A taxonomy for the use of AI in education

Key points:

Non-use of generative ai tools by students
Partial ban on generative ai tools by students
No feedback or decisions on students' use of generative ai
Allow initial prototyping, wireframes and idea generation.
Enable ai generation of materials that then require human review
Enable ai tools without the need for human review

As generative ai continues to advance, its potential applications in education become increasingly varied and complex. Educators and institutions are struggling to find the best way 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. It outlines a range of practical options, from restrictive to fully permissive approaches. These could be implemented at an institutional level, but instructors should be given the opportunity to determine the level of use of generative ai tools at the course or even assignment level.

For example, for my courses on educational technology topics, I allow students almost full use of generative ai tools with the caveat that they need to document the tools they used and why they selected them. In other courses, I restrict the use of generative ai tools to particular uses for specific tasks. The range of options goes from a complete ban on the use of generative ai tools to allowing students to fully use any available tools.

No use of generative ai tools by students

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

Partial ban on generative ai tools by students

In this case, the use of generative ai tools is restricted in specific contexts or for certain tasks. For example, ai could be prohibited during exams or in tasks where personal creativity and original thinking 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 also choose to ban specific tools. This approach seeks to achieve a balance between taking advantage of technological advances and maintaining academic standards.

No feedback or decisions on students' use of generative ai

Some educational institutions may adopt a stance of neutrality and choose not to comment or make formal decisions about the use of generative ai. This passive approach leaves the decision in the hands of individual faculty or departments, which can lead to varying practices within the same institution. While this flexibility can be advantageous, it can also create inconsistencies in how ai tools are used and evaluated across different courses, which could cause confusion for students.

Allow initial prototyping, wireframes and idea generation.

In this category, students can use generative ai tools for the initial stages of their work, such as brainstorming, prototyping, 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 further developing their concepts, ensuring that the end result is a product of their own intellectual efforts.

Allow editing and review of student-generated materials.

Another approach allows students to use ai tools to edit and review their work. In this case, ai acts as an intelligent assistant that helps students improve the grammar, structure, and coherence of their writing. This use of ai can improve the quality of students' work and provide valuable feedback that helps them learn and improve their skills over time. Importantly, original content must continue to be generated by students, maintaining the integrity of their work.

Allows ai generation of materials, but requires human review

In this scenario, students can use generative ai to produce complete materials, such as essays or reports, which are then subjected to human review. Educators play a critical role in evaluating ai-generated content, providing feedback, and ensuring that material meets academic standards. This approach recognizes the potential of ai to assist in content creation while reinforcing the importance of human oversight and judgment in the educational process. In practice, this level of use would likely align with high-level tasks in Bloom's Taxonomy that require students to evaluate or synthesize a variety of generated products and then explain their thought processes.

Enabling ai tools without human review

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

The expansion of generative ai tools within the educational setting illustrates the diverse ways these tools can be integrated into learning environments. From outright 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 realizing the full potential of generative ai in education in a way that improves educational outcomes while preserving the core values ​​of academic excellence.

Dr. Steve Baule is a faculty member at Winona State University (WSU), where he teaches in the Department of Leadership Education. Before joining WSU, Baule spent 28 years in K-12 school systems in Illinois, Indiana and Iowa, and two years teaching in the University of Wisconsin system. For 13 years before moving to the university level, Baule served as superintendent of public schools. He has written ten books on a variety of educational and historical topics and has served on the editorial boards of two magazines. Baule earned an advanced diversity and equity certificate while in the University of Washington system. He holds a doctorate in educational technology from Northern Illinois University and a doctorate in educational leadership and policy studies from Loyola University Chicago.

Baule’s academic interests focus on online student engagement, educational technology, particularly the impact of 1:1 implementations, social-emotional learning, and the history of education. Baule led several efforts to improve student emotional health and reduce discipline problems before moving into higher education. She also writes on aspects of early American history.

Baule has been a member of the American Association of School Administrators, the American Library Association, the American Association of School Librarians, the Association for Supervision and Curriculum Development, the Consortium for the School Network, the International Association of School Librarians, the National Association of Secondary School Principals, the National Staff Development Council, and many of their state affiliates. He has served as a consultant in the areas of educational technology, facilities design, library program development, team building, and communications.

Latest publications by Steven M. Baule, Ed.D., Ph.D. (see everything)