E-learning for carers

Solberg, Olga; Miller, Jeanette Ullmann; Heivang, Synne; Bjerke, Mads

doi:10.1186/1750-1172-5-s1-p13

Cited by 16 publications

(1 citation statement)

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“…The teachers take more effort than students, which had become unsuitable to today's curriculum in this traditional learning. The relationship between the teacher and the learner is more impressive and effective through the classifications and categories in Virtual Learning Environment [6,7,8]. The Figure 1 represents parameters and model to analyze students behavior.…”

Section: Introductionmentioning

confidence: 99%

Data Mining Approach towards Students Behavior Assessment Methods for Higher Studies

Gangele¹,

Soni²,

Patil³

2018

IJCA

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The quality education to the students is primary point of higher educational institutions. One of the method to achieve high quality education in higher education system is analysis of students behavior with reference to examination performance, mark sheets, abnormal values and other students activities. Data mining methods discovers knowledge from these records for analysis and prediction about students behavior. In this paper, data mining techniques such as association rules and classification are applied to analyze and present a behavior model of students. The students behavior assessment framework is proposed as model for analysis using data mining technique, the model presents the indication to the critical quantities that regulate the students behavior on learning method. The proposed framework can be applied to extract valuable data that shows all characteristic of student behavior by clustering and subdivision of the student behavior large data set.

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Section: Introductionmentioning

confidence: 99%