A Systematic Review of Educational Data Mining

Xu, FangYao; Liu, Zhiqiang; Yue, JiaQi; Qu, Shaojie

doi:10.1007/978-3-030-80126-7_54

Cited by 4 publications

(2 citation statements)

References 80 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With the popularity and rapid development of information technologies, most schools are continuing to increase the construction of hardware and software information equipment and invest in the construction of digital service platforms to collect, store, and apply a large amount of data related to the overall educational process [24]. In general, the data collected, stored, and used in the educational process can be divided into four main categories [25,26]:…”

Section: Educational Informationmentioning

confidence: 99%

Sustained Improvement of Educational Information Asymmetry: Intentions to Use School Social Media

Huang

Chueh

2023

Sustainability

View full text Add to dashboard Cite

Under the impact of digitization, many schools in Taiwan have started to actively operate social media. Using social media to release important school information can reduce the educational information asymmetry between schools and students. Educational information asymmetry may cause problems of adverse selection and moral hazard, and damage the rights and interests of students. The main purpose of this study is to explore the intentions of high school students to use school social media as a channel to obtain important information about their schools. A questionnaire survey was administered to the students of a high school in Taoyuan City, Taiwan, and the collected data were statistically analyzed. The research results of this study show that perceived usefulness, subjective norm, and trust had positively significant effects on the intention to use school social media; however, perceived ease-of-use, and perceived behavioral control did not have significant effects on the intention to use school social media. Through the operation of social media, schools can not only eliminate the adverse selection and moral hazard caused by information asymmetry but also improve their brand images and reduce their marketing costs.

show abstract

Section: Educational Informationmentioning

confidence: 99%

Sustained Improvement of Educational Information Asymmetry: Intentions to Use School Social Media

Huang

Chueh

2023

Sustainability

View full text Add to dashboard Cite

show abstract

“…Machine learning and data mining techniques were applied to hybrid clustering and prediction outcomes for finding the problem in the education system. It helps researchers to improve the educational process and learning outcomes of students (Xu et al, 2021). Ensemble learning techniques have been used to enhance the predicting model of them (Badal & Sungkur, 2022;Karalar et al, 2021;Nachouki & Abou Naaj, 2022;Smirani et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Predictive Model for Clustering Learning Outcomes Affected by COVID-19 Using Ensemble Learning Techniques

Nuankaew¹,

Nuankaew²

2023

INT J EDUC METHODOL

View full text Add to dashboard Cite

<p style="text-align: justify;">The influence of COVID-19 has caused a sudden change in learning patterns. Therefore, this research studied the learning achievement modified by online learning patterns affected by COVID-19 at Rajabhat Maha Sarakham University. This research has three objectives. The first objective is to study the cluster of learning outcomes affected by COVID-19 at Rajabhat Maha Sarakham University. The second objective is to develop a predictive model using machine learning and data mining technique for clustering learning outcomes affected by COVID-19. The third objective is to evaluate the predictive model for clustering learning outcomes affected by COVID-19 at Rajabhat Maha Sarakham University. Data collection comprised 139 students from two courses selected by purposive sampling from the Faculty of Information Technology at the Rajabhat Maha Sarakham University during the academic year 2020-2021. Research tools include student educational information, machine learning model development, and data mining-based model performance testing. The research findings revealed the strengths of using educational data mining techniques for developing student relationships, which can effectively manage quality teaching and learning in online patterns. The model developed in the research has a high level of accuracy. Accordingly, the application of machine learning technology obviously supports and promotes learner quality development.</p>

show abstract

Improving Learning Outcomes through Predictive Analytics: Enhancing Teaching and Learning with Educational Data Mining

Alam

2023

2023 7th International Conference on Intelligent Computing and Control Systems (ICICCS)

View full text Add to dashboard Cite

A Systematic Review of Educational Data Mining

Cited by 4 publications

References 80 publications

Sustained Improvement of Educational Information Asymmetry: Intentions to Use School Social Media

Sustained Improvement of Educational Information Asymmetry: Intentions to Use School Social Media

Predictive Model for Clustering Learning Outcomes Affected by COVID-19 Using Ensemble Learning Techniques

Improving Learning Outcomes through Predictive Analytics: Enhancing Teaching and Learning with Educational Data Mining

Contact Info

Product

Resources

About