Curriculum Development Efforts

Adding Visual Aids to CMSE 201

Folks Involved: E. Bolger (lead), D. Silvia

For her Mentored Teaching Project as a part of the Certificate of College Teaching, Emily integrated visual aids in the CMSE 201 course materials to help students strengthen their understanding of coding practices like lists, data frames, and two-dimensional arrays, particularly in relation to indexing with those tools. The purpose of the visual aids was to help students conceptualize the structure of the object as well as walk through examples that showed information retrieval from these objects. We also embedded guided questions for students to practice explaining their coding choices and implementations. Specifically, we were looking to study how students think about and explain code using descriptive language to their instructors, fellow coding classmates, and non-coders. To assess the modifications implemented in the CMSE 201 curriculum, we used three methods: bi-semesterly survey, in-class student observations, and class assignment observations. While we struggled to encourage students to respond to the written critical thinking questions, we noticed that the students asked more targeted, thoughtful questions and referred to the visual aids frequently throughout the course.

AI in the Real World: Data, Power, & Society (CMSE 101)

Folks Involved: D. Caballero (lead)

We are developing CMSE 101, a new course that explores how artificial intelligence and modern society shape one another. Rather than treating AI as either a threat or a cure-all, the course asks students to examine its applications, limitations, and implications across ethics, policy, economics, employment, and justice. Through readings, case studies, and student-designed cases, students trace how AI technologies have been used in domains such as education, healthcare, and criminal justice, and consider their impacts on individuals and communities. The course is organized around the Data, Tools, Practices, and Actions (DTPA) framework, which helps students analyze how these four elements relate to one another, and moves from historical to contemporary to future-oriented case studies so students can see how these relationships change over time. Our goal is for students to become critical pragmatists who can navigate the ethical, social, and political dimensions of AI in their personal and professional lives. All course materials are openly available on the course website and GitHub, which is designed with accessibility controls and offers materials in multiple formats. The course has been shaped by contributions from across CERL, and we are especially grateful to Vashti Sawtelle and Isaac Record for their thoughtful input on the course’s design and framing. This work is supported by Michigan State’s AI-Ready Spartans Initiative.

Ethical Impact of STEM Professionals on the Holocaust and Beyond

Folks Involved: R. Roca, E. Bolger, R. Frisbie, V. Piercey

Roca, Bolger, and Frisbie have begun a collaboration with professor and Honors Program Director Piercey, historians at Ferris State University, and the Zekelman Holocaust Center in Detroit. Honors students from CMSE at MSU and the Math Department at FSU will have the opportunity to study the ethical impact of STEM innovation in the Holocaust. Students will research a STEM professional involved in the Holocaust, visit the Zekelman Holocaust center, discuss their research with students from the other school, and present their findings at both universities. We anticipate this timely experience to be highly impactful for our students, giving them the space to grapple with their impact as a future STEM professional by considering the past.

Data Literacy and Ethics in CMSE 201

Folks Involved: Emily Bolger and Rachel Roca

Following a class assignment, Rachel and Emily developed a research backed CMSE 201 assignment to help students learn about bias that’s inherent in data and the implications it can have on hiring practices. Students interact with the simulation “Survival of the Best Fit” developed by Gabor Csapo, Jihyun Kim, Miha Klasinc, and Alia ElKattan and take a deeper dive into the data creation. This assignment explores the nuances of impact vs. intent of using AI, interrogates how bias shows up in data and algorithms, and celebrates students’ abilities to read and interact with outside code while supporting their self-efficacy. Their materials can be found here.