Strategies for teaching teachers on AI

The demand for skills in AI increases rapidly in many industries, but nowhere faster than in teaching, according to some experts, because educators must lay the foundations for professional knowledge for all other sector. During the ISTELIVE 25 conference in San Antonio last week, a panel of teachers and consultants said that professional development (PD) for teachers should include knowledge of the content, technology and pedagogy of AI, as well as specific examples of implementation and familiarity with related research.

Moderate the discussion, Nancye Blair Black, CEO of the Education Consulting Consulting The Block Uncarved, said that it was part of the ISTE AI program in education that has collected ideas on this subject in various universities. The group realized that what teacher training programs most needed to prioritize the priority in three categories that overlap aligned themselves on the TPACK framework (knowledge of technological educational content), an educational model popularized in the 2000s: knowledge of content, such as literacy and learning AI on AI; technical knowledge, including mastery of AI and knowing how to use tools; And educational knowledge, which includes the teacher's responsibilities and how to adjust the teaching practices accordingly.

Stacy George, assistant professor of the University of Hawaii in Manoa, described the ideal approach of AI in teacher training as “a prudent defender with a moral compass”.

Content knowledge

Amy Eguchi, an associate teacher professor at the University of California in San Diego, said that teachers must learn how AI works – and not just generating AI -, which means that their training must include IT elements.

To do this, Eguchi recommended AI4K12.orgWho describes a handful of large ideas in AI, and stressed that the literacy of AI for primary and secondary educators involves teaching them to get involved, to create, manage and design AI.

Technological knowledge

With regard to technological knowledge, Black stressed the importance of ensuring that teachers in terms of preservation and during service are competent not only with their own personal uses of AI, but in particular with the tools that they are likely to use in class. And this probably means different lessons for teachers at different levels. “You may be elementary, and your students use an I-READY or KHAN academy, and AI does this personalized learning and adaptive evaluation. Then (teachers) must understand how this tool works and how to use it safely, ethical and deeply, “she said. “Likewise, they may need strategies to effectively and effectively examine transcription of students' conversations with chatbots. Many people, especially in the middle and high level, now bring AI tutors to enter, but it is the teacher's burden, the play responsible for AI, to review these conversations to ensure that the content is correct. We must teach this competence. “

Black has added that most teachers will have to know how to use a teaching machine, a web tool to create automatic learning models and may need new key skills such as fast engineering or problems.

Educational knowledge

George said that teachers update their educational approach to integrate AI will start with professional development. She cited research showing that teachers often take the educational models they have experienced in PD in their own classrooms.

“There are research that supports this adage that we teach how we have been taught, but AI has only recently filtered into our educational systems, and it transforms our society,” she said. “Our preservation teachers will become leaders in this class.

George said it could take some reframing, illustrating how new and improved practices can involve new ethical considerations, such as data confidentiality and new potential risks, such as cognitive decline.

Infuse AI skills in teacher preparation

Black then went to seven critical strategies developed by ISTE AI in the education preparation program to guide teacher training on AI:

• Promote a fundamental universal understanding of AI.
• Teach them skills to effectively exploit AI tools for teaching.
• For AI literacy education, use national executives such as the five major IA ideas.
• Ask them to test and explore AI tools so as to develop and apply their knowledge.
• Infuse AI literacy in existing programs.
• Include Critical examinations of AI tools in class K-12 experiences and teachers' preparation.
• Intends intentionally what precedes in the preparation of teachers.

Offering examples of the way she does this, the assistant professor of the University of Longwood, Alecia Blackwood, said that she was starting first -year students at the basic university of literacy and ethics of the basic AI, proceeds juniors on AI in disciplinary literacy and ethics, and finally teaches Seniors for educational design, creation ethical guidelines and the use of specific tools and to build AI cats.

For the integration of the course program, Sue Kasun, member of the Education Faculty of the Georgia State University, recommended the Gai2n Genai integration browserA set of 28 -page directives to decide if, when and how to integrate Genai into a course.

Camille Dempsey, professor of education technology at the Pennsylvania Western University, stressed the importance of the institutional movement and to build a culture of preparation for AI. She said it happens thanks to individual interactions and not to be afraid of difficult conversations.

“I find myself telling a lot of stories, which, I think, is another excellent strategy-not pushing people to that, but perhaps inviting them to see what types of things we all do,” she said. “I also thought it was quite important to involve our students, so we started a program of AI Ambassadors … and I took all those who applied. There were 36 students – undergraduate and doctoral student, we had the whole range. These students now … are the use of the calendar for this fall, and there will be what they will learn at the next one, to teach some of professional development.

Excessive and cognitive decline

At the end, Black cited recent MIT search showing that an excessive exception of AI, especially in young people, can negatively affect memory and cognition.

“We have to somehow fight this, and we need teachers to have their minds,” she said. “There are also research that says that say:” But when AI is in fact a partner of thought which gives comments and provokes a reflection, learning increases. “It is therefore really important that we teach these tools in a way that is really beneficial for students.”