Updated: Apr 28
Dr. Wei Cui & Francisco Nieto
There’s a big future for Artificial Intelligence (AI) in K12 education but it is still developing. During the past couple years, the push has been to develop AI for high school students to better prepare them for university studies. Education is a very competitive arena. Parents want students to enter a good college. But studies show that 80% of homework is useless. The focus needs to be on improving weaknesses in the student’s knowledge and skills.
The strength of AI education systems is in image and pattern recognition. AI education systems put emphasis on prerequisite learning topics that may represent weaknesses. AI can recommend content and learning paths to reduce weaknesses.
Dr. Wei is involved in the development and deployment of the first Intelligent Adaptive Learning System in China designed to improve learning outcomes. The challenge centers around developing an algorithm to recommend adaptive or personalized learning.
AI education systems put emphasis on prerequisite learning topics that may represent weaknesses. Diagnostic assessments report areas where students have weaknesses as well as proficiencies. They are very effective at diagnosing the knowledge state of a learner.
AI models can quickly adjust content to optimize the learning path. This involves presenting the most suitable content and difficulty level to the student at the appropriate time. This differs from traditional classroom learning where every student is expected to progress through the same material at the same pace. Traditional classrooms present learning in a linear fashion for all students. AI customizes the learning sequence.
One drawback of AI models is that they can be biased depending upon who builds the model. For example, an app that looks at faces to determine the likelihood of that individual serving time in prison might be biased against minorities. This fault must be avoided.
Effective video presentations should be produced by very experienced teachers, so learning content is more effectively communicated to students. The performance of AI education systems is based on improvements in learning effectiveness compared with traditional methods of teaching. Better interaction and engagement of the student produces better performance. For instance, short videos are more engaging and help students keep their focus on learning. 1 to 3 minutes for elementary level, 3 to 5 minutes for secondary level, and 5 to 7 minutes for high school level are most appropriate.
A challenge for the future is to have a smoother interaction with the machine. This requires a move away from multiple choice questions to open ended questions here it seems more like the student is having a conversation with the AI system. It also means performing a better analysis of wrong answers.
Just adding an AI system in the classroom doesn’t automatically translate into enhanced learning; the teacher has to be able to effectively utilize the system. The future will see human teachers and AI education systems coexisting within the classroom. AI provides a better assessment the learning status of the student. AI can help standardize education and relieve teachers to create more meaningful experiences for their students. The human can give warmth and understanding to students that the machine is incapable of giving. Routine processes can be performed by AI systems, leaving the teacher to focus on more meaningful human social issues.
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Dr. Wei Cui
is the Chief Scientist at Squirrel AI Learning, the leading AI+ education innovator at the forefront of K12 AI revolution. Dr. Cui led the development of the first intelligent adaptive learning system-Squirrel AI in China which has been proved to be more efficient at teaching than human-teacher with 20-years teaching experience during a series of human-vs-AI competitions hosted by Squirrel AI Learning.
is Curriculum Manager, Code Net at Google. He has over 19 years of experience hacking the education space and currently working with Code Next as Curriculum Manager. Francisco is a maker, web and mobile developer, STEM equity champion, curriculum designer, teacherpreneur, computer science teacher and advocate. Francisco has experience designing and launching new products, programs and schools.
is an award-winning Digital Citizenship and international STEAM/robotics educator with a demonstrated history of working in the education technology management industry. Skilled in Curriculum Development, Project Management, Social-Emotional Learning, 21st Century Skills,
Design Thinking, Education Technology, and Project-based Learning. Global Instructional Coach and Speaker with a Master focused in Education (M.Ed.) from the University of Hawaii at Manoa.