Is AI and Machine Learning a "Watershed" Moment in Edtech?

 

Artificial intelligence (AI) and machine learning (ML) are rapidly becoming integral parts of the global economy, creating a high demand for professionals with the skills and knowledge to work in these fields. There are just not enough skilled workers in these fields. Many students are not adequately prepared to enter these fields due to a lack of relevant education and training. In order to ensure that students are well-equipped to succeed in the AI and ML industries, teachers must adjust their teaching methods to better align with the skills and knowledge required for these fields. 

First, teachers should place a greater emphasis on math and computer science. These subjects are essential for understanding the underlying principles and algorithms of AI and ML. Students should be exposed to a wide range of mathematical concepts, including calculus, linear algebra, and statistics. They should also have a strong foundation in computer science, including programming languages such as Python, as well as data structures and algorithms. 

Second, teachers should incorporate hands-on, project-based learning into their curriculum. This approach allows students to apply the concepts they have learned to real-world problems, which is essential for developing practical skills in AI and ML. For example, students could work on projects that involve building and training their own machine learning models, or using AI to solve a specific problem in a particular industry. 

Third, teachers should encourage students to engage in self-directed learning and experimentation. The field of AI and ML is constantly evolving, and it is important for students to have the ability to learn and adapt as new technologies and techniques become available. Teachers can facilitate this by providing students with resources and support for pursuing their own interests in AI and ML, such as online tutorials and open-source software.

 

Fourth, teachers should ensure that students are exposed to a diverse range of applications of AI and ML. While the technology is often associated with cutting-edge research in the tech industry, it has a wide range of applications across many different sectors, such as healthcare, finance, and transportation. By exposing students to these different applications, teachers can help them understand the potential of AI and ML and how it could impact different industries, and help them to find where they would like to fit in. 

Finally, teachers should encourage students to think critically about the ethical and societal implications of AI and ML. As these technologies continue to advance, it is important for students to understand the potential risks and benefits, as well as the ethical considerations involved in their development and use. Teachers can facilitate this by incorporating discussions and debates on these topics into their curriculum, and encouraging students to think critically about the impact of AI and ML on society. 

At the very least, artificial intelligence and machine learning may be a “watershed’ moment in educational technology, which causes teachers to be introspective. Every teacher should think about what students should be learning in a world where AI and ML exist.