Everyone's on the AI bandwagon.
People often over-estimate the short term impact and under-estimate the long term impact of new disruptive technologies.
But AI is different, because you can just tell it what to do. We are already struggling to keep up, to use capabilities it already has.
Education is no exception. In the next 2 years, AI won't just enter education. It will revolutionize it entirely. Here's why!
Current State
AI is already extensively used by students and teachers to
- Prepare lesson plans and assessment exercises
- Create presentations and learning materials
- Summarize complex topics
- Assist with revision and reinforcement
- Answer assessment exercises
- Attempt to detect AI answers to assessment exercises
That's pretty much everything, and yet it's just the tip of the iceberg!
Personalized Learning at Scale
AI has the capability to maintain a complete knowledge of each student's progress, including:
- What has been learned
- What areas need practice
- Gaps in understanding
It can question and test the student to confirm learning achievements.
With this information, AI can:
- Identify knowledge gaps in real-time
- Customize content to address these gaps effectively
Adaptive Teaching Methods
AI can also observe and adapt to individual learning styles. By analyzing how each student interacts with the material, AI can:
- Determine the most effective learning approach for each student
- Customize the delivery of educational content to maximize outcomes
- Continuously refine its teaching methods based on student responses
Cross-Learner Optimization
As AI systems accumulate data from numerous students, they will:
- Identify patterns in learning behaviors
- Determine which teaching methods are most effective across different types of learners
- Continuously improve and optimize educational strategies
Biometric Feedback
Biometric data will provide deeper insights into the learning process:
- Eye movement tracking to gauge attention and engagement
- EEG (electroencephalogram) monitoring to assess cognitive load and understanding
- Analysis of physical responses to tailor the pace and difficulty of lessons
We don't need to tell AI how to interpret and apply this information. For example, some students might learn more effectively in a state of sleepiness or boredom. The AI will associate the related physiological data to the improved learning outcomes, without needing to understand that the data indicate a state of sleepiness or boredom. It may notice that students who start earlier are more sleepy, so it might request that the student starts classes earlier.
The Ethical Imperative
Given the potential for highly tailored and optimized learning experiences, it may soon be considered irresponsible for parents not to utilize AI in their children's education. The advantages offered by AI-driven personalized learning could create a significant educational gap between those who have access to these technologies and those who don't.
And Why AI is the Only Way
The final crucial factor driving the adoption of AI in education: the challenge of academic integrity.
Current efforts to limit student use of AI for completing homework and assignments have proven largely unsuccessful. As AI becomes more sophisticated, it will be increasingly difficult to distinguish between work done by students and work generated by AI. For example, students will tell the AI to base its work on samples of their past work, to make its responses more believable.
This reality presents two significant implications:
- Educational institutions will be forced to integrate AI into their teaching methods to stay ahead of potential misuse. If AI is not monitoring learning and assessments, then it will be used to subvert assessments.
- The traditional methods of assessing student understanding and awarding degrees will need to be fundamentally re-imagined. A movement from delivery by professors to delivery by processors will democratise and commoditise education.
If educational systems don't adapt, there's a risk that:
- The validity of degrees and other educational attainments could be called into question
- Employers may lose confidence in the skills and knowledge that these qualifications are meant to represent, and student's won't have appropriate skills for the positions that they are qualified for.
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