2025 ASEE Annual Conference & Exposition

The ability to think critically and communicate about data is becoming an essential skill in engineering as data availability is exploding. Students need to evaluate datasets, connect data to appropriate statistical tools, and communicate data to a range of audiences; they need to be data literate.

At [University], students across engineering majors take an introductory probability and statistics course that includes a data literacy module worth twenty percent of the course grade, which meets university requirements for Information and Data Literacy, Communication, Critical Thinking, and Problem-Solving. This course is offered every semester in large blended face-to-face/online sections to an annual total of >1000 students. Based on eleven semesters teaching this course, we identified several challenges with the current data literacy assignments:
1. Students did not work with or create data visualizations, an important element of communicating about data.
2. Students focused on formulaic assignment elements while avoiding making arguments with data, as required for documenting critical thinking.
3. Assignments were not engaging to students, and often required them to research new topics unrelated to the core assignment goals.

This case study documents a multidisciplinary, collaborative process for revising the data literacy module in this introductory probability and statistics course. The Communication instructor, who teaches this module across all course sections, collaborated with a Library faculty member with expertise in developing and delivering data literacy content through discrete instructional modules that the Library maintains. Three goals for the redesign included:
1. To move from a focus on written communication about data and statistics to a multimodal communication process involving the creation of both data visualizations and text.
2. To provide students opportunities to think critically about data and its presentation by presenting arguments that integrate data visualizations with text effectively and professionally.
3. To engage students with problems related to a topic in the news that several different engineering fields are involved in addressing.
Other important considerations included the practicalities of scaling across multiple sections and instructional modalities.

We developed our approach and content drawing from the literature across multiple fields, including information and data literacy pedagogy, technical writing for engineering, argumentation, and data visualization. The resulting problem series offers students assignments with applied engineering problems derived from the existing scientific literature and real-world datasets.
We deployed the new assignments in fall 2024. While we have confidence in the assignments developed, we recognize that some aspects may not work as expected. To formatively evaluate those elements in the assignments needing improvement the instructor teaching the module is compiling observations about how students are reacting to the assignments, and documenting student responses to them during in-class workshops, open help sessions, and office hours interactions. She will review completed assignments with the aim of assessing how well students' work on data visualizations and arguments aligned with the assignment objectives.
We recognize that data literacy is becoming increasingly essential for engineering students, and we hope the embedded data literacy module can serve as a model for other programs.