Data mining of computer game assisted e/m-learning systems in higher education

Juric, Petar; Matetić, Maja; Brkić, Marija

doi:10.1109/mipro.2014.6859665

Cited by 6 publications

(3 citation statements)

References 17 publications

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“…By clustering the k sample data points in the space as the center, the information of big data which is closest to different samples is finally classified [11][12][13][14].…”

Section: Cluster Analysis Algorithmmentioning

confidence: 99%

Construction of English Intelligent Translation Software Framework Based on Data Analysis Algorithm

Zhou¹

2022

Mobile Information Systems

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In the era of “Internet + education,” the information technology and learning methods of college students have become inseparable. The rapid development of intelligent translation software can provide convenience for English-Chinese translation and computer English learning and simultaneously improve the quality and efficiency of professional English learning. Under such background, the English teaching of software majors is chosen as the breakthrough to analyze the measures of applying intelligent translation software during the teaching process. Therefore, a data mining algorithm including cluster analysis and BP neural network model is designed. Then, the cluster analysis algorithm is used to classify the data in different forms, which can improve the data utilization efficiency. In addition, K-means algorithm based on feature selection is improved to achieve better performance. In the comparison of translation speed and matching rate, our method is much better than other software.

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“…By clustering the k sample data points in the space as the center, the information of big data which is closest to different samples is finally classified [11][12][13][14].…”

Section: Cluster Analysis Algorithmmentioning

confidence: 99%

Construction of English Intelligent Translation Software Framework Based on Data Analysis Algorithm

Zhou¹

2022

Mobile Information Systems

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“…The Association Mining techniques help us to identify the relationship between the student's interest for a project work, the faculty interest and the applicability of the project work [29]. Moreover, open source software such as Moodle, e/m learning and learning through play models can be used to collect and analyze data [30]. Mathematical models can also predict student retention rate and their academic performance [31].…”

Section: Related Studymentioning

confidence: 99%

The Role of Global Educational Database in Educational Data Mining

Banerjee

2018

EJENG

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Educational Data Mining is one of the major on-going research platforms now. Students’ records need to be maintained and analyzed in a manner so that they can be utilized to predict students’ behavior and learning methods. Although students’ academic records need to be processed and analyzed through data mining tools, the primary challenge is to gather individual academic student details. This paper proposes a global database of students irrespective of geographical boundaries. Academic performance of every student from every country will be updated in this platform. Students’ performance on major examinations will be available in the database. Supporting documents and performance details will be readily available and accessible to the evaluators from any geographic location. This will be helpful to standardize the evaluation process and analyze the performance of a student, irrespective of geographic boundaries. The following paper will discuss the available EDM tools and how data can be analyzed to extract information.

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“…The Association Mining techniques help us to identify the relationship between the student's interest for a project work, the faculty interest and the applicability of the project work [11]. Moreover, open source software such as Moodle, e/m learning and learning through play models can be used to collect and analyze data [12]. Mathematical models can also predict student retention rate and their academic performance.…”

Section: Related Studymentioning

confidence: 99%