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Guiyun Feng; Honghui Chen – Education and Information Technologies, 2025
Data mining has been successfully and widely utilized in educational information systems, and an important research field has been formed, which is educational data mining. Process mining inherits the characteristics of data mining which can not only use historical data in the system to analyze learning behavior and predict academic performance,…
Descriptors: Educational Research, Artificial Intelligence, Data Use, Algorithms
Sghir, Nabila; Adadi, Amina; Lahmer, Mohammed – Education and Information Technologies, 2023
The last few years have witnessed an upsurge in the number of studies using Machine and Deep learning models to predict vital academic outcomes based on different kinds and sources of student-related data, with the goal of improving the learning process from all perspectives. This has led to the emergence of predictive modelling as a core practice…
Descriptors: Prediction, Learning Analytics, Artificial Intelligence, Data Collection
Nesrine Mansouri; Mourad Abed; Makram Soui – Education and Information Technologies, 2024
Selecting undergraduate majors or specializations is a crucial decision for students since it considerably impacts their educational and career paths. Moreover, their decisions should match their academic background, interests, and goals to pursue their passions and discover various career paths with motivation. However, such a decision remains…
Descriptors: Undergraduate Students, Decision Making, Majors (Students), Specialization
Luiz Rodrigues; Filipe Dwan Pereira; Marcelo Marinho; Valmir Macario; Ig Ibert Bittencourt; Seiji Isotani; Diego Dermeval; Rafael Mello – Education and Information Technologies, 2024
Intelligent Tutoring Systems (ITS) have been widely used to enhance math learning, wherein teacher's involvement is prominent to achieve their full potential. Usually, ITSs depend on direct interaction between the students and a computer. Recently, researchers started exploring handwritten input (e.g., from paper sheets) aiming to provide…
Descriptors: Intelligent Tutoring Systems, Handwriting, Equal Education, Access to Education
Korchi, Adil; Dardor, Mohamed; Mabrouk, El Houssine – Education and Information Technologies, 2020
Learning techniques have proven their capacity to treat large amount of data. Most statistical learning approaches use specific size learning sets and create static models. Withal, in certain some situations such as incremental or active learning the learning process can work with only a smal amount of data. In this case, the search for algorithms…
Descriptors: Learning Analytics, Data, Computation, Mathematics
Csapó, Gábor; Csernoch, Mária; Abari, Kálmán – Education and Information Technologies, 2020
In the modern, information driven society managing and handling data is unavoidable. The most common form of data handling is to organize data into tables and complete operations on them in spreadsheets. Sprego (Spreadsheet Lego) is a programming-oriented methodology focusing on schemata construction and authentic problem-solving working with only…
Descriptors: Instructional Effectiveness, Spreadsheets, Data Processing, Computer Software
Feldman-Maggor, Yael; Barhoom, Sagiv; Blonder, Ron; Tuvi-Arad, Inbal – Education and Information Technologies, 2021
Research based on educational data mining conducted at academic institutions is often limited by the institutional policy with regard to the type of learning management system and the detail level of its activity reports. Often, researchers deal with only raw data. Such data normally contain numerous fictitious user activities that can create a…
Descriptors: Data Analysis, Educational Research, Data Processing, Learning Analytics
Zhang, Wei; Zeng, Xinyao; Wang, Jihan; Ming, Daoyang; Li, Panpan – Education and Information Technologies, 2022
Programming skills (PS) are indispensable abilities in the information age, but the current research on PS cultivation mainly focuses on the teaching methods and lacks the analysis of program features to explore the differences in learners' PS and guide programming learning. Therefore, the purpose of this study aims to explore horizontal…
Descriptors: Programming, Skill Development, Information Retrieval, Data Processing
Gang Zhao; Hui He; Bingbing Di; Qingqing Guo – Education and Information Technologies, 2024
With the rapid development of information technology, various online education platforms support the sharing of digital educational resources. Because digital educational resources are simple to duplicate and disseminate quickly, there exists copyright infringement, which threatens the interests of copyright owners. In addition, the existing…
Descriptors: Educational Resources, Technology Uses in Education, Technological Advancement, Copyrights
Gupta, Shivangi; Sabitha, A. Sai – Education and Information Technologies, 2019
Aimed at a massive outreach and open access education, Massive Open Online Courses (MOOC) has evolved incredibly engaging millions of learners' over the years. These courses provide an opportunity for learning analytics with respect to the diversity in learning activity. Inspite of its growth, high dropout rate of the learners', it is examined to…
Descriptors: Retention (Psychology), Online Courses, Learner Engagement, Electronic Learning
Singh, Archana – Education and Information Technologies, 2017
The youth power to speak their mind, recommendations and opinions about various issues on social media cannot be ignored. There is a generated by students on social media websites like, facebook, Orkut, twitter etc. This paper focusses on the extraction of knowledge from the data floated by the University students on social websites in different…
Descriptors: Social Media, College Students, Data Processing, Web Sites
Sabitha, A. Sai; Mehrotra, Deepti; Bansal, Abhay – Education and Information Technologies, 2017
Currently the challenges in e-Learning are converging the learning content from various sources and managing them within e-learning practices. Data mining learning algorithms can be used and the contents can be converged based on the Metadata of the objects. Ensemble methods use multiple learning algorithms and it can be used to converge the…
Descriptors: Electronic Learning, Metadata, Computer System Design, Design Preferences