AI Thinking for Cloud Education Platform with Personalized Learning Rad, Paul Roopaei, Mehdi Beebe, Nicole Shadaram, Mehdi Au, Yoris 2017-12-28T00:30:51Z 2017-12-28T00:30:51Z 2018-01-03
dc.description.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.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2018.003
dc.identifier.isbn 978-0-9981331-1-9
dc.language.iso eng
dc.relation.ispartof Proceedings of the 51st Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.subject Best and Next Practices in Online Education: Opportunities and Challenges
dc.subject Artificial Intelligence Machine learning AI Thinking Cloud Education Deep Learning
dc.title AI Thinking for Cloud Education Platform with Personalized Learning
dc.type Conference Paper
dc.type.dcmi Text
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