NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Laws, Policies, & Programs
Assessments and Surveys
Massachusetts Comprehensive…1
What Works Clearinghouse Rating
Showing 1 to 15 of 17 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Elena Drugova; Irina Zhuravleva; Ulyana Zakharova; Adel Latipov – Journal of Computer Assisted Learning, 2024
Background: Driven by the ongoing need to provide high-quality learning and teaching, universities recently have shown an increased interest in using learning analytics (LA) for improving learning design (LD). However, the evidence of such improvements is scarce, and the maturity of such research is unclear. Objectives: This study is aimed to…
Descriptors: Learning Analytics, Instructional Design, Higher Education, Instructional Improvement
Peer reviewed Peer reviewed
Direct linkDirect link
Umer, Rahila; Susnjak, Teo; Mathrani, Anuradha; Suriadi, Lim – Interactive Learning Environments, 2023
Predictive models on students' academic performance can be built by using historical data for modelling students' learning behaviour. Such models can be employed in educational settings to determine how new students will perform and in predicting whether these students should be classed as at-risk of failing a course. Stakeholders can use…
Descriptors: Prediction, Student Behavior, Models, Academic Achievement
Peer reviewed Peer reviewed
Direct linkDirect link
Pillutla, Venkata Sai; Tawfik, Andrew A.; Giabbanelli, Philippe J. – Technology, Knowledge and Learning, 2020
In massive open online courses (MOOCs), learners can interact with each other using discussion boards. Automatically inferring the states or needs of learners from their posts is of interest to instructors, who are faced with a high attrition in MOOCs. Machine learning has previously been successfully used to identify states such as confusion or…
Descriptors: Learning Processes, Online Courses, Data Collection, Data Analysis
Peer reviewed Peer reviewed
PDF on ERIC Download full text
McFarland, Daniel A.; Khanna, Saurabh; Domingue, Benjamin W.; Pardos, Zachary A. – AERA Open, 2021
This AERA Open special topic concerns the large emerging research area of education data science (EDS). In a narrow sense, EDS applies statistics and computational techniques to educational phenomena and questions. In a broader sense, it is an umbrella for a fleet of new computational techniques being used to identify new forms of data, measures,…
Descriptors: Learning Analytics, Statistics, Computation, Measurement
Peer reviewed Peer reviewed
Direct linkDirect link
Charitopoulos, Angelos; Rangoussi, Maria; Koulouriotis, Dimitrios – International Journal of Artificial Intelligence in Education, 2020
The aim of this paper is to survey recent research publications that use Soft Computing methods to answer education-related problems based on the analysis of educational data 'mined' mainly from interactive/e-learning systems. Such systems are known to generate and store large volumes of data that can be exploited to assess the learner, the system…
Descriptors: Data Collection, Learning Analytics, Educational Research, Artificial Intelligence
Peer reviewed Peer reviewed
Direct linkDirect link
Renz, André; Hilbig, Romy – International Journal of Educational Technology in Higher Education, 2020
The ongoing datafication of our social reality has resulted in the emergence of new data-based business models. This development is also reflected in the education market. An increasing number of educational technology (EdTech) companies are entering the traditional education market with data-based teaching and learning solutions, and they are…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Data Collection
Peer reviewed Peer reviewed
Direct linkDirect link
Knox, Jeremy; Williamson, Ben; Bayne, Sian – Learning, Media and Technology, 2020
This paper examines visions of 'learning' across humans and machines in a near-future of intensive data analytics. Building upon the concept of 'learnification', practices of 'learning' in emerging big data-driven environments are discussed in two significant ways: the "training" of machines, and the "nudging" of human…
Descriptors: Data Collection, Data Analysis, Artificial Intelligence, Man Machine Systems
Peer reviewed Peer reviewed
Direct linkDirect link
Cho, Eunsoon; Cho, Young Hoan; Grant, Michael M.; Song, Donggil; Huh, Yeol – TechTrends: Linking Research and Practice to Improve Learning, 2020
The Korean Society for Educational Technology (KSET) hosted its second panel discussion partnering with the Association for Educational Communications and Technology (AECT) at the 2019 AECT Convention in Las Vegas, Nevada. A total of four panelists, two from Korea and two from the U.S., participated in the discussion on the trends of educational…
Descriptors: Foreign Countries, Educational Technology, Technology Uses in Education, Telecommunications
Peer reviewed Peer reviewed
Direct linkDirect link
Singer, Judith D. – Journal of Research on Educational Effectiveness, 2019
The arc of quantitative educational research should not be etched in stone but should adapt and change over time. In this article, I argue that it is time for a reshaping by offering my personal view of the past, present and future of our field. Educational research--and research in the social and life sciences--is at a crossroads. There are many…
Descriptors: Educational Research, Research Methodology, Longitudinal Studies, Evaluation
Luckin, Rosemary, Ed. – UCL IOE Press, 2018
The educational technology sector is growing fast, with schools, colleges and universities more than ever looking for the best ways to use technology in the classroom. At the same time, there is an increasing appetite for learning and teaching practices to be backed up by evidence. However, there are few resources that bring these two things…
Descriptors: Teaching Methods, Educational Technology, Technology Uses in Education, Educational Research
Peer reviewed Peer reviewed
Direct linkDirect link
Dillenbourg, Pierre – International Journal of Artificial Intelligence in Education, 2016
How does AI&EdAIED today compare to 25 years ago? This paper addresses this evolution by identifying six trends. The trends are ongoing and will influence learning technologies going forward. First, the physicality of interactions and the physical space of the learner became genuine components of digital education. The frontier between the…
Descriptors: Artificial Intelligence, Educational Trends, Trend Analysis, Educational Technology
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Worsley, Marcelo; Blikstein, Paulo – Journal of Learning Analytics, 2014
Learning analytics and educational data mining are introducing a number of new techniques and frameworks for studying learning. The scalability and complexity of these novel techniques has afforded new ways for enacting education research and has helped scholars gain new insights into human cognition and learning. Nonetheless, there remain some…
Descriptors: Data Analysis, Data Collection, Engineering, Design
Peer reviewed Peer reviewed
PDF on ERIC Download full text
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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
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
Previous Page | Next Page »
Pages: 1  |  2