Rate My Professor Paula De Barba

De Barba's research focuses on self-regulated learning, achievement motivation, learning analytics, online learning, and the integration of educational technology in higher education and lifelong learning contexts. She examines how student motivation, participation, and self-regulation strategies predict performance in digital environments, including MOOCs, and explores the role of generative AI in co-regulated learning processes. Key publications include 'The role of students' motivation and participation in predicting performance in a MOOC' (2016, Journal of Computer Assisted Learning, 603 citations), 'Visualizing patterns of student engagement and performance in MOOCs' (2014, 344 citations), 'A tale of two MOOCs: How student motivation and participation predict learning outcomes in different MOOCs' (2018, 142 citations), 'Learning with generative artificial intelligence within a network of co-regulation' (2023, Journal of University Teaching and Learning Practice, 103 citations), and 'Development and validation of a learning analytics rubric for self-regulated learning' (2025, Educational Technology Research and Development). With 33 research outputs and over 2,738 citations on Google Scholar, her work has significantly influenced practices in data-informed teaching and student empowerment through analytics-driven insights. She has co-authored book chapters such as 'Self-regulated learning and the student experience in online higher education' (2023) and contributed to proceedings on adaptive learning systems and feedback interpretation.