Teaching Strategies

ChatGPT can be used to generate learning objectives that reflect taxonomies of learning, such as those in Bloom’s cognitive domain: knowledge, comprehension, application, analysis, synthesis, and evaluation. This can help educators ensure that their learning objectives are aligned with the appropriate level of cognitive complexity and that they are challenging but achievable for their students. Of course, instructors should review and refine AI-generated learning objectives to ensure that they are appropriate for their course and student population. Instructors might also consider adapting their objectives given the proliferation of AI use in our lives. To this end, learning objectives might also be evaluated against Bloom’s Taxonomy Revisited (Oregan State University, 2023). 

Generative AI tools, like ChatGPT, can generate assessment and survey questions of varying types (factual, evaluative, etc.) and formats (true-false, multiple choice, matching, short answer, etc.). These could be used in formal and informal assessments, knowledge checks, and even allow students to create their own self-assessments and set personalized learning goals. An added benefit of using generative AI is it can generate massive question pools.

Generative AI tools can generate multiple scenarios or compile real-life scenarios based on keywords, providing students with ample opportunities to apply concepts and theories in these scenarios.

Generative AI tools can be programmed to generate different levels of prompts and assessment questions based on Bloom’s Taxonomy. This means that students of different ability levels can be challenged and engaged at their own level, as the AI can provide appropriate prompts and questions based on the cognitive complexity of the topic being studied.

Adaptive learning is an approach to education that tailors the learning experience to the needs and preferences of individual students. This means that rather than providing a one-size-fits-all curriculum, adaptive learning uses data about and insights into the student to deliver personalized content and instruction. One of the challenges of adaptive learning is the time and effort required to create personalized learning materials for each student. Educators need to design multiple sets of learning materials, including activities, case studies, and assessments, to personalize the learning process.

However, with the help of generative AI tools, this process can become much easier and more efficient. AI can analyze data about the student, such as background and learning preferences, and generate multiple series of learning activities, case studies, and assessments tailored to the student’s specific needs.

For example, one student is interested in real estate, whereas another is interested in banking. The tool can then generate personalized learning materials that focus on these specific areas, helping each student develop competencies in their own area of interest.

Generative AI tools can easily design activities of various formats for learning purposes.

Students can develop critical digital literacy skills by evaluating or critiquing a product written by a generative AI tool. What information is not accurate? Is there information missing? Is the information false or misleading? How can students find out the answers to these questions? What can students write to make the response more meaningful? t may be helpful to develop this type of activity using the OSU CC-BY-4.0 doc: Blooms Taxonomy Revisited.”

Faculty who are anticipating students’ use of generative AI in their course, or those who are concerned with the tools, have an opportunity to set expectations in their course syllabi and in written instructions for individual assignments. Currently, integrating or limiting the use of AI is at the individual JHU faculty’s discretion.

In Fall 2023, Oregon State University’s College of Business rolled out a set of icons for faculty to embed in their syllabi and assignments to indicate to students what role AI might play in the course. Voluntary for now, the goal is to establish some common language and consistency for students across the university regarding AI usage in courses. The four syllabi icons include an ‘X’ for no AI permitted, a quarter circle for minor AI usage, a half circle for AI integration into some of the course, and an exclamation point for specific expectations and notes provided by the faculty regarding AI usage. The assignment icons are more varied, depending on what type of assignment is used. With each icon, faculty are encouraged to include detailed descriptions and examples of what is and is not acceptable.

In Summer 2023, Oregon State University “reinvented” Bloom’s Taxonomy to account for the integration of AI into coursework. In addition to an enhanced graphic, more detailed guidance and considerations are provided for faculty including how AI tools might be used in learning activities and assessments for each level of Bloom’s.