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AI for higher education, why - Coggle Diagram
AI for higher education
Features
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and More, Someday perhaps
Biometrics are used by some school systems as a way of automating payments, library borrowing and access to IT services.
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Decision Management
Enabling critical decision making about the student journey (drop-out, non- completion, program switching, remediation requirements), providing instant supports “just in time”
Deep Learning Platforms
Generate learning pathways and resources to support specific learner needs, once the engine has mastered the learning outcomes expected of learners.
Text Analytics
Analysis of errors in objective assessments and for the assessment of essays and complex answers to questions
Receive resources such as tutoring or advising based on their previous and predicted academic performance.
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Self-reflection support (learning analytics, meta- cognitive dashboards)
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The top business drivers for education leaders to adopt AI include better student engagement, higher funding, and accelerated innovation.(Microsoft-2019 :)
AI will be able to assess students, provide feedback and generate and test scientific hypotheses at least as well as humans can.(THE-Microsoft survey on AI)
Real cases
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California State University, AI speech technology
Students suffering from Zoom call fatigue can use Otter for Education to turn spoken lectures into lecture notes
University of Michigan, Adaptive Courseware
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The global AI in education market will reach $25.7 billion in 2030 (AI in Education Market Research Report)
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There is no doubt that AI will revolutionize the delivery and management of education and learning, And while we believe that teachers will not be replaced by machines by 2030, we still need a dynamic review of how AI will transform teachers’ roles.(UNESCO, April, 2019)
Market drivers
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Growing numbers of adaptive learning programs, games
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