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Articles 1 - 6 of 6
Full-Text Articles in Social and Behavioral Sciences
Evolutionary Learner Profile Optimization Using Rare And Negative Association Rules For Micro Open Learning, Geng Sun, Jiayin Lin, Jun Shen, Tingru Cui, Dongming Xu, Huaming Chen
Evolutionary Learner Profile Optimization Using Rare And Negative Association Rules For Micro Open Learning, Geng Sun, Jiayin Lin, Jun Shen, Tingru Cui, Dongming Xu, Huaming Chen
Faculty of Engineering and Information Sciences - Papers: Part B
The actual data availability, readiness and publicity has slowed down the research of making use of computational intelligence to improve the knowledge delivery in an emerging learning mode, namely adaptive micro open learning, which naturally has high demand in quality and quantity of data to be fed. In this study, we contribute a novel approach to tackle the current scarcity of both data and rules in micro open learning, by adopting evolutionary algorithm to produce association rules with both rare and negative associations taken into account. These rules further drive the generation and optimization of learner profiles through refinement and …
Managing Open Innovation: An Exploration Of Information Technologies And Open Search Patterns, Tingru Cui, Na Liu
Managing Open Innovation: An Exploration Of Information Technologies And Open Search Patterns, Tingru Cui, Na Liu
Faculty of Engineering and Information Sciences - Papers: Part B
No abstract provided.
Towards Massive Data And Sparse Data In Adaptive Micro Open Educational Resource Recommendation: A Study On Semantic Knowledge Base Construction And Cold Start Problem, Geng Sun, Tingru Cui, Ghassan Beydoun, Shiping Chen, Fang Dong, Dongming Xu, Jun Shen
Towards Massive Data And Sparse Data In Adaptive Micro Open Educational Resource Recommendation: A Study On Semantic Knowledge Base Construction And Cold Start Problem, Geng Sun, Tingru Cui, Ghassan Beydoun, Shiping Chen, Fang Dong, Dongming Xu, Jun Shen
Faculty of Engineering and Information Sciences - Papers: Part B
Micro Learning through open educational resources (OERs) is becoming increasingly popular. However, adaptive micro learning support remains inadequate by current OER platforms. To address this, our smart system, Micro Learning as a Service (MLaaS), aims to deliver personalized OER with micro learning to satisfy their real-time needs.
Assisting Open Education Resource Providers And Instructors To Deal With Cold Start Problem In Adaptive Micro Learning: A Service Oriented Solution, Geng Sun, Tingru Cui, Dongming Xu, Huaming Chen, Shiping Chen, Jun Shen
Assisting Open Education Resource Providers And Instructors To Deal With Cold Start Problem In Adaptive Micro Learning: A Service Oriented Solution, Geng Sun, Tingru Cui, Dongming Xu, Huaming Chen, Shiping Chen, Jun Shen
Faculty of Engineering and Information Sciences - Papers: Part B
No abstract provided.
A Framework Of Mlaas For Facilitating Adaptive Micro Learning Through Open Education Resources In Mobile Environment, Geng Sun, Tingru Cui, Wanwu Guo, Shiping Chen, Jun Shen
A Framework Of Mlaas For Facilitating Adaptive Micro Learning Through Open Education Resources In Mobile Environment, Geng Sun, Tingru Cui, Wanwu Guo, Shiping Chen, Jun Shen
Faculty of Engineering and Information Sciences - Papers: Part B
No abstract provided.
Organizing Online Computation For Adaptive Micro Open Education Resource Recommendation, Geng Sun, Tingru Cui, Ghassan Beydoun, Shiping Chen, Dongming Xu, Jun Shen
Organizing Online Computation For Adaptive Micro Open Education Resource Recommendation, Geng Sun, Tingru Cui, Ghassan Beydoun, Shiping Chen, Dongming Xu, Jun Shen
Faculty of Engineering and Information Sciences - Papers: Part B
Our previous work, Micro Learning as a Service (MLaaS), aimed to deliver adaptive micro open education resources (OERs). However, relying solely on the offline computation, the recommendation lacks rationality and timeliness. It is also difficult to make the first recommendation to a new learner. In this paper we introduce the organization of the online computation of the MLaaS. It targets at solving the cold start problem due to the shortage of learner information and real-time updates of the learner-micro OER profile