MOOCs to Continue Your U-M Learning this Summer

Onawa Gardiner, Marketing Specialist
@onawanna

Students – with summer break and/or commencement rapidly approaching, continue learning with U-M by taking a massive open online course (MOOC) from Michigan. These courses are available online and open for enrollment, providing the perfect opportunity to explore diverse subjects while developing new skills to enhance your internship experience, build out your resume, and/or help you prepare for graduate school.

Graduates standing at Michigan Diag

Courses like data science and web development can add to your professional skill set and bolster growth in future internship, classroom and professional settings. Other courses, such as Finance for Everyone, provide the opportunity to improve decision making and the ability to make strategic daily choices. These MOOCs showcase the potential to foster new skills, explore different subjects and develop decision-making strategies to strengthen future educational and professional experiences.

Check out these courses available now through U-M:

Data Science Ethics

Learn about shared values regarding data ownership and privacy issues in the digital sphere. Data Science Ethics addresses ethical issues surrounding the way data is used in a wide variety of digital and technological areas of study and for a diverse range of professions. Take this course to dive deeper into data science and enhance your knowledge base for future professional and internship endeavors.

Finance for Everyone: Smart Tools for Decision-Making

Dive into the world of finance with this course to learn the skills and tools to make smart decisions on a day-to-day basis. This course provides a framework for making financial decisions, such as saving money, paying student loans, leasing or purchasing a car, and other strategic choices .

Python for Everybody Specialization

Work with program applications by visualizing, retrieving and processing data with Python. This series of courses introduces the fundamental programming concepts of the Python programming language used in data structures, networked application program interfaces and databases. Enroll in this MOOC to learn these concepts, which can assist in building valuable skill sets to leverage for school projects, enhance impact in your internship and career.

Successful Negotiation: Essential Strategies and Skills

This course explains the core strategies, tactics and steps involved in planning and successfully negotiating everything from job offers, salary range and and work relationships to structuring business strategies. Enroll in this MOOC as a way to explore negotiation strategies while building lifelong skills to leverage in a variety of educational and professional situations.

Web Design for Everybody (Basics of Web Development and Coding)

Jump start your next step, either professionally or vocationally, by learning to develop professional quality web sites. This Specialization covers how to write HTML5 and CSS3 in order to create interactive web sites that are accessible on mobile, tablet and large screen browsers. Take this course and learn the skills for designing and building a professional web portfolio for creative work, resume building and professional enhancement.

Enroll in a MOOC to continue your U-M learning.

To check out more about learning opportunities visit our Learn with U-M portal.    

 

Globalized Physics for Advanced Learners: Interview with Professor Garikipati

Onawa Gardiner, Marketing Specialist
@onawanna

As we continue to enable engaged, personalized and lifelong learning for the Michigan community and learners around the world, we are committed to providing a diversified range of MOOCs that are accessible to global learners and learners in different stages of their education and careers. With this approach, we strive to develop MOOCs intended for novice learners while also recognizing the needs of advanced learners seeking to strengthen their knowledge base and skill set in a specialized area.

Professor Krishna Garikipati has developed two specialized MOOCs focused on physics that are specifically designed for advanced learners seeking to gain greater understanding of specialized methods in physics, which play a fundamental role in a number of research, education and industrial fields: The Finite Element Method in Physics and the Lectures in Continuum Physics. We recently sat down with him and discussed his inspiration for developing these courses, as well as his experience teaching specialized courses through an open format with a globalized audience.

What was the inspiration for developing specialized MOOCs that target advanced learners, rather than a broader, generalized audience?

The inspiration comes from my research. In my group, we develop mathematical models that describe the physics of materials and biological systems, as well as the numerical methods and computational frameworks needed to investigate a range of interesting phenomena with them. This field, which I refer to as computational physics, is advanced stuff, but is important in a number of industrial settings (automotive, biomedical, electrical, semiconductor, manufacturing, chemical, structural…) in addition to representing a broad and active research area in academe. Advanced computer programming is also central to this type of research. About three years ago, I had been following the evolving conversation on MOOCs, and was intrigued by the idea of developing them for computational physics. I was encouraged particularly by the fact that the first MOOC was in a computer programming-heavy subject: artificial intelligence. The multifaceted nature of the community that is involved in computational physics, I felt, would offer an interested audience. The way that this has been borne out has actually exceeded my expectations.

How do your two MOOCs, the Finite Element Method for Problems in Physics and Lectures in Continuum Physics, aim to contribute to diversity, equity and inclusion, both residentially and globally?

The way the numbers break down, the Finite Element Method MOOC reaches scores of learners  in Africa, hundreds in Latin America and thousands in South Asia. So, access is being provided to a very diverse audience. Comments in the forums suggest that many of these learners do not have access to brick and mortar campuses that teach these advanced topics. The open source/open access software packages that we used in the Finite Element Method MOOC are right at the cutting edge of computational physics research. I think it is very compelling that such a diverse audience is gaining this exposure that could set some members of that audience on the road to higher education with a research component, much like we have in the world’s best universities. Furthermore, to ensure that no learner would be left behind, we provided the entire software suite on Amazon Web Services (AWS), bundled in a manner that would not require resources beyond those available via AWS’ free instances. There is the possibility that some of these diverse, global learners will end up in residential universities, propelled by their exposure to these advanced MOOCs.

How does the global dissemination of these two MOOCs that focus on physics serve to expand learners’ foundational knowledge in the sciences?

We (I and my student Greg Teichert, who did the coding tutorial lectures) write out everything in both these MOOCs. No prepared slides, but a total of over 70 hours of physics and numerical methods written out painstakingly. Almost unanimously, the audience (global and residential) has expressed appreciation of this approach, which makes the mathematical content come alive. This, they insist, leads to far deeper foundational learning in the mathematical sciences.

What outcomes have you observed with learners who have taken the Finite Element Method for Problems in Physics MOOCs and what learning outcomes do you expect to see from students who take the Lectures in Continuum Physics MOOC?

Students of the Finite Element Method MOOC become proficient scientific programmers in modern programming languages, and learn how the careful development of the mathematical content leads to workable scientific code for computational physics. The Continuum Physics MOOC translates sophisticated mathematics to insight for the physics. I expect that those learners will see that connection very clearly.

To learn more about Professor Garikipati’s MOOCs on physics, visit: The Finite Element Method for Problems in Physics and Lectures on Continuum Physics.  

 

Krishna Garikipati

Krishna Garikipati
Professor, Departments of Mechanical Engineering and Mathematics
College of Engineering and College of Literature, Science and the Arts
University of Michigan
@KrishnaGarikipa

Panel Speakers for U-M edX Workshop Announced

Onawa Gardiner, Marketing Specialist
@onawanna

As we continue to shape the future of learning and redefine public residential education at a 21st century research university, we are excited to host the U-M edX Workshop: Exploring MOOCs and Academic Innovation on May 3 – 4. This workshop is designed for faculty across campus to join us for an informative, interactive two-day session to learn about MOOCs (massive open online courses) and other opportunities for academic innovation at U-M.  Participants in this workshop will explore new opportunities to advance online pedagogy, create more diverse and inclusive learning environments, engage in research, and increase access to academic excellence at Michigan. They’ll hear from current U-M faculty on their experiences as MOOC instructors and researchers, and from edX, a nonprofit, open source MOOC provider and online learning destination.

U-M has been a charter member of the edX consortium since Fall of 2015 and became a founding partner of Coursera in 2012. In that time U-M has created nearly 50 MOOCs and reached more than 4 million lifelong learners. More than 40 U-M faculty to date have experienced working with Coursera and/or edX. Through creative initiatives they have collaborated with DEI to leverage the MOOC environment to design personalized, engaged and lifelong opportunities for the U-M community and learners around the world.

The workshop will kick off with the MOOC Experiences, Opportunities and Insights Panel featuring U-M faculty who have created MOOCs. This informal panel discussion will focus on how faculty have designed MOOCs to reach global learners and how that process has changed the way they think about teaching and learning on campus. The panelists will briefly discuss their experiences and answer questions from the audience as a part of this interactive session. The featured panelists will include the following U-M faculty partners:

Elizabeth DuDr. Elizabeth Du, M.D., Clinical Assistant Professor

Department of Ophthalmology & Visual Sciences, Kellogg Eye Center

Introduction to Cataract Surgery MOOC

Krishna GarikipatiDr. Krishna Garikipati, Professor, Departments of Mechanical Engineering and Mathematics

College of Engineering and College of Literature, Science, and the Arts

Lectures in Continuum Physics MOOC
The Finite Element Method for Problems in Physics MOOC

Gautam KaulDr. Gautam Kaul, Fred M. Taylor Professor of Business Administration, Professor of Finance

Ross School of Business

Finance for Everyone: Smart Tools for Decision-Making MOOC
Introduction to Finance: Valuation and Investing Specialization
Introduction to Finance MOOC

Charles SeveranceDr. Charles Severance, Clinical Associate Professor

School of Information

Python for Everybody Specialization
Internet, History and Technology MOOC
Programming for Everybody: Python MOOC

Colleen van LentDr. Colleen van Lent, Lecturer IV

School of Information

Web Design for Everybody (Basics of Web Development and Coding) Specialization

Margaret WooldridgeDr. Margaret Wooldridge, Arthur F. Thurnau Professor, Departments of Mechanical and Aerospace Engineering

College of Engineering

Introduction to Thermodynamics: Transferring Energy from Here to There MOOC

 

After the panel session, participants in the workshop will continue to explore the world of MOOCs with sessions featuring additional U-M faculty partners, edX speakers and DEI faculty. These sessions will include a range of topics, including MOOC design, best practices for engaging with students and exploring creative new models of learning. For the second day of the workshop, participants can choose between either a research based session or hands on training.

We look forward to hearing from our collaborative faculty partners during the panel discussion and sharing experiences and insights throughout the U-M edX workshop with edX guests, DEI staff and faculty on creative initiatives underway as well as exploring academic innovation at Michigan.

Registration for this panel discussion and to the U-M edX Workshop is currently open. To RSVP: U-M edX Workshop: Exploring MOOCs and Academic Innovation.

Impact of Data Science: An Interview with Professor H. V. Jagadish

Onawa Gardiner, Marketing Specialist
@onawanna

On May 1, Professor H.V. Jagadish, in collaboration with DEI, will launch the Data Science Ethics MOOC on edX. This MOOC serves to cultivate guidelines for ethical practices that are broadly applicable across the data science field. Professor Jagadish, as an expert on data science, has contributed to publications such as Slate Magazine, U.S. News and the Conversation U.S. In addition, he has recently received a grant from the Bill and Melinda Gates Foundation to leverage data to promote social good through the Foundation’s Grand Challenge Explorations. He also discusses key issues regarding ethics in data science with his blog, Big Data Dialog.

We sat down with Professor Jagadish to discuss the importance of ethics in this growing field and the impetus for creating a MOOC that provides a structure for data science ethics.

Data science illustration

What motivated you to design a succinct, educational module for data science ethics and how do you see this course being used in the future?

Data Science is having a huge impact on our society today. While the progress in Data Science is mostly in terms of better technology—better systems and better algorithms—it is not true that Data Science is all about technology. Rather, as sentient beings in a rapidly changing world, we need to be aware of where technology begins and where it ends. As a technologist myself, I have seen far too many techies who confine themselves into a narrow technology box and refuse to see the real impact their work is having on people. My goal is to enrich the education of every Data Scientist so that they can see the impact they are having on the world, own this impact, and ensure that this impact is in line with what they would like to see happen.

Your blog, Big Data Dialog, focuses on validity, privacy and fairness as the three pillars for data science ethics. What was the reasoning for selecting these three and how do they, together, form the basis for ethics in data science?

Ethics is a very broad topic, and there is a great deal of deep philosophical thinking about ethics. My goal, in my course, is to package something that summarizes and encapsulates a few key concepts that provide the typical Data Scientist with the tools to reason through most situations they are likely to face. While I do not have the same constraints in my blog, I do feel strongly that a blog has the greatest impact if it is organized by topic. I have chosen three major themes in Data Science Ethics as the initial organizing structure for my blog; validity, privacy and fairness.

How has working with DEI and edX on creating a MOOC brought to light new aspects or resulted in you reevaluating certain aspects of ethics in data science?

The DEI team has been fantastic to work with. They have asked me many penetrating questions that has resulted in my thinking hard about the objectives of this MOOC and the best way for me to present the material I have in mind. I believe that this MOOC is very much improved due to their penetrating questions and creative input.

How have recent news surrounding algorithmic bias confirmed the fallacy of the notion that data speaks for itself? How can ethical guidelines address this?

Yes, algorithmic bias has indeed been in the news recently, and is a great example that illustrates why it is not enough for Data Scientists merely to manage and analyze a given data set, but rather to understand what the goals of the analysis are and to own the impact of their work.

What are some ways you have observed the data science field evolve and how has it changed to necessitate the formation of structured ethical guidelines?

We all make thousands of decisions every day, which collectively have an impact on us as an economy, as a society and as a planet. These decisions could be as banal as what time to wake up in the morning, what brand of toothpaste to use and what route to take to work. For most of us, for most of these decisions, understanding the broader impacts is too much: we just want to decide based on our local preferences and move on. But, in the aggregate, it does matter what decisions each of us makes individually. Technological progress is similar. Creative minds devise new ways of doing something. Just finding the new way is progress enough: it is unfair and progress-impeding to ask them to address hard to identify consequences. However, as a technology matures, and particularly as it begins to have the kind of pervasive social impact that Data Science does today, it is no longer possible to ignore the societal effects. Ethical guidelines then become crucial.

As we continue to see more emphasis on data science, how do you anticipate the role of ethical guidelines will change and grow in the future?

The greater the impact of Data Science on our society, and the greater the number of different spheres in which this impact occurs, the greater will be the importance of considering ethics.

Enrollment is open for Data Science Ethics, which will launch on May 1. To learn more and/or to enroll visit Data Science Ethics.

 

H.V. Jagadish
Professor of Electrical Engineering and Computer Science
College of Engineering
University of Michigan

New Specialization: Survey Data Collection and Analytics

The Survey Data Collection and Analytics Specialization, an inter-institutional collaboration between the University of Michigan and the University of Maryland, launches April 4. The six-course series of MOOCs provides learners with techniques to collect and analyze good data from various sources and effectively communicate results. With this new Specialization, the U-M Office of Digital Education & Innovation (DEI) continues to shape the future of learning by enabling personalized, engaged, and lifelong learning for the U-M community and learners around the world.

“We’ve entered an era where it’s now well understood that data analysis and visualization skills are incredibly valuable for professionals across fields and industries,” says James DeVaney, Associate Vice Provost for Digital Education & Innovation. “We are excited by our newest digital learning offering as it prepares learners not only to understand how to effectively analyze data and communicate results but also how to apply the best mix of techniques to collect good data in the first place.”

The Survey Data Collection and Analytics Specialization teaches the tools and techniques needed for professionals to source diverse types of data in order to collect information to be used for market research, evaluation research, social science, political research and official government statistics. Professionals in NGOs, government agencies and anyone whose work incorporates customer surveys and/or data collection on a regular basis will find this Specialization useful to understand the importance of collecting quality data and for implementing best practices that differentiate useful data from the large swathes of data available in order to curate useful and correct input.

The Survey Data Collection and Analytics Specialization builds off the success of the Questionnaire Design for Social Surveys MOOC, which has reached over 65,000 global learners and helped to establish a framework for creating well-designed surveys. The Survey Data Collection and Analytics Specialization expands upon the subject of survey design and delves into key aspects for collecting and using data. The Specialization will release the following six courses sequentially: Framework for Data Collection (available today), Questionnaire Design, Data Collection Methods, Sampling People Networks and Records, Dealing with Missing Data and Combining and Analyzing Complex Data.

“Michigan is interested in preparing diverse learners to solve complex global problems,” said DeVaney. “With complex global problems, the data required for breakthrough doesn’t often live in a single tidy discoverable file. 21st century problem solvers have to know how to collect good data in order to analyze and communicate. We’re thrilled to further expand our partnership with Coursera and to share expertise and learning resources from U-M’s Institute for Social Research, and the Joint Program in Survey Methodology, with learners around the world.”

This Specialization, the result of the collaborative efforts of Professors Frederick Conrad and James Lepkowski from the University of Michigan and Professors Frauke Kreuter and Professor Richard Valliant from the University of Maryland, showcases the potential for innovation to arise from collaboration between institutions. The Specialization aligns with U-M President’s Schlissel’s priorities to enhance U-M excellence through inter institutional collaboration in order to foster experimentation and innovation in education, on both a residential and global scale. The seed for this collaborative endeavor can be sourced to the faculty partners’ involvement with the University of Michigan’s Institute for Statistical Research (ISR) which is the world’s largest academic social science survey and research organization. Professors Conrad, Lepkowski, Kreuter and Valliant have collaborated together on numerous committees and development activities over the past decade through their participation in the Michigan Program in Survey Methodology through the ISR and the Joint Program in Survey Methodology through the University of Maryland.

The University of Maryland is the state’s flagship university and one of the nation’s preeminent public research universities. A global leader in research, entrepreneurship and innovation, the university is home to more than 37,000 students, 9,000 faculty and staff, and 250 academic programs. Its faculty includes three Nobel laureates, three Pulitzer Prize winners, 47 members of the national academies and scores of Fulbright scholars.

DEI aims to redefine public residential education at a 21st century research university through the creative use of technology and targeted experimentation with digital programs in order to enable engaged, personalized and lifelong learning for the entire Michigan community and learners around the world. To date, U-M has reached more than 4 million lifelong learners through MOOCs developed by faculty in partnership with DEI and continues to be a pioneer in digital learning and learning analytics. This Specialization is part of a continued commitment from DEI to transform 200 courses by 2017.

Enrollment for the first course in the Survey Data Collection and Analysis Specialization is currently open. To enroll/for additional information, please visit: Survey Data Collection and Analysis Specialization.

Creators

Frederick Conrad
Professor Frederick Conrad
Research Professor, Survey Methodology
Institute for Social Research
University of Michigan

James Lepkowski
Professor James Lepkowski
Research Professor, Survey Methodology and Professor of Biostatistics
Institute for Social Research and School of Public Health
University of Michigan

Frauke Kreuter
Professor Frauke Kreuter
Professor, Joint Program in Survey Methodology
University of Maryland

Richard Valliant
Professor Richard Valliant
Research Professor, Joint Program in Survey Methodology
University of Maryland

ART 2.0 Launches CourseProfile Service

Academic Reporting Tools 2.0 (ART 2.0), a suite of data visualization services that render U-M course and academic program data in order to help students, faculty, and administration make informed decisions, has released a first service to campus called CourseProfile. The tool was developed by a team within the Digital Innovation Greenhouse (DIG), part of the Office of Digital Education & Innovation (DEI), led by Arthur F. Thurnau Professor of Physics and Astronomy August Evrard.

ART 2.0 aims to provide robust data on courses and programs from past academic terms in a user-friendly format to further enable personalized and engaged learning on campus. By increasing the amount of information available for students and faculty alike, ART 2.0 is fostering a community that leverages data for better decision making and opportunities at U-M, promotes transparency and serves as a driving force for innovation. Additionally, the tool harnesses data to improve understanding of how learning procedures and teaching practices affect learning while providing more insights into courses, academic programs and student learning at U-M. Currently, data is available for nearly 9,000 courses across U-M.

ART 2.0 is an updated and extended version of a service tool originally developed in 2006 by the LSA Information Technology Advisory Committee. That service focused on data surrounding course enrollment, grade correlations among courses, the impact of standardized test scores on course performance, and other curricular features. In 2014, ART 1.0 was selected as a program to be scaled up through DIG in order to enhance its impact and usefulness as a tool for faculty, staff and students.

The Digital Innovation Greenhouse (DIG) consists of a team of software developers, user experience designers, behavioral scientists and multi-disciplinary student fellows that works directly with user communities within U-M in order to provide resources for homegrown educational software innovations on campus and scale up these digital enterprises to maturity through collaboration across U-M’s digital ecosystem.

DEI aims to redefine public residential education at a 21st century research university through the creative use of technology and targeted experimentation with digital programs in order to enable engaged, personalized and lifelong learning for the entire Michigan community and learners around the world. DEI houses three labs, the Digital Innovation Greenhouse, the Digital Education & Innovation Lab and the Learning, Education, & Design Lab, within its infrastructure. To date, U-M has reached more than 4 million lifelong learners through MOOCs developed by faculty in partnership with DEI and continues to be a pioneer in digital learning and learning analytics.

The ART 2.0 CourseProfile service is available to the U-M campus community at Academic Reporting Tools 2.0