keys (data scientist, Airbnb) will give the industry perspective on the various training paths that students can take for a career in data science.
  • Open discussion of ideas and collaboration, and sharing resources

For questions, please contact Jing Liu, MIDAS Senior Scientist and Industry Partnership Leader (ljing@umich.edu; 734-764-2750).

Dec 05
0

Institute for the Humanities Lecture: Jay Clayton

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jay-clayton

Jay Clayton, PhD

William R. Kenan, Jr. Professor of English
Director of the Curb Center for Art, Enterprise, and Public Policy

 

“A Humanist in the World of Genomics:

Privacy, Big Data, and Science Policy”

 

Abstract: How can humanists successfully compete for NIH and NSF funding? What roles can the humanities play in the public sphere? How can we influence public policy around a host of issues ranging from genomics, neuroscience, and medicine to the environment, economic inequality, racial disparities, digital media, and big data? Drawing on his experience as a Co-PI and researcher on two collaborative NIH grants totaling more than $4-million, as director of a center focused on the role of the arts in shaping public policy, and as a participant in projects with the Institute of Medicine, Personal Genome Project, Broad Institute, and several Medical schools, Jay Clayton will outline answers that have worked at his institution and other universities.

Bio: Jay Clayton is author or editor of seven books and more than 35 articles and chapters, and he has received fellowships from the Guggenheim Foundation, the American Council of Learned Societies, and elsewhere. His published scholarship has ranged from Romantic poetry and the Victorian novel to contemporary American literature, film and digital media, science and literature, and medicine, health, and society. His book, Charles Dickens in Cyberspace: The Afterlife of the Nineteenth Century in Postmodern Culture, focused on the depiction of computers, information technology, and cyborgs from the Victorian era to the twenty-first century. This study won the Suzanne M. Glasscock Humanities Prize for Interdisciplinary Scholarship. His recent work has concentrated on the ethical, social, and cultural issues raised by genomics.

Sep 13
0

Q & A with Chaoyi Jiao, first recipient of the MIDAS Graduate Certificate in Data Science

By | Educational, General Interest, News

The MIDAS Graduate Certificate in Data Science was established in 2015 to offer students a way to enhance their skills and prepare for a workforce that values multidisciplinary knowledge, broad analytical skills, and agile technological abilities. Nearly 50 students have enrolled in the program, which requires 9 credits of courses and 3 credits of experiential training, and involves mentorship opportunities with MIDAS-affiliated faculty members.

Chaoyi Jiao, who recently received his Ph.D from the Department of Climate and Space Sciences and Engineering and is now a post-doc there, was the first recipient of the MIDAS Graduate Certificate in Data Science. He recently answered a few questions about the program.

What are your research interests, and how does “data science,” broadly speaking, pertain to them?
My research primarily focuses on the Arctic climate change and climate modeling. Observation shows that the Arctic is warming at a much more rapid pace compared to the middle latitudes and tropics. Thus further warming of the climate system may pose an increasing threat to the climate and ecosystem in the Arctic. I hope to gain better understanding of the Arctic climate change and improve the numerical representation of Arctic climate in the climate models. As the data generated by the current generation of climate models and observational networks are growing rapidly, more sophisticated data analyses skills become more and more important for this research area.

Why did you decide to pursue the Graduate Certificate in Data Science?
As I started to conduct my PhD research project, I realized that statistics and data analysis skills are quite important. So I started to take some statistics classes on my second year. Later I learnt that there is a Data Science certificate program. I was very interested in the learning opportunities and academic experience proposed by this program. And I also think it could greatly benefit my career. So I decided to apply.

How hard or easy was it to meet the academic requirements?
Some classes are quite challenging when I started. But generally speaking, I think the academic requirement of this certificate is quite reasonable.

Were you required to take courses that you wouldn’t otherwise have taken? If so, how did they help you broaden your view of data science?
I would say probably not. I was planning to take some courses relate to statistics and machine learning topics before this certificate becomes available. But I think if I enrolled the data science program at a earlier time, I may take one or two extra classes. My experience tells that taking classes outside one’s own research field often helps to think with a broader perspective.

Why should other U-M students pursue this certificate?
I think as many research fields are becoming more and more data driven, mastering the cutting edge data analysis skills can greatly benefit one’s career. I would say if you believe that your research field is data driven and you hope to learn more advanced data science related topics, you definitely should consider this certificate. Moreover, the data science certificate also provides a great opportunities for networking with other students in this program.

For more information on the program, visit http://midas.umich.edu/certificate/ or contact midas-contact@umich.edu.

Aug 15
1

Raising the next generation of data scientists at the MIDAS Summer Camp

By | Educational, Feature, General Interest, News

This summer, 10 high school students from around the country gathered in Ann Arbor for the first annual Michigan Institute for Data Science Summer Camp on the campus of the University of Michigan.

The weeklong camp, titled “From Simple Building Blocks to Complex Shapes: A Visual Tour of Fourier Series,” drew students from as far away as Kansas City, MO, and as nearby as Ypsilanti and Ann Arbor.

The camp was organized by Raj Nadakuditi, assistant professor in the Electrical Engineering and Computer Science Department. Other U-M faculty instructors at the camp were Prof. Jenna Weins, and MIDAS co-directors Prof. Al Hero and Prof. Brian Athey.

The camp was well received by the participants, who ranged from high school sophomores to seniors. A total of 10 students attended, five boys and five girls. Students used the Fourier Series to make art, diagnose disease, and “play detective.”

“I’ve been looking to learn about what been going on with Big Data,” said Daniel Neamati, a 16-year-old from Ann Arbor who hopes to someday study deep space with NASA. “I was really surprised by this camp. Math is basically everywhere.”

Elizabeth Fitzgerald, 16, traveled from South Carolina to take part in the camp. She said she wants to study artificial intelligence and machine learning, but was interested to see what else data science can explain.

“It was enlightening to see all the different applications of data science,” she said.