NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Policymakers1
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing all 10 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Arantes, Janine Aldous – Research in Education, 2022
In the last decade education has experienced a shift from privatization to commercialization. This paper argues that the commercialization of education has evolved more recently as a result of artificially intelligent corporate players, enabling forms of insights sales called 'Dark Advertising'. It unpacks how Dark Advertising are profiting from…
Descriptors: Educational Policy, Corporations, Commercialization, Foreign Countries
Peer reviewed Peer reviewed
Direct linkDirect link
Kamdjou, Herve D. Teguim – Open Education Studies, 2023
This article revisits the Mincer earnings function and presents comparable estimates of the average monetary returns associated with an additional year of education across different regions worldwide. In contrast to the traditional Ordinary Least Squares (OLS) method commonly employed in the literature, this study applied a cutting-edge approach…
Descriptors: Outcomes of Education, Artificial Intelligence, Human Capital, Regression (Statistics)
Peer reviewed Peer reviewed
Direct linkDirect link
Chelsea Wilkinson; Michelle Leanne Oppert; Mikaela Sian Owen – Australasian Journal of Educational Technology, 2024
ChatGPT, at the forefront of artificial intelligence advancement, has caused excitement and scepticism within academic spheres due to its potential to affect academic processes. Understanding attitudes towards ChatGPT could help manage expectations and concerns for ChatGPT in academia, predict behaviour and inform policy. This study aimed to…
Descriptors: College Faculty, Teacher Attitudes, Artificial Intelligence, Computer Software
Peer reviewed Peer reviewed
Direct linkDirect link
Polak, 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
Peer reviewed Peer reviewed
Direct linkDirect link
Arantes, Janine Aldous – Australian Educational Researcher, 2023
Recent negotiations of 'data' in schools place focus on student assessment and NAPLAN. However, with the rise in artificial intelligence (AI) underpinning educational technology, there is a need to shift focus towards the value of teachers' digital data. By doing so, the broader debate surrounding the implications of these technologies and rights…
Descriptors: Foreign Countries, Elementary Secondary Education, Electronic Learning, Artificial Intelligence
Peer reviewed Peer reviewed
Direct linkDirect link
Christopher Dann; Petrea Redmond; Melissa Fanshawe; Alice Brown; Seyum Getenet; Thanveer Shaik; Xiaohui Tao; Linda Galligan; Yan Li – Australasian Journal of Educational Technology, 2024
Making sense of student feedback and engagement is important for informing pedagogical decision-making and broader strategies related to student retention and success in higher education courses. Although learning analytics and other strategies are employed within courses to understand student engagement, the interpretation of data for larger data…
Descriptors: Artificial Intelligence, Learner Engagement, Feedback (Response), Decision Making
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Khosravi, Hassan; Shabaninejad, Shiva; Bakharia, Aneesha; Sadiq, Shazia; Indulska, Marta; Gasevic, Dragan – Journal of Learning Analytics, 2021
Learning analytics dashboards commonly visualize data about students with the aim of helping students and educators understand and make informed decisions about the learning process. To assist with making sense of complex and multidimensional data, many learning analytics systems and dashboards have relied strongly on AI algorithms based on…
Descriptors: Learning Analytics, Visual Aids, Artificial Intelligence, Information Retrieval
Chai, Kevin E. K.; Gibson, David – International Association for Development of the Information Society, 2015
Improving student retention is an important and challenging problem for universities. This paper reports on the development of a student attrition model for predicting which first year students are most at-risk of leaving at various points in time during their first semester of study. The objective of developing such a model is to assist…
Descriptors: Undergraduate Students, Student Attrition, Prediction, Models
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
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers