Strategies for Integrating AI into Teacher Training Courses

In late 2022, access to AI-based platforms like ChatGPT and others became widely available, marking a significant shift in the educational landscape. However, this rapid advancement poses a challenge for teacher educators who may not have been trained on AI and its use in the classroom.

As pre-service teachers graduate and enter K-12 education, it is crucial that they are intentionally prepared to tackle the use of AI in the classroom. If they have not been exposed to AI in their teacher education program or have not seen its use in classrooms, it may be challenging for them to effectively integrate AI into their teaching practices.

To address this issue, it is recommended that teacher education programs develop coursework focused on AI methods as part of the curriculum for pre-service teachers. This coursework should be grounded in a respected inclusive framework like Universal Design for Learning, helping pre-service teachers focus on specific learning opportunities and outcomes.

Navigating AI biases in the classroom is another important aspect for pre-service teachers to learn. Teacher education programs should also include in the training an understanding of the potential harms of AI and ways to address them in teaching. Exposing pre-service teachers to diverse scholars like Dr. Joy Buolamwini, founder of the Algorithmic Justice League, can support their critical consumption of AI content.

Teacher educators have the responsibility, duty, and challenge to prepare pre-service teachers for the use of AI in education. Addressing AI in teacher education should be a priority. Teacher educators should also be prepared to help pre-service teachers recognize the potential harms of AI and learn strategies to mitigate them.

It is unrealistic to expect teacher education programs to provide pre-service teachers with a robust computer science education in AI. Instead, it is suggested that pre-service teachers should at a minimum be exposed to foundational knowledge around AI. Demonstrating prompt engineering and its potential outcomes to pre-service teachers can help them understand the impact of AI in education.

The aim is to equip teacher educators with the knowledge, skills, and dispositions needed to support pre-service teachers' AI foundational knowledge development and use of AI within teaching and learning spaces. To achieve this, teacher education programs should provide faculty with training and professional development (PD) on AI technologies to enhance their AI literacy.

Several institutions in Germany have integrated training and continuing education on artificial intelligence (AI) into teacher education. For example, the Saxon school portal offers self-learning modules, regional media education centers provide support on AI in schools, the University of Giessen conducts advanced workshops on AI in higher education teaching, and the Fraunhofer IFF in Magdeburg hosts expert meetings on AI integration in vocational teacher training and higher education.

In addition, companies like Google and Adobe offer free basic AI literacy courses for educators. These resources can provide valuable opportunities for teacher educators and pre-service teachers to learn new tricks in the context of AI integration in education.

In conclusion, the integration of AI in education is a complex and evolving field. Teacher education programs play a crucial role in preparing pre-service teachers for this new landscape. By developing AI-focused coursework, providing faculty with PD on AI technologies, and exposing pre-service teachers to diverse scholars and resources, teacher education programs can help ensure that the next generation of educators is equipped to navigate the challenges and opportunities presented by AI in the classroom.