Dr Paula de Barba
- Building: Elisabeth Murdoch Building
- Road: Spencer Road
- Campus: Parkville
Paula's role focuses on research in the areas of educational technology, educational psychology and learning analytics in higher education. Her main research interests include self-regulated learning and achievement motivation.
Paula de Barba has worked as research fellow at the Melbourne Centre for Studies in Higher Education since July 2014. Her role focuses on research in the areas of educational technology, educational psychology and learning analytics. More specifically, Paula is interested on the cognitive and emotional influences on student learning, such as achievement motivation and self-regulated learning, in digital learning environments. She is part of the Educational Technology Research Group and the Learning Analytics Research Group.
Paula completed her PhD at the Melbourne School of Psychological Sciences in 2018, at the University of Melbourne. Her PhD investigated how students’ autonomous learning skills and achievement motivation function in online learning environments. Paula’s supervisors were Gregor Kennedy and Mary Ainley. She is currently undertaking post-doctoral studies at MCSHE, supervised by Kristine Elliott and Gregor Kennedy.
2019. Supporting self-regulated learning through personalised analytics-based feedback in STEM education. Paula de Barba. The University of Melbourne, Early Career Researcher Grants Scheme. Funding: $25,000.
2017. Learning reflections: Designing interventions to promote learning in museums. Gregor Kennedy, Cameron Hocking, Eduardo Araujo Oliveira, Paula de Barba, Kristine Elliot, Ben Cleveland. The University of Melbourne and Museum Victoria, McCoy Project. Funding: $20,000.
2016. Determining students’ assessment feedback preferences for personal analytics solutions. Linda Corrin, Paula de Barba, Gregor Kennedy. Office of Learning and Teaching (Seed grant). Funding: $40,000.
Broadbent, J., Panadero, E., Lodge, J., & de Barba, P. G. (2019). Technologies to enhance self-regulated learning in online and computer mediated learning environments. In M. J. Bishop, J. Elen, E. Boling, & V. Svihla (Eds), Handbook of Research in Educational Communications and Technology. New York, NY: Springer.
Lodge, J., Panadero, E., Broadbent, J., & de Barba, P. G. (2018). Supporting self-regulated learning with learning analytics. In J. M. Lodge, J. C. Horvath & L. Corrin (Eds), Learning Analytics in the Classroom: Translating Learning Analytics for Teachers (Chapter 4). New York, NY: Routledge.
Brooker, A., Corrin, L., de Barba, P. G., Lodge, J., & Kennedy, G. (2018). A tale of two MOOCs: How student motivation and participation predict learning outcomes in different MOOCs. Australasian Journal of Educational Technology 34 (1), 73-87.
Kennedy, G., Corrin, L., & de Barba, P. G. (2017). Analytics of what? Negotiating the seduction of big data and learning analytics. In R. James, S. French & P. Kelly (Eds), Visions for Australian Tertiary Education (pp. 67-76). Melbourne, Australia: Melbourne Centre for the Study of Higher Education.
de Barba, P., Ainley, M.D. & Kennedy, G. (2016). The role of motivation and participation for predicting performance in MOOCs. Journal of Computer Assisted Learning, 32(3), 218-231.
de Barba, P., Kennedy, G., & Trezise, K. (2018). Procedural and conceptual confusion in a discovery-based digital learning environment. Proceedings ASCILITE 2018 Geelong (pp. pp. 340-345). Australia.
Corrin, L., & de Barba, P. (2017). Understanding students’ views on feedback to inform the development of technology-supported feedback systems. Proceedings ASCILITE 2017 Toowoomba (pp. 47). Australia.
Trezise, K., de Barba, P., Jennens, D., Zarebski, A., Russo, R., & Kennedy, G. (2017). A learning analytics view of students’ use of self-regulation strategies for essay writing. Proceedings ASCILITE 2017 Toowoomba (pp. 411). Australia.
Corrin, L., de Barba, P. G., & Bakharia, A. (2017). Using learning analytics to explore help-seeking learner profiles in MOOCs. Proceedings of the 7th International Learning Analytics & Knowledge Conference (pp. 424-428). New York: ACM.
de Barba P., Ainley, M.D. & Kennedy, G. (2017). Interest development across a MOOC (Massive Open Online Course). Presentation at the 17th Biennial EARLI conference for Research on Learning and Instruction. Helsinki, Finland.
Arguel, A., Lodge, J. M., Pachman, M. & de Barba, P. (2016). Confidence drives exploration strategies in interactive simulations. In S. Barker, S. Dawson, A. Pardo, & C. Colvin (Eds.). Proceedings ASCILITE 2016 Adelaide (pp. 33-42). Australia.
Bakharia, A., Corrin, L., de Barba, P., Kennedy, G., Gasevic, D., Mulder, R., Williams, D., Dawson, S., Lockyer, L. (2016). A conceptual framework linking learning design with learning analytics. In T. Reiners, B.R. von Konsky, D. Gibson, V. Chang, L. Irving, & K. Clarke (Eds,), Proceedings of the 6th International Conference on Learning Analytics and Knowledge (pp. 409-413). New York: ACM.
Corrin, L., Kennedy, G., de Barba, P.D., Bakharia, A., Lockyer, L., Gasevic, D., Williams, D., Dawson, S., & Copeland, S. (2015). Loop: A learning analytics tool to provide teachers with useful data visualisations. In T. Reiners, B.R. von Konsky, D. Gibson, V. Chang, L. Irving, & K. Clarke (Eds.), Globally connected, digitally enabled. Proceedings ascilite 2015 in Perth (pp. 409-413). Perth, Australia.
de Barba P., Ainley, M.D. & Kennedy, G. (2015). Situational Interest and Online Learning: A Closer Look. Presentation at the 16th Biennial EARLI conference for Research on Learning and Instruction, Cyprus University of Technology, Limassol, Cyprus.
Corrin, L., & de Barba, P. (2015). How do students interpret feedback delivered via dashboards?. In Proceedings of the Fifth International Conference on Learning Analytics And Knowledge. ACM.
de Barba P., Ainley, M.D. & Kennedy, G. (2015). The trajectory of situational interest in an online learning session. Presentation at the American Educational Research Association Annual Meeting, Chicago, United States of America.
Kennedy, G., de Barba, P., Coffrin, C., & Corrin, L. (2015). Predicting success: How learners’ prior knowledge, skills and activities predict MOOC performance. In P. Blikstein, A. Merceron, & G. Siemens (Eds.), Proceedings of the 5th International Conference on Learning Analytics and Knowledge (pp. 136-140). New York: ACM.
Corrin, L., & de Barba, P. (2014). Exploring students’ interpretation of feedback delivered through learning analytics dashboards. In B. Hegarty, J. McDonald, & S.-K. Loke (Eds.), Proceedings ascilite Dunedin 2014 (pp. 629-633). Dunedin, New Zealand.
de Barba, P. (2014). Massive Open Online Courses (MOOCs), Learning Analytics, and the Future of Higher Education. Presentation at the Universitas 21 Future of International Higher Education Workshop, The University of Nottingham, Ningbo, China.
de Barba, P., Ainley, M.D. & Kennedy, G. (2014). The role of motivation and participation in predicting performance in MOOCs. International Conference on Motivation. Helsinki, Finland.
Coffrin, C., Corrin, L., de Barba, P., & Kennedy, G. (2014). Visualizing patterns of student engagement and performance in MOOCs. In M. Pistilli, J. Willis, D. Koch, K. Arnold, S. Teasley, & A. Pardo (Eds.), Proceedings of the 4th International Conference on Learning Analytics and Knowledge (pp. 83-92).
Bower, M., Kennedy, G. E., Dalgarno, B., Lee, M. J., Kenney, J., & de Barba, P. (2012). Use of media-rich real-time collaboration tools for learning and teaching in Australian and New Zealand universities. In Proceedings of the 2012 ascilite.
Araujo Oliveira, E., & de Barba, P. (2018, December 11). How does learning happen in museums? Pursuit.
Corrin, L., Kennedy, G., & de Barba, P. (2017, February 17). Asking the right questions of big data in education. Pursuit.
Harding, S., de Barba, P., & Goh, F. (2016, October 11). Teaching self-regulated learning skills. Teacher Magazine.