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Caspari-Sadeghi, Sima – Journal of Educational Technology Systems, 2023
Intelligent assessment, the core of any AI-based educational technology, is defined as embedded, stealth and ubiquitous assessment which uses intelligent techniques to diagnose the current cognitive level, monitor dynamic progress, predict success and update students' profiling continuously. It also uses various technologies, such as learning…
Descriptors: Artificial Intelligence, Educational Technology, Computer Assisted Testing, Barriers
Bergner, Yoav; von Davier, Alina A. – Journal of Educational and Behavioral Statistics, 2019
This article reviews how National Assessment of Educational Progress (NAEP) has come to collect and analyze data about cognitive and behavioral processes (process data) in the transition to digital assessment technologies over the past two decades. An ordered five-level structure is proposed for describing the uses of process data. The levels in…
Descriptors: National Competency Tests, Data Collection, Data Analysis, Cognitive Processes
Fraillon, Julian, Ed.; Ainley, John, Ed.; Schulz, Wolfram, Ed.; Friedman, Tim, Ed.; Duckworth, Daniel, Ed. – International Association for the Evaluation of Educational Achievement, 2020
IEA's International Computer and Information Literacy Study (ICILS) 2018 investigated how well students are prepared for study, work, and life in a digital world. ICILS 2018 measured international differences in students' computer and information literacy (CIL): their ability to use computers to investigate, create, participate, and communicate at…
Descriptors: International Assessment, Computer Literacy, Information Literacy, Computer Assisted Testing
Valenza, Marco; Dreesen, Thomas; Kan, Sophia – UNICEF Office of Research - Innocenti, 2022
One tool that many families own, across the globe, is a basic mobile phone. The use of low-cost basic mobile phones for educational purposes in humanitarian settings is critical where access to connectivity and higher cost devices is limited. The portability of mobile phones, combined with their communication features, offers multiple uses to…
Descriptors: COVID-19, Pandemics, Telecommunications, Handheld Devices
Martin, Florence; Ndoye, Abdou – Journal of University Teaching and Learning Practice, 2016
Learning analytics can be used to enhance student engagement and performance in online courses. Using learning analytics, instructors can collect and analyze data about students and improve the design and delivery of instruction to make it more meaningful for them. In this paper, the authors review different categories of online assessments and…
Descriptors: Educational Research, Data Collection, Data Analysis, Academic Achievement
Gibson, David; de Freitas, Sara – Technology, Knowledge and Learning, 2016
This article summarizes the methods, observations, challenges and implications for exploratory analysis drawn from two learning analytics research projects. The cases include an analysis of a games-based virtual performance assessment and an analysis of data from 52,000 students over a 5-year period at a large Australian university. The complex…
Descriptors: Foreign Countries, Educational Research, Data Collection, Data Analysis
Casey, Kevin – Journal of Learning Analytics, 2017
Learning analytics offers insights into student behaviour and the potential to detect poor performers before they fail exams. If the activity is primarily online (for example computer programming), a wealth of low-level data can be made available that allows unprecedented accuracy in predicting which students will pass or fail. In this paper, we…
Descriptors: Keyboarding (Data Entry), Educational Research, Data Collection, Data Analysis
Fu, Jianbin; Zapata, Diego; Mavronikolas, Elia – ETS Research Report Series, 2014
Simulation or game-based assessments produce outcome data and process data. In this article, some statistical models that can potentially be used to analyze data from simulation or game-based assessments are introduced. Specifically, cognitive diagnostic models that can be used to estimate latent skills from outcome data so as to scale these…
Descriptors: Simulation, Evaluation Methods, Games, Data Collection
Levy, Yair; Ramim, Michelle M. – Interdisciplinary Journal of E-Learning and Learning Objects, 2012
Procrastination appears to be an inevitable part of daily life, especially for activities that are bounded by deadlines. It has implications for performance and is known to be linked to poor personal time management. Although research related to procrastination as a general behavior has been well established, studies assessing procrastination in…
Descriptors: Computer Assisted Testing, Time Management, Student Behavior, Data Collection
Means, Barbara; Anderson, Kea – Office of Educational Technology, US Department of Education, 2013
This report describes how big data and an evidence framework can align across five contexts of educational improvement. It explains that before working with big data, there is an important prerequisite: the proposed innovation should align with deeper learning objectives and should incorporate sound learning sciences principles. New curriculum…
Descriptors: Educational Technology, Technology Uses in Education, Educational Resources, Individualized Instruction
Ritter, Lois A., Ed.; Sue, Valerie M., Ed. – New Directions for Evaluation, 2007
The general steps in conducting an evaluation using an online survey are the same as in using other methods: planning, data collection, data analysis, reporting, and application. Even though the process of evaluation using Internet-based surveys begins in a familiar manner, the unique requirements of the online methodology become apparent almost…
Descriptors: Data Analysis, Internet, Surveys, Computer Assisted Testing
Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
Nunes, Miguel Baptista, Ed.; McPherson, Maggie, Ed. – International Association for Development of the Information Society, 2015
These proceedings contain the papers of the International Conference e-Learning 2015, which was organised by the International Association for Development of the Information and Society and is part of the Multi Conference on Computer Science and Information Systems (Las Palmas de Gran Canaria, Spain, July 21-24, 2015). The e-Learning 2015…
Descriptors: Conference Papers, Failure, Electronic Learning, Success
Lawrence, Arul A. S. – Online Submission, 2015
The XX IDEA annual conference has been focused and reflected on different ways and means of meeting various kinds of methodological challenges, new technologies and multi-media developments, newly emerging partnerships and collaboration between emerging sectors on one hand and between the institutions functioning with similar objectives and…
Descriptors: Foreign Countries, Open Education, Distance Education, Barriers
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