NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Patterson, Chris R.; York, Emily; Maxham, Danielle; Molina, Rudy; Mabrey, Paul, III – Journal of Learning Analytics, 2023
The anticipation, inclusion, responsiveness, and reflexivity (AIRR) framework (Stilgoe et al., 2013) is a novel framework that has helped those in science and technology fields shift their focus from products to the processes used to create those products. However, the framework has not been known to be applied to the development and…
Descriptors: Learning Analytics, Innovation, School Holding Power, At Risk Students
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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Herodotou, Christothea; Naydenova, Galina; Boroowa, Avi; Gilmour, Alison; Rienties, Bart – Journal of Learning Analytics, 2020
Despite the potential of Predictive Learning Analytics (PLAs) to identify students at risk of failing their studies, research demonstrating effective application of PLAs to higher education is relatively limited. The aims of this study are: (1) to identify whether and how PLAs can inform the design of motivational interventions; and (2) to capture…
Descriptors: Learning Analytics, Predictive Measurement, Student Motivation, Intervention
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Herodotou, Christothea; Rienties, Bart; Verdin, Barry; Boroowa, Avinash – Journal of Learning Analytics, 2019
Predictive Learning Analytics (PLA) aim to improve learning by identifying students at risk of failing their studies. Yet, little is known about how best to integrate and scaffold PLA initiatives into higher education institutions. Towards this end, it becomes essential to capture and analyze the perceptions of relevant educational stakeholders…
Descriptors: Prediction, Data Analysis, Higher Education, Distance Education