Using learning analytics to scale the provision of personalised feedback

By Abelardo Pardo, Jelena Jovanovic, Shane Dawson, Dragan Gasevic, Negin Mirriahi. British Journal of Educational Technology, 2019

350 citations recorded by the source corpus.

Subfields: Computer Science Applications, Education, Media Technology

View Paper: https://www.semanticscholar.org/paper/1d462617e323383ada6df0e20ed37cb51b2d4d4c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Science Applications

1. D. Carless
2. Dragan Gasevic

In Education

1. N. Winstone
2. D. Carless
3. Dragan Gasevic
4. Wannisa Matcha
5. Nora'ayu Ahmad Uzir
6. Abelardo Pardo
7. David Boud
8. Phillip Dawson

In Media Technology

1. D. Carless
2. Abelardo Pardo
3. Dragan Gasevic

Citations in the corpus

• A Systematic Review of Empirical Studies on Learning Analytics Dashboards: A Self-Regulated Learning Perspective (2020, background): “Recent studies suggest that strong positive effects on learning outcomes and satisfaction with feedback can be achieved if analytics-based feedback is provided in form of weekly emails [88].”
• Promises and challenges of generative artificial intelligence for human learning (2024, neutral): “Another promise of GenAI in supporting human learning is its potential to provide timely, specific and constructive feedback—a key element of high­quality instruction that is essential for effective learning 34–36 .”
• Teacher feedback literacy and its interplay with student feedback literacy (2020, positive): “The information based on these digital traces can be used to provide timely feedback at scale and facilitate student uptake of feedback (Pardo et al. 2017).”