AI thinking for cloud education platform with personalized learning

Paul Rad, Mehdi Roopaei, Nicole Beebe, Mehdi Shadaram, Yoris A. Au

Research output: Contribution to book or proceedingConference articlepeer-review

26 Scopus citations

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.

Original languageEnglish
Title of host publicationProceedings of the 51st Annual Hawaii International Conference on System Sciences, HICSS 2018
EditorsTung X. Bui
PublisherIEEE Computer Society
Pages3-12
Number of pages10
ISBN (Electronic)9780998133119
StatePublished - 2018
Event51st Annual Hawaii International Conference on System Sciences, HICSS 2018 - Big Island, United States
Duration: Jan 2 2018Jan 6 2018

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
Volume2018-January
ISSN (Print)1530-1605

Conference

Conference51st Annual Hawaii International Conference on System Sciences, HICSS 2018
Country/TerritoryUnited States
CityBig Island
Period01/2/1801/6/18

Scopus Subject Areas

  • General Engineering

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