The mission of Atlas is to promote deeper knowledge of the University of Michigan’s curricular history within the Ann Arbor campus community, and, in so doing, support exploration, discovery, and decision making by U-M students, faculty, and staff.
Atlas was first developed as an application called ART (Academic Reporting Tools) within the College of Literature, Science, and the Arts Information Technology Advisory Committee in 2006 as an effort to display academic program data to students, faculty, and administration--encouraging students to explore and make informed decisions about the diverse range of academic opportunities available at the University of Michigan.
In 2014, ART 1.0 was selected by the Center for Academic Innovation to be one of their supported software projects. The team that formed following that decision then released a public interface (ART 2.0) for visualizing academic program information, complete with student evaluations of teaching.
ART 2.0 was rebranded as Atlas in 2019 and was redesigned to improve the user experience of U-M faculty and students, allowing for active discovery of courses, instructors, and major profiles. Today, the platform continues to synthesize and visualize historical academic data in order to support engaged learning at the University.
For questions about Atlas, please contact email@example.com.
The unprecedented disruption to residential classes during the Winter 2020 term due to the coronavirus outbreak has led the U-M Provost and Registrar’s Offices to temporarily change the content and reporting of course evaluations.
Atlas users should be aware of the following changes:
On April 9th, interim Provost Susan Collins stated in the University Record,
“[W]e feel it is important to proceed with evaluations — rather than canceling them — in an effort to maintain academic excellence and integrity, accountability in instruction and to assess and build remote teaching capabilities.”
Eight core evaluation items (five Likert options from Strongly Disagree to Strongly Agree):
Three new evaluation items for the Winter 2020 term: (not included in Atlas)
The Atlas team is made up of University of Michigan faculty, administrators, designers, developers, researchers, and students who are passionate about meaningful academic exploration and discovery.
Senior Software Ambassador
Software Developer Fellow
User Experience Designer
Senior Associate University Registrar
Founder, Thurneau Professor, Physics & Astronomy
User Experience Research Lead
Director, Software Development & UX Design
Associate Director, Research & Development
Associate Registrar for Student Services
Software Portfolio Manager
Eungyu (Dave) Park
User Experience Design Fellow
Software Development & DevOps Manager
Quality Assurance Analyst
Shaelyn Albrecht - User Experience Research Fellow
Peter Chen - Software Developer Fellow
Mike Daniel - Director, Operation & Policy
Dana Demsky - User Experience Design Fellow
Guanchao (Mark) Huang - User Experience Design Fellow
Valerie Le - User Experience Design Fellow
Luc Le Pottier - Data Science Fellow
Nathan Magyar - User Experience Designer
Kushank Raghav - Software Developer
Paul Robinson - University Registrar
Chris Teplovs - Software Developer
Yankun Wang - User Experience Design Fellow
Mike Wojan - User Experience Designer
Xucong Zhan - Software Developer Fellow
Atlas offers comprehensive information, data visualizations, and networked views of courses, instructors, and majors at the University of Michigan, Ann Arbor.
Course Profiles display availability, enrollment, and student evaluation data about an individual course, allowing users to learn about course demographics, student evaluation feedback, average grade distribution, and more.
Instructor Profiles feature recent courses an instructor has taught and a summary of the evaluations students have given that instructor.
Major Profiles show data about students who have received a particular major degree in the last 10 years, including total number of graduates, common co-majors and minors, and most commonly taken courses.
My Dashboard shows students a quick overview of their academic information, including past courses and grades, and any courses, instructors or majors that they’ve saved in Atlas. Once they’ve declared a major, students can also view the most commonly taken courses by students in their major.
View some of what advisors, faculty, and students have to say about Atlas - many thanks to those who have provided feedback throughout Atlas’ history.
“Atlas is one of our favorite advising tools in the Engineering Advising Center! We introduce it to incoming students at Orientation, and they quickly come to rely on it to research courses, instructors, and majors. Advisors use it to access course evaluation data to learn about anticipated workload, student level, enrollment, and common course pathways.”
Kerri Wakefield, Director of U-M Engineering Advising Center
“I adore Atlas. I use Atlas with nearly every advising appointment. It answers most of the common questions I hear from students regarding their courses. It’s an empowering tool for students and advisors alike in creating a degree plan best suited for a student’s interests.”
Kristel Oelke, Senior Academic Advisor
“I wish Atlas had been available to me when and where I was an undergraduate! As a faculty member, I appreciate knowing the degrees, affiliations, and coursework patterns of my students.”
Jim Adams, Shorey Peterson Professor, Arthur F. Thurnau Professor, Professor of Economics, and Secretary to the LSA Faculty
“I really like being able to see what experiences students in my class might have had before, might be likely to have in the future, or might be having concurrently; I use this information to help me think about what students might already know and what they will be likely to need to know.”
Robin Fowler, Lecturer IV, Technical Communication Program
“Atlas provides students with the opportunity to interact with an immense amount of student data to help guide their college education experience.”
Aditi Rao, Neuroscience Major
“Atlas is a simple way of seeing how the majority of previous students actually felt about classes, not just those who wrote a review on Rate My Professors.”
Jay Cutler, LSA
For more student testimonials check out this video!
Percentage of respondents who chose “Agree” or “Strongly Agree” to “the instructor seemed well-prepared for class meetings.”
Percentage of respondents who chose “Agree” or “Strongly Agree” to “the instructor explained material clearly.”
Shows the percentage of respondents who chose “Agree” or “Strongly Agree” to “the instructor seemed well-prepared for class meetings.”
Percentage of respondents who chose “Agree” or “Strongly Agree” to “I knew what was expected of me in this course.”
In 2017, the University Registrar, University Privacy Officer, and the Center for Academic Innovation began working on a set of U-M Learning Analytics Guiding Principles. As we collect and use data for learning analytics, our guiding principles ensure that the creation, collection, analysis, and reporting of learning analytics data remains transparent and secure. These guiding principles also make certain we take privacy and ethical considerations into account.
For example, ensuring that data is not exploited for unexpected or unwanted uses or outcomes, and where appropriate, consent or approval is sought from students we are collecting and/or using data for.
We define learning analytics as, “the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs.”
Respect: We respect the dignity of students and their rights. We strive to balance the good of the students, the University of Michigan’s needs, and improving higher education through learning analytics data. We acknowledge that data students contribute to learning analytics research may benefit themselves and fellow students.
Transparency: We act with transparency, purpose, and specification when collecting and using learning analytics data. We disclose to students the educational interest in and benefits of collecting and analyzing learning analytics data. We inform students about the types of information we collect, how it is used, and how it is shared. We help students understand they are part of a community that seeks to improve approaches to teaching and learning by using learning analytics data.
Accountability: We create processes for the security, integrity, and accountability of learning analytics data. We enforce policies and procedures for appropriate data-sharing, privacy, and data stewardship. We provide ways for students to inspect and review their learning analytics data.
Empowerment: We achieve individual participation in and respect the rights and dignity of students. We have a defined process to scrutinize data accuracy. We aim to use anonymized, de-identified, or aggregated data unless there is a legitimate need to use personally identifiable information with a clear and measurable impact on improving teaching and learning. We give students the ability to view their learning analytics data and to make choices about whether certain identifiable data may be shared.
Continuous Consideration: We continually review and reexamine our learning analytics policies and models to maintain a balance between the benefits of learning analytics for the University of Michigan with the privacy and ethical considerations of students. We welcome students to participate in our learning community, and to inquire about their role in supplying learning analytics data.
For questions about Atlas, please contact firstname.lastname@example.org.
Atlas displays hundreds of pages of course, instructor, and major profiles that allow students, faculty, and staff to gain insight into information such as popular courses and grade distribution. Atlas data can be used to make informed decisions in regards to planning, reporting, and more.
Instructors are only visible on Atlas if they are considered full-time and have taught a course in the past 5 academic years.
In order to protect individual student and instructor privacy, we have data minimum thresholds that were determined in collaboration with U-M leadership. We show “Data not available” or “Data is not available” when there’s not enough data to meet our data minimum thresholds.