Sin and Muthu (2015) conducted a systematic literature review with a focus on educational data mining and learning analytics, and its implications for higher education.
This paper studies the application of data mining technology based on Weka in student management. As an open data mining platform, Weka collects a large number of machine learning algorithms that can undertake the task of data mining, including data preprocessing, classification, regression, clustering, association rules and …
In the field of science and technology information management, broadening the application of Web data mining technology, such as web data mining technology and university library integration, can optimize the resource construction. With limited funds, we can give full play to the carrier advantages and expand document storage.
Data mining is the process of extracting knowledge or insights from large amounts of data using various statistical and computational techniques. The data can be structured, semi-structured or unstructured, and can be stored in various forms such as databases, data warehouses, and data lakes. The primary goal of data mining is to …
Future research may improve its utility in educational data science by developing tools for counting pattern occurrences as well as identifying and removing unreliable patterns. Future work needs to establish a systematic guideline for data preprocessing, parameter setting, and interpreting sequential patterns.
To drive the "mind" demand for data mining technology, the "mind" type of "big data + psychology education" will be combined to create "mind" platform for the study of mental health combined with the "mind" of the school. The system identifies the "mind" benefits of current activity and seeks to achieve the goal of ...
Educational Data Mining involves applying data mining and statistical techniques to information from educational institutions to help analyze student performance. It identifies patterns in large datasets that can help predict student choices, assess their knowledge over time, and help administrators and teachers improve the educational …
Growing popularity in DM and the system of education is transforming educational data mining into a modern, rising research culture.
This Special Issue focuses on applying data mining algorithms and big data analytics within educational settings. While generally neglected in the field, the application of big data includes the application by end users, …
In the process of data mining, the emphasis is on the mining of low level concepts. That is, all the indexes can be excavated together, and each module can be excavated separately. Then, it extends to its corresponding high-level concept mining, looking for the law between financial indicators.
This paper briefly introduces the concept of data mining and personalized teaching, and studies the application of data mining technology in the personalized teaching of Internet education platform, in order to improve the school's teaching management level and students' academic performance.
This study is a systematic literature review (SLR) of the application of neural networks for educational data mining in higher education, from the perspective of modeling, learning tasks/algorithms, and cost function optimization. The ultimate goal of EDM is to use information obtained for decision making that enhances student retention, …
Educational data mining (EDM) is the application of data mining in the educational field. EDM is used to classify, analyze, and predict the students' academic performance, and students' dropout rate, as well as instructors'performance in order to improve teaching–learning process.
This article provides a comprehensive guide on the applications of Data Mining. It also provides information on its benefits and importance.
Applying data mining (DM) in education is an emerging interdisciplinary research field also known as educational data mining (EDM). It is concerned with developing methods for exploring the unique types of …
The purpose of this article mainly discusses the public welfare sports education in the artificial intelligence era. The article discusses the research background and significance, development of education data mining, and decision tree technology and enumerates the application of education data mining in real life.
This prediction problem is a kernel task toward personalized education and has attracted increasing attention in the field of artificial intelligence and educational data mining (EDM). This paper provides a systematic review of the SPP study from the perspective of machine learning and data mining.
Distance education has changed the traditional teaching mode, allowing students to study without leaving home. However, compared with traditional online teaching, there are some problems such as large amount of data and difficulty in information processing in the distance education system. Data mining is a new technology that quickly discovers …
Data mining is a process used by companies to turn raw data into useful information. By using software to look for patterns in large batches of data, businesses can learn more about their ...
The technology acceptance model (TAM) was used as a theoretical framework for the operational definition of the variables. Through the use of data mining techniques (clustering and decision trees), …
What is data mining? 7 key data mining applications and examples in: business, telecommunications, banking sector, e-commerce, finance, medicine, security.
Figure 1 illustrates a qualitative shift in the degree to which education research is hosting data-intensive studies inspired by methodological innovations from computer science and statistics. We refer to the research leading this shift as "educational data science" (EDS). This topic captures several interrelated areas of growth. Consider …
Semantic Scholar extracted view of "Research trend in Earth Science education: based on an application of data mining, Latent Dirichlet Allocation" by Minho Kwak et al.
In recent years, two communities have grown around a joint interest on how big data can be exploited to benefit education and the science of learning: Educational Data Mining and Learning Analytics. This article discusses the relationship between these two communities, and the key methods and approaches of educational data mining. …
Student marks and grade prediction from their historic academic data is a popular and useful application in educational data mining, so it is becoming a valuable source of information which can be used in different manners to improve the education quality in the country.
This study looks into the recent applications of Big Data technologies in education and presents a review of literature available on Educational Data Mining and Learning Analytics. The usage of learning management systems in education has been increasing in the last few years. Students have started using mobile phones, primarily …
Applying data mining (DM) in education is an emerging interdisciplinary research field also known as educational data mining (EDM). It is concerned with developing methods for exploring the unique types of data that come from educational environments. Its goal is to better understand how students learn and identify the …
The technology acceptance model (TAM) was used as a theoretical framework for the operational definition of the variables. Through the use of data mining techniques (clustering and decision trees), groupings were made based on the b-learning adoption stage and a subsequent predictive model of these stages.
The application of big data mining technology in the field of education has provided a new development path for education, realized the informatization of education and promoted the better development of education. To enhance the usage of big data mining technology as well as help to improve the current education system, this paper …
What is data mining? Data mining, also known as knowledge discovery in data (KDD), is a branch of data science that brings together computer software, machine learning (i.e., the process of teaching machines how to learn from data without human intervention), and statistics to extract or mine useful information from massive data sets.
Data mining has applications in numerous industries, including manufacturing, education, health care, technology, media, banking, and more. In addition to serving several industries, data mining is a regular task you will perform in a career in data science and business analytics.
The paper also discusses potential applications of data mining in higher education. The benefits of data mining are its ability to gain deeper understanding of the patterns previously unseen using current available reporting capacities.
Researchers have started paying attention to the application of data mining and data analytics to handle big data generated in the educational sector.
