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Online education is combined by internet technology and traditional education. It grows rapidly recently. Big data has the characteristics of massiveness, diversification, low value and rapidity, which is deeply influencing and reconstructing the online education. The study on the educational technology matching big data analysis, and the exploration of the development trend and law of online education...
Learning analytics (LA) leverages learner-related data to generate reliable and factual information for the purpose of enhancing decision making in higher education, workplace and schools. Therefore, we have envisioned the need for a learning analytics system for a consortium of Nigerian universities that could serve as a tool for academic advising. The system should be able to offer advice at several...
In this paper, we design a five-sided educational data mining framework (5S-EDMF) to analyze college students' diligence and effectiveness of study, and to recommend learning resource accordingly. We noticed data collected from students' E-learning activities to reveal a lot about the attitudes and behaviors of students online as well as offline. This provides us an additional valuable tool to access...
Data with high volume, velocity, variety and veracity brings the new experience curve of analytics. Big data in higher education comes from different sources that include blogs, social networks, student information systems, learning management systems, research, and other machine-generated data. Once the data is analysed it promises better student placement processes; more accurate enrolment forecasts,...
Through the continuous collection and in-depth analysis of the quality monitoring data of colleges and universities, we combine the efficiency processing of big data and data evaluation, monitor the status of higher education normally, and construct a higher education quality monitoring and evaluation platform based on Spark. This platform is teaching centered with schools as its basis, including...
Data mining technology is the key technology and core content of big data age. The undergraduate data mining course introduces the basic concepts, basic principles and application techniques of data mining, as well as the characteristics and new technologies of data mining under the background of big data. According to the characteristics of undergraduate students, the curriculum should weaken the...
With the rapid development of big data technology and the rapid growth of big data industry market, big data talent demand is also a substantial increase in China. In order to cultivate more talented people satisfying the needs of the community, we have designed the big data course for undergraduates. The big data course stresses not only on many theories but also lots of practice. The project of...
The inclusion of information and communication technologies in Healthcare and Medical Education is a fact nowadays. Furthermore numerous virtual learning environments have been established in order to host both educational material and learners online activities. Online modules in a VLE can be designed in very different ways being part of different types of courses, while different models can be used...
Learning Analytics (LA) has become a prominent paradigm in the context of education lately which adopts the recent advancements of technology such as cloud computing, big data processing, and Internet of Things. LA also requires an intensive amount of processing resources to generate relevant analytical results. However, the traditional approaches have been inefficient at tackling LA challenges such...
In the paper the problems of modeling and investigating the behavior of complex socio-economic systems are considered. Authors are deeply concerned about decision-making support issues in the case of evaluation for such complex socio-economic systems. To solve these problems, the totality of the development goals of the object and the priorities of these goals are determined, then the indicators are...
Online education interaction is an important part in online education research. The emergence and development of cloud computing and large data technology provide new opportunities for online education interaction research, and have great influence on its service mode and data processing. Based on the characteristics of cloud computing and large data, this paper discusses the problems faced by online...
Inferring latent user preferences using both structured and unstructured data is an important social computing task. In this paper, we propose a user preference representation based on user activities embedded in unstructured data to better encode the homophily theory. The representation of an individual user is learned using a embedding based method to integrate latent user preferences in social...
In this paper, we aimed to guide about latest development and studies about students' performance analysis and Learning Analytics in Massively Open Online Courses (MOOCs) for researchers related with the topics. For this purpose short review for usage of performance prediction and Learning Analytics in MOOCs is investigated In our study, to help readers get familiar with our topic, firstly literature...
MOOC develops quite well and provides a new learning platform, which becomes a prominent representative of big data due to its massive behavior data accumulated in the process of using vast teaching resources. Big data analytics technology based on MOOC is a new research trend and its frame can be involved in four stages: where to get big data (Where), what are data types of MOOC (What), how to deal...
Education helps people develop as individuals. It not only helps build social skills but also enhances the problem solving and decision making skills of individuals. With the growing number of schools, colleges and universities around the globe, education now has taken new dimension. The main focus of higher Educational Institutes is to improve the overall quality and effectiveness of education. Predicting...
We develop a practical technique in this paper to classify the scholars in different disciplines, organizations according to their research interests. The scholar classification is important to the scholars, research organizations,, government for research, evaluation, education, research resource allocation. It becomes really difficult because name abbreviation, interdisciplinary, especially tautonym...
A good scholar evaluation system is very important for students to select advisors and majors and for government to get a good policy of the educational resource. The factor of scholars should be the most important parameter in the various college rankings, however, it seems not appear in the college ranking since it is difficult to evaluate it. In this paper, we propose a new evaluation system for...
Educational Data Mining and Learning Analytics are two growing fields of study, trying to make sense of education data and to improve teaching and learning experience. We study dropout prediction in Massively Open Online Courses (MOOCS), where the goal is given student's learning behavior log data in one month, to predict whether students would drop out in next ten days. We collect 39 courses data...
The ideological and political education is facing new and greater challenges in the large data environment. In the current environment, the full use of information technology to carry out ideological and political education work, is the effective strategy to adapt to the big data environment. This paper mainly introduces the new situation of College Students' Ideological and political education, and...
The purpose of this paper is to explore whether the use of big data has the potential for application in the Higher Education (HE) sector in Oman in addressing part of their current challenges. Higher Education institutions in Oman are facing challenges relate to enhancing the learning experience, improving educator effectiveness, providing appropriate and effective learning methods tailored to individual...
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