In the fall of 2025, Mechanical Engineering and Library faculty will develop and pilot Artificial Intelligence (AI) literacy learning outcomes within a Mechanical Engineering and Physics courses. The university currently does not have institution-wide AI literacy learning outcomes or systematic support for AI instruction. In preparation, the faculty will collaborate to create an AI literacy framework for courses in which students carry out quantitative experimentation. Instructional and assessment materials designed to teach students about the uses, ethical implications, and limitations of AI throughout the technical paper writing process will be created. Students will practice and evaluate the use of AI throughout the experimentation process, including the literature search, interpretation of past work, data analysis, and manuscript review.
This project seeks to advance AI literacy across diverse educational contexts and to provide an instructional opportunity to establish an equitable understanding about the application of AI, regardless of the level of an individual’s prior exposure. The materials will be designed to be applicable in any course where students pair research with quantitative data analysis. This work-in-progress paper will present the theoretical models and existing research that will inform the creation of the AI literacy learning outcomes and framework. The authors will make use of research on AI literacy and competencies across disciplines within and outside of Engineering and Library Science to determine the current state and efficacy of AI literacy instruction at the undergraduate level. This paper will not explore individual AI tools but rather provide a foundational overview of the competencies and skills students need to engage with current and future AI tools.
The full paper will be available to logged in and registered conference attendees once the conference starts on June 22, 2025, and to all visitors after the conference ends on June 25, 2025