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Download full textKudzayi Savious Tarisayi; Ronald Manhibi – Journal of Learning and Teaching in Digital Age, 2025
This paper critically examines the transformative potential of Artificial Intelligence (AI) in Zimbabwe's higher education system, focusing on how AI can enhance learning outcomes and optimize administrative processes. The study employs a qualitative research approach, gathering insights from key stakeholders in the educational sector to identify…
Descriptors: Foreign Countries, Artificial Intelligence, Technology Uses in Education, Higher Education
Warnes, Zachary; Smirnov, Evgueni – International Educational Data Mining Society, 2020
Selecting courses in an open-curriculum education program is a difficult task for students and academic advisors. Course recommendation systems nowadays can be used to reduce the complexity of this task. To control the recommendation error, we argue that course recommendations need to be provided together with "statistical" confidence.…
Descriptors: Course Selection (Students), Automation, Validity, Prediction
Direct linkPolak, Julia; Cook, Dianne – Journal of Statistics and Data Science Education, 2021
Kaggle is a data modeling competition service, where participants compete to build a model with lower predictive error than other participants. Several years ago they released a simplified service that is ideal for instructors to run competitions in a classroom setting. This article describes the results of an experiment to determine if…
Descriptors: Artificial Intelligence, Data Analysis, Models, Competition
Mu, Tong; Jetten, Andrea; Brunskill, Emma – International Educational Data Mining Society, 2020
In some computerized educational systems, there is evidence of students "wheel-spinning," where a student tries and repeatedly fails at an educational task for learning a skill. This may be particularly concerning in low resource settings. Prior research has focused on predicting and modeling wheel-spinning, but there has been little…
Descriptors: Computer Uses in Education, Artificial Intelligence, Academic Failure, Automation
Konstantinos Pouliakas – Cedefop - European Centre for the Development of Vocational Training, 2021
The world of work is being impacted by a fourth industrial revolution, transformed by artificial intelligence and other emerging technologies. With forecasts suggesting large shares of workers, displaced by automation, in need of upskilling/reskilling, the design of active skills policies is necessary. Conventional methods used to anticipate…
Descriptors: Job Skills, Information Technology, Artificial Intelligence, Employment Qualifications
Pouliakas, Konstantinos, Ed. – Cedefop - European Centre for the Development of Vocational Training, 2021
The world of work is being impacted by a fourth industrial revolution, transformed by artificial intelligence and other emerging technologies. With forecasts suggesting large shares of workers, displaced by automation, in need of upskilling/reskilling, the design of active skills policies is necessary. Conventional methods used to anticipate…
Descriptors: Job Skills, Information Technology, Artificial Intelligence, Employment Qualifications
Konstantinos Pouliakas – Cedefop - European Centre for the Development of Vocational Training, 2021
The world of work is being impacted by a fourth industrial revolution, transformed by artificial intelligence and other emerging technologies. With forecasts suggesting large shares of workers, displaced by automation, in need of upskilling/reskilling, the design of active skills policies is necessary. Conventional methods used to anticipate…
Descriptors: Job Skills, Information Technology, Artificial Intelligence, Employment Qualifications
Ng, Kelvin H. R.; Hartman, Kevin; Liu, Kai; Khong, Andy W. H. – International Educational Data Mining Society, 2016
During the semester break, 36 second-grade students accessed a set of resources and completed a series of online math activities focused on the application of the model method for arithmetic in two contexts 1) addition/subtraction and 2) multiplication/division. The learning environment first modeled and then supported the use of a scripted series…
Descriptors: Word Problems (Mathematics), Mathematics Instruction, Arithmetic, Problem Solving
Bekele, Rahel; McPherson, Maggie – British Journal of Educational Technology, 2011
This research work presents a Bayesian Performance Prediction Model that was created in order to determine the strength of personality traits in predicting the level of mathematics performance of high school students in Addis Ababa. It is an automated tool that can be used to collect information from students for the purpose of effective group…
Descriptors: Foreign Countries, Personality Traits, Mathematics Education, Prediction
Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020
The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…
Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing
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
Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction
Bonk, Sharon C. – 1981
Based on interviews and correspondence conducted during 1981, this report describes British library and book trade plans for expansion of their internal order processing systems to include the eventual exchange of data through the use of telecommunications. Comparisons are made between the situation in England and the United States. The report…
Descriptors: Bookstores, Check Lists, Cooperative Planning, Foreign Countries
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
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries
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