The integration of Artificial Intelligence (AI) in education is rapidly gaining momentum and has the potential to revolutionize the way teachers and educational professionals guide student learning. While the critical presence of teachers is undoubtedly irreplaceable, AI is set to bring about significant changes to the roles and responsibilities of educators, as well as to educational best practices. From providing personalized learning experiences to automating administrative tasks and grading, AI has the potential to greatly assist educators in their efforts to educate the next generation.
Social media has made access to the voices of differently able individuals readily available, and they are constantly discussing perspectives and events that affect their lives. Open discussions about current issues may help pre-service teachers gain confidence in having difficult conversations about and with the students they serve.
Data-based decision making (DBDM) is the process by which professionals collect, graph, and analyze observational data to inform instructional decisions. With some modifications, Google Workspace may be a practical alternative to support DBDM for special education professionals.
Student choice is an important aspect of Universal Design for Learning (UDL), which is often hard to provide when you are trying to find resources that relate to your course goals. If you want all your students to receive the same background information, how can you give choice?
Teacher educators can guide preservice teachers through the connection between learner variability and instructional design decisions. “Look at how different your profiles appear from one another- what could I do as your professor with this in mind?”