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This brief research report presents exploratory findings from a study examining student-use of a mandatory artificial intelligence (AI) disclosure form in a general chemistry and citizen science honors course. Students documented every instance of AI use, describing the AI tool utilized, their purpose, the context of the assignment and their perceived outcomes. Originally created as a practical solution, the form aligns retrospectively with established frameworks in AI Literacy, Digital Ethics, Universal Design for Learning (UDL), and Metacognitive Reasoning. Qualitative analysis of responses identified major themes: verification, immediate academic aid, procrastination, and material obstacles. Findings underscore the disclosure form’s potential as a pedagogical tool, fostering transparency, ethical engagement, and self-regulation. The author proposes broader adoption of the form as a replicable strategy for instructors integrating AI in the classroom and advocates for exposing students to literacy in AI, ethics, and intellectual property. 

This original research article focuses on the investigation of the use of generative artificial intelligence (GAI) use among students in communication-intensive STEM courses and how this engagement shapes their scientific communication practices, competencies, confidence, and science identity. Using a mixed-methods approach, patterns were identified in how students perceived their current science identity and use of incorporating artificial intelligence (AI) into writing, oral, and technical tasks. Thematic analysis reveals that students use AI for a range of STEM communication endeavors such as structuring lab reports, brainstorming presentation ideas, and verifying code. While many minoritized students explicitly describe AI as a confidence-boosting, timesaving, and competence-enhancing tool, others—particularly those from privileged backgrounds—downplay its influence, despite evidence of its significant role in their science identity. These results suggest the reframing of science identity as being shaped by technological usage and social contingency. This research illuminates both the potential and pitfalls of AI-use in shaping the next generation of scientists. 

This perspective article focuses on the exploration and advocacy of approaches to be considered in designing equitable learning experiences for students’ use of artificial intelligence, machine learning, and technology through the Universal Design for Learning Framework (UDL) exemplifying chemistry examples that can be applied to any course in STEM. The use of artificial intelligence (AI) and machine learning are causing disruptions within learning in higher education and is also casting a spotlight on systemic inequities particularly affecting minoritized groups broadly and in STEM fields. Particularly, the emergence of AI has focused on inequities toward minoritized students in academic and professional ethics. As the U.S. education system grapples with a nuanced mix of acceptance and hesitation towards AI, the necessity for inclusive and equitable education, impactful learning practices, and innovative strategies has become more pronounced. Promoting equitable approaches for the use of artificial intelligence and technology in STEM learning will be an important milestone in addressing STEM disparities toward minoritized groups and equitable accessibility to evolving technology.