Written by Kevin Forman and Rob Piercy
Center for Innovative Teaching and Learning (CITL) instructional designers and NIU faculty are collaborating and integrating AI tools to re-design course content, fine-tune formative and summative assessments, and create engaging and meaningful discussions in online asynchronous courses.
AI is revolutionizing how we teach, and in nursing education programs, it’s enabling faculty to create more personalized, engaging, and practical learning experiences. Nursing faculty are beginning to explore how AI can simultaneously support learners and help faculty create more authentic experiences in classroom environments. Thus, faculty need to make sure that AI tools are used effectively and ethically, and their oversight ensures that AI integration aligns with course goals and supports academic rigor.
One of the most impactful uses of AI in nursing education is its ability to personalize learning. AI-powered platforms like Nursify AI offer adaptive study tools that help students master complex topics at their own pace. These tools act as skill accelerators, finding knowledge gaps and providing targeted resources to support student success.
Faculty can also use AI to redesign course content and assessments. For example, AI can help in developing authentic assignments that connect theoretical knowledge to real-world applications. An example of this is centered on the use of simulation in Nutrition case-based learning. In a case study, a dietician helps a pregnant woman facing food insecurity during prenatal care. Students are tasked with exploring various intervention strategies, including eligibility for services, policy implications, and access facilitation. This type of scenario encourages critical thinking and exposes students to the complexities of real-world healthcare.
To enhance engagement, faculty can design discussion prompts with multiple response options. Let’s imagine an instructor creating four different prompts for a discussion. Students select one of the prompts and develop their responses accordingly. When students respond to a peer, they must respond to someone who chose a different option from their own. This approach fosters deeper dialogue and collaborative problem-solving—skills essential in nursing practice. Going further, AI can support the grading process for this assessment by generating rubrics based on instructor-defined criteria, ensuring consistent and transparent evaluation.
Speaking of assessment, Anthology Blackboard’s AI integration helps faculty to auto generate assessment questions based on content that is in a course module. The faculty decide the type of questions (multiple choice, fill in the blank, or matching), the complexity based on Bloom’s Taxonomy, and the number of questions (up to 20). Once questions are generated, faculty check questions for accuracy, edit as needed, and create question banks for future use. Rather than spending time writing questions, faculty can now edit and refine AI-generated questions based on original course content, thus innovating and optimizing assessment practices.
Overall, AI offers powerful opportunities to enhance nursing education through personalized learning, realistic simulations, and authentic assessments. Tools like Nursify AI and healthcare chatbots exemplify how AI can support both education and practice, while Anthology Blackboard AI can make assessment more efficient. However, the success of these innovations depends on the ability and guidance of faculty, who should thoughtfully and ethically evaluate and integrate AI to ensure it enriches students’ learning experience and prepares them to enter the world of modern nursing.
How can AI support the development of assessments that are authentic and relevant to real-world nursing practice?