The revolution in artificial intelligence (AI) and machine learning (ML) has been a long time coming. Since the mid-1980s, scholarly journals have been predicting the widespread adoption of AI in education. However, momentum is accelerating.
Just four years ago, a study predicted that AI in education and learning would increase 47.5% through 2021; as it turned out, the prediction was conservative.
The current landscape
AI and ML are being used at every step of the student and educator journey to:
- Build statistical models of student knowledge, evaluating student achievement and instructor proficiency
- Streamline recruiting and reduce unconscious bias
- Create a digital “paper trail” for audit purposes
- Organize and optimize learning materials, and continually update them based on student and instructor feedback
- Create optical systems that can automatically grade students’ work with a cell phone picture
- Move toward AI-powered voice recognition systems that can help detect reading issues
- Make scheduling algorithms that can help determine optimal learning times for students and subjects
- Construct grading systems that quickly aggregate assessment data and decrease response time to student needs
- Create rule-based tutoring systems that “learn” from student errors and teacher corrections
That’s all in addition to broader-scale, district-wide assessment and application.
Are the machines taking over?
To many, that sounds like technology successfully educating and preparing kids; to others, it may sound like the machines are taking over.
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