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Generative AI as a Learning Tool in the Sciences

Originally published in September 2024

Approaching Generative AI Tools in the Sciences

Generative AI tools and technologies are increasingly present in science education, and instructors have a valuable role to play in teaching about the effectiveness and application of generative AI tools as they prepare students for future professions. For example, generative AI tools and technologies are now routinely being embraced, adopted, and integrated within the disciplinary practice of numerous fields of science, such as pharmacy (i.e., antibiotics), imaging, drug discovery (i.e., proteomics), and personalized medicine (Ghebrehiwet et al., 2024; Bhardwaj et al., 2022; Abdellatif et al., 2022).  
At the same time, educators can demonstrate where generative tools are lagging in robust evaluation capabilities and factual accuracy, as well as identify frameworks for ethical use in science and society more broadly. For example, instructors can support student learning by encouraging the analysis of unexpected data (e.g., outliers) and contextualizing results within the broader field – areas where AI may fall short (Cooper, 2023; Shaw et al., 2023).  
To support instructors in deciding how to approach authorized use of generative AI, below are some common activities and assessments in science education to consider through a generative AI lens. 

Laboratory Reports

Lab reports are commonly used in science education to assess laboratory activities. Using a generative AI lens, AI-generated lab reports have been found to be vague, general, and generate fake citations (Wang, 2023; West et al., 2023), giving instructors an opportunity to develop detailed assessment criteria and teach students critical evaluation of AI outputs (and watch Christian Danve Castroverde's new Assessment Snapshot featured later in this bulletin for more on this!)    
To mitigate AI use, instructors may wish to: 
  • emphasize the value of in-person activities in the assessment practice where performing experiments, following procedures, and measuring outcomes builds foundational skills;  
  • integrate process-oriented strategies by requesting that students submit laboratory notes to demonstrate their work and engagement with the activities;  
  • highlight the importance of metacognitive elements where students reflect on their learning experience through the interpretation of collected data, and/or an explanation of missteps (i.e., errors and/or unexpected results). 
To integrate AI use, instructors may wish to: 
  • encourage students to critically evaluate a baseline AI-generated lab report and ask students to verify results, identify materials or procedures, and/or discuss the robustness of output;
  • invite students to use AI as a collaborative partner to facilitate the interpretation of failed experiments. 

Anatomy Laboratories

Anatomy Laboratories are common instructional methods for numerous biology and health-related courses. These laboratories incorporate three-dimensional structures and two-dimensional images. Students can be asked to actively locate and identify structures and features including muscles and bones, with origin and insertion points as well as nerves and vessels. The tactile experience of these labs provides a rich hands-on learning experience. The value of these in-person instructional activities engages the senses in the learning process, i.e., trace, touch, and feel. 
To mitigate AI use, instructors may wish to:  
  • emphasize the process of learning with the hands-on approach of touching, feeling, and tracing various anatomical structures; 
  • incorporate course-specific elements with reflective learning activities whereby students are asked to reflect on their participation in physical activities and exercises to experience the movement of extremities, joints, and muscles.  
To incorporate AI use, instructors may wish to: 
  • use AI-generated images to demonstrate to students the limited abilities of these tools to generate accurate images;  
  • encourage students to highlight inaccuracy, lack of precision, and errors and make corrections;
  • engage students with critical evaluation of AI-generated images and comparative analysis with in-class resources.  

Specimens & Artifacts 

Specimens and artifacts are routinely used in multiple different types of courses in the sciences. These can include histology or other slides, preserved tissues, bones, taxidermy specimens, impressions, fossils, stones, and shells, to artwork (e.g., clay bowls), as a few examples.
To mitigate AI use, instructors may wish to:  
  • incorporate specimens into their instructional practice with assessments designed to address specific features of the exact specimens used in class;  
  • invite students to hand-draw their own pictures and/or create visual notes using the exact specimens that were provided in the classroom. Students could be asked to include labels, create a description and/or narrative of the specimen with concepts from the course as a way to demonstrate their learning process.  
To incorporate AI use, instructors may wish to: 
  • include generative AI-created images of local specimens in their course and ask students to evaluate the correctness, accuracy, and completeness of the images;  
  • utilize generative AI to create descriptions of various specimens that are used in the courses and ask students to enhance these descriptions with more specific and local contexts.   
What is key in approaching generative AI is to guide students toward using AI responsibly and ethically, emphasizing the importance of their own critical thinking and creativity.

Assessment Snapshot: Generative AI as a Learning Tool in Biology 

Christian Danve Castroverde from Laurier's Biology department shares an assignment that integrates generative AI tools to enhance student understanding of how these tools may support or detract from learning. Emphasizing scaffolded learning, detailed instructions, and transparent grading, Danve highlights the benefits and challenges of using AI tools in education and reflects on student performance and the potential for AI in learning. Watch the Video >>
Explore more ways our colleagues are engaging with Generative AI tools: 

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