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IOE undergraduates prep for a modern workforce with expanded data analytics courses and support

U-M IOE makes curriculum changes to enhance the data analytics and computing skills of its undergraduate students, including creating a new advanced analytics course for seniors.| Medium Read

In 2018, U-M Industrial and Operations Engineering (IOE) faculty set their sights on strengthening their undergraduate students’ data analytics and computing skills. With the goal of fully-preparing students for the modern workforce and advanced studies, the department has enhanced the curriculum by incorporating computing and data analytics into many existing courses, creating a new advanced analytics course for seniors, and implementing a new help desk to support students.

Emphasizing Data Analytics Using R and Python

One of the main opportunities identified was to emphasize R and Python in key courses with computational or data analytics components. Previously, many different programming languages were used in U-M IOE classes, and some of them were no longer as popular in industry and academia as they once were.

“By introducing some uniformity, students will have an easier time navigating data analytics and computational tasks across the curriculum, and with these particular tools they will have better control of some key technologies that are commonly sought by employers,” explained Eunshin Byon, U-M IOE associate professor and leader of the faculty group implementing the changes.

"By introducing some uniformity, students will have an easier time navigating data analytics and computational tasks across the curriculum, and with these particular tools they will have better control of some key technologies that are commonly sought by employers."Eunshin Byon, Associate Professor, U-M Industrial & Operations Engineering

Many existing courses have been refined to include data analytic components. For example, Data Processing (IOE 373) that teaches programming and concepts of algorithms and data structures, now includes a more robust collection of tools including data manipulation and visualization, inferential statistical analyses, and predictive analytics and machine learning using Python.

The course name has been updated from “Data Processing” to “Data Analytic Tools and Techniques” to reflect this new focus and content.

New advanced 400-level data analytics course

Another change on the horizon is the creation of a new advanced 400-level data analytics course. This course, offered for the first time next semester, will teach advanced topics in applied data analytics, including fundamental computational tools and methods such as machine learning.

“The new course will involve concrete case studies from real-world applications,” said Byon. “We aim to expose students to a variety of data analytics methods and then showcase the applicability of these methods through a diverse set of real-world problems. This course will be offered in the winter 2021 term as a special topics class, Advanced Topics in Applied Data Analytics (IOE 491).”

Portrait of Eunshin Byon

"The new course will involve concrete case studies from real-world applications. We aim to expose students to a variety of data analytics methods and then showcase the applicability of these methods through a diverse set of real-world problems."

Eunshin Byon, Associate Professor, U-M Industrial & Operations Engineering

The new course builds on the learning outcomes of existing data analytics courses such as Introduction to Engineering Data Analytics (IOE 363) that emphasizes modernized data analytics techniques and statistical tools.

New Data Analytics and Computing Help Desk

To help support U-M IOE students who do not have a background in programming, the department has created the Data Analytics and Computing Help Desk. This includes hiring two instructional assistants (IAs) who have expertise in R and Python.

The IAs record tutorial videos and post the videos and useful handouts in the dedicated Help Desk website on the U-M IOE Canvas platform. They also hold office hours to answer any R and Python-related questions from students.

This semester, Christopher Schemanske and Gongyu Chen, are working as IAs for the Help Desk.

“It’s been exciting to work on this initiative, especially knowing its importance to IOE’s future.  Understanding the struggles students face with programming, specific to what we’re asking for in IOE, has been important for developing the Help Desk as a support tool,” said Schemanske.

“From my perspective, a big picture consideration is that the Help Desk serves as a platform for students to communicate their insights into applied programming in the IOE context and resolve programming-related IOE problems together,” said Chen.

Schemanske views the new help desk as a valuable vehicle for promoting equity as U-M IOE introduces programming’s more important role in the program. “In some cases, a student’s programming experience can be representative of their personal, educational background,” he said. “Most students utilizing the help desk’s resources have little programming experience beyond their first-year class, ENGR 101, so it’s been critical to figure out how to bridge the knowledge gap between that course and the expected knowledge in IOE courses. On the whole, it’s rewarding to be a part of helping students grow this essential skill.”

Based on the success and positive feedback from students and faculty, U-M IOE plans to expand the Help Desk service to assist graduate students, especially master’s students who need to develop skills quickly for success in their future careers.

Researchers
  • Eunshin Byon

    Eunshin Byon

    Associate Professor of Industrial and Operations Engineering

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