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AI Thinking for Cloud Education Platform with Personalized Learning

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Title:AI Thinking for Cloud Education Platform with Personalized Learning
Authors:Rad, Paul
Roopaei, Mehdi
Beebe, Nicole
Shadaram, Mehdi
Au, Yoris
Keywords:Best and Next Practices in Online Education: Opportunities and Challenges
Artificial Intelligence Machine learning AI Thinking Cloud Education Deep Learning
Date Issued:03 Jan 2018
Abstract:Artificial Intelligence (AI) thinking is a framework beyond procedural thinking and based on cognitive and adaptation to automatically learn deep and wide rules and semantics from experiments. This paper presents Cloud-eLab, an open and interactive cloud-based learning platform for AI Thinking, aiming to inspire i) Deep and Wide learning, ii) Cognitive and Adaptation learning concepts for education. It has been successfully used in various machine learning courses in practice, and has the expandability to support more AI modules. In this paper, we describe the block diagram of the proposed AI Thinking education platform, and provide two education application scenarios for unfolding Deep and Wide learning as well as Cognitive and Adaptation learning concepts. Cloud-eLab education platform will deliver personalized content for each student with flexibility to repeat the experiments at their own pace which allow the learner to be in control of the whole learning process.
Pages/Duration:10 pages
URI:http://hdl.handle.net/10125/49890
ISBN:978-0-9981331-1-9
DOI:10.24251/HICSS.2018.003
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Best and Next Practices in Online Education: Opportunities and Challenges


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