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http://hdl.handle.net/1942/28822
Title: | Integration of Data Mining Clustering Approach in the Personalized E-Learning System | Authors: | Kausar, Samina Xu Huahu HUSSAIN, Iftikhar Zhu Wenhao Zahid, Misha |
Issue Date: | 2018 | Publisher: | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | Source: | IEEE ACCESS, 6, p. 72724-72734 | Abstract: | Educational data-mining is an evolving discipline that focuses on the improvement of self-learning and adaptive methods. It is used for finding hidden patterns or intrinsic structures of educational data. In the arena of education, the heterogeneous data is involving and continuously growing in the paradigm of big-data. To extract meaningful information adaptively from big educational data, some specific data mining techniques are needed. This paper presents a clustering approach to partition students into different groups or clusters based on their learning behavior. Furthermore, the personalized e-learning system architecture is presented, which detects and responds to teaching contents according to the students' learning capabilities. The primary objective includes the discovery of optimal settings, in which the learners can improve their learning capabilities. Moreover, the administration can find essential hidden patterns to bring the effective reforms in the existing system. The clustering methods K-Means, K-Medoids, Density-based Spatial Clustering of Applications with Noise, Agglomerative Hierarchical Cluster Tree and Clustering by Fast Search and Finding of Density Peaks via Heat Diffusion (CFSEDP-HD) are analyzed using educational data mining. It has been observed that more robust results can be achieved by the replacement of existing methods with CFSEDP-HD. The data mining techniques are equally effective in analyzing the big data to make education systems vigorous. | Notes: | [Kausar, Samina; Xu Huahu; Zhu Wenhao] Shanghai Univ, Sch Comp Engn & Sci, Shanghai 200444, Peoples R China. [Kausar, Samina] Univ Kotli Azad Jammu & Kashmir, Dept CS&IT, Kotli Azad Kashmir 11100, Pakistan. [Hussain, Iftikhar] Hasselt Univ, Inst Voor Mobiliteit IMOB, B-3500 Hasselt, Belgium. [Hussain, Iftikhar; Zahid, Misha] Beaconhouse Natl Univ, Sch Comp & IT, Terogil Campus, Lahore 53700, Pakistan. | Keywords: | Big data; clustering; data-mining; educational data-mining; e-learning; profile learning;Big data; clustering; data-mining; educational data-mining; e-learning; profile learning | Document URI: | http://hdl.handle.net/1942/28822 | ISSN: | 2169-3536 | e-ISSN: | 2169-3536 | DOI: | 10.1109/ACCESS.2018.2882240 | ISI #: | 000454058200001 | Rights: | 2018 IEEE | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2020 |
Appears in Collections: | Research publications |
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