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 proficiencyStreamline recruiting and reduce unconscious biasCreate a digital “paper trail” for audit purposesOrganize and optimize learning materials, and continually update them based on student and instructor feedbackCreate optical systems that can automatically grade students’ work with a cell phone pictureMove toward AI-powered voice recognition systems that can help detect reading issuesMake scheduling algorithms that can help determine optimal learning times for students and subjectsConstruct grading systems that quickly aggregate assessment data and decrease response time to student needsCreate 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.
Author Recent PostsCasey Thompson, Digital Media Manager, SkywardCasey Thompson advocates for ethical digital experience and security as the digital media manager for Skyward. His expertise covers digital media marketing, while his passion lies in user experience, web design, and digital artwork. When not in the digital realm, Casey ventures into nature in pursuit of adventure. Latest posts by eSchool Media Contributors (see all)
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