The expansion of generative AI tools in education illustrates the diverse ways in which it can be integrated into learning environments.

A taxonomy for using AI in education


Key points:

No use of generative AI tools by students
Partial ban of generative AI tools by students
No comment or decision on the use of generative AI by students
Allow for initial creation of prototypes, outlines, idea generation
Allow for AI generation of materials that then require human review
Allow for AI tools without a requirement for human review

As generative AI continues to advance, its potential applications in education grow increasingly varied and complex. Educators and institutions are grappling with how best to integrate these tools into the learning environment while balancing innovation with ethical considerations, assessment concerns, and instructor comfort.

Below is a taxonomy of generative AI for educators to consider. These outline a range of practical options, from restrictive to fully permissive approaches. They could be implemented at the institutional level, but instructors should be given the opportunity to determine the level of generative AI tool use at the course or even the assignment level.

For instance, for my courses around instructional technology topics, I allow students nearly full use of generative AI tools with the caveat that they need to document the tools they used and why they selected those tools. In other courses, I restrict the use of generative AI tools to particular uses for specific assignments. The continuum of options run from a total ban on the use of generative AI tools to allowing students to fully utilize any available tools.

No use of generative AI tools by students

At the most restrictive end of the spectrum, some institutions may opt for a complete ban on the use of generative AI tools by students (and potentially by teachers). This approach stems from concerns about academic integrity, originality, and the potential for AI to undermine the development of critical thinking and problem-solving skills. Schools or instructors adopting this stance may wish to emphasize traditional methods of learning and assessment.

Partial ban of generative AI tools by students

In this case, the use of generative AI tools is restricted in specific contexts or for certain tasks. For instance, AI might be prohibited during exams or in assignments where personal creativity and original thought are paramount. However, its use could be allowed for collaborative projects or in areas where AI can serve as a brainstorming aid. Schools or instructors may choose to ban specific tools as well. This approach seeks to strike a balance between leveraging technological advancements and maintaining academic standards.

No comment or decision on the use of generative AI by students

Some educational institutions may adopt a stance of neutrality, choosing not to comment or make formal decisions regarding the use of generative AI. This passive approach leaves the decision to individual instructors or departments, potentially leading to varied practices within the same institution. While this flexibility can be advantageous, it may also create inconsistencies in how AI tools are utilized and evaluated across different courses. It could potentially cause confusion for students.

Allow for initial creation of prototypes, outlines, idea generation

In this category, students are permitted to use generative AI tools for the initial stages of their work, such as brainstorming, creating prototypes, or generating outlines. The rationale is that AI can serve as a catalyst for creativity, helping students overcome writer’s block or explore new ideas. By using AI in the early phases, students can focus on refining and developing their concepts further, ensuring that the final output is a product of their own intellectual efforts.

Allow for editing and revision of student-generated materials

Another approach allows students to use AI tools for editing and revising their work. Here, AI acts as an intelligent assistant, helping students improve grammar, structure, and coherence in their writing. This use of AI can enhance the quality of student submissions and provide valuable feedback that helps students learn and improve their skills over time. Importantly, the original content must still be generated by the students, maintaining the integrity of their work.

Allow for AI generation of materials but require human review

In this scenario, students can use generative AI to produce complete materials, such as essays or reports, which then undergo human review. Educators play a critical role in assessing the AI-generated content, providing feedback, and ensuring that the material meets academic standards. This approach acknowledges the potential of AI to assist in content creation while reinforcing the importance of human oversight and judgment in the educational process. Practically, this level of use would most likely align with assignments high on Bloom’s Taxonomy that require students to evaluate or synthesize a range of generated products and then explain their thought processes.

Allow for AI tools without a requirement for human review

At the most permissive end of the spectrum, some institutions might allow the unrestricted use of AI tools without requiring subsequent human review. It is unclear what the educational goals might be to merit this stance, but it is the logical opposite end of a continuum that starts with a total ban. It would raise significant concerns about the authenticity of student work and the potential for over-reliance on technology.

The expansion of generative AI tools within the educational environment illustrates the diverse ways in which these tools can be integrated into learning environments. From complete bans to unrestricted use, each approach has potential. As educators and institutions navigate this evolving landscape, it is crucial to consider the implications of each policy on student learning, assessments, academic integrity, and the future of education. Balancing innovation with ethical considerations will be key to harnessing the full potential of generative AI in education in a way that enhances educational outcomes while preserving the core values of academic excellence.

Steven M. Baule, Ed.D., Ph.D.
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