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Direct linkTafesse, Wondwesen – International Journal of Educational Technology in Higher Education, 2022
With the widespread adoption of social networking sites among college students, discerning the relationship between social networking sites use and college students' academic performance has become a major research endeavor. However, much of the available research in this area rely on student self-reports and findings are notably inconsistent.…
Descriptors: Social Networks, College Students, Computer Software, Academic Achievement
Download full textChinsook, Kittipong; Khajonmote, Withamon; Klintawon, Sununta; Sakulthai, Chaiyan; Leamsakul, Wicha; Jantakoon, Thada – Higher Education Studies, 2022
Big data is an important part of innovation that has recently attracted a lot of interest from academics and practitioners alike. Given the importance of the education industry, there is a growing trend to investigate the role of big data in this field. Much research has been undertaken to date in order to better understand the use of big data in…
Descriptors: Student Behavior, Learning Analytics, Computer Software, Rating Scales
Zualkernan, Imran – International Association for Development of the Information Society, 2021
A significant amount of research has gone into predicting student performance and many studies have been conducted to predict why students drop out. A variety of data including digital footprints, socio-economic data, financial data, and psychological aspects have been used to predict student performance at the test, course, or program level.…
Descriptors: Prediction, Engineering Education, Academic Achievement, Dropouts
Panagiotis Panagiotidis – European Journal of Education (EJED), 2022
New technological developments, such as 5G networks, smart and interconnected devices, and the development of the Internet of Things (IoT), lead to a new reality in which the secure flow of data is non-negotiable. In this new reality, blockchain technology can play a crucial role, as it has the ability to provide the necessary background for the…
Descriptors: Second Language Learning, Second Language Instruction, Telecommunications, Handheld Devices
Qazdar, Aimad; Er-Raha, Brahim; Cherkaoui, Chihab; Mammass, Driss – Education and Information Technologies, 2019
The use of machine learning with educational data mining (EDM) to predict learner performance has always been an important research area. Predicting academic results is one of the solutions that aims to monitor the progress of students and anticipates students at risk of failing the academic pathways. In this paper, we present a framework for…
Descriptors: Data Analysis, Academic Achievement, At Risk Students, High School Students
Henry, Philip – College and University, 2019
Phillip Henry is a semi-retired former U.K. Registrar and Secretary with almost 40 years' experience in higher education. He has been active in staff development in the United Kingdom (Association of University Administrators, Academic Registrars Council, and Association of Heads of University Administration), in the United States (AACRAO and a…
Descriptors: Academic Achievement, Administrator Attitudes, Educational Experience, College Students
Shneyderman, Aleksandr – Office of Assessment, Research, and Data Analysis, Miami-Dade County Public Schools, 2015
Imagine Learning is a computer-based instructional program used with English Language Learners (ELLs) in the District. It is designed to provide instruction specifically to ELLs. During the 2014-2015 school year, the Imagine Learning (IL) program was implemented across the District, mostly for students at the initial level of participation in the…
Descriptors: Program Evaluation, English Language Learners, Comparative Analysis, English (Second Language)
Alabama Department of Education, 2011
This guide is a training and supportive tool for use by local education agencies (LEAs) in the state of Alabama that are utilizing the Science, Technology and Innovation (STI) Information-INow-INFocus information system software. The Graduation Tracking System (GTS) utilizes existing STI technology to capture student information pertaining to…
Descriptors: Guides, Computer Software, Information Management, Student Records
Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
North Carolina State Dept. of Public Instruction, Raleigh. Div. of Vocational Education Services. – 1993
This guide focuses on use of the North Carolina Vocational Competency Achievement Tracking System (VoCATS)-designated software in the instructional management process. (VoCATS is a competency-based, computer-based instructional management system that allows the collection of data on student performance achievement prior to, during, and following…
Descriptors: Academic Achievement, Competence, Competency Based Education, Computer Managed Instruction
