Dr Paula de Barba

Postdoctoral Research Fellow

Melbourne CSHE

Dr Paula de Barba is a Postdoctoral Research Fellow in the Melbourne Centre for the Study in Higher Education. She has been part of the centre as a Research Fellow since 2014, contributing and conducting several research projects in the fields of educational technology and educational psychology. Paula is currently part of the Technology-Enhanced Learning in Higher Education research group at the Melbourne CSHE.

Paula’s expertise is on the cognitive and emotional influences on student learning in digital learning environments. She is particularly interested on how people learn autonomously and how we can best support them. From a social cognitive theory perspective, Paula uses models of self-regulated learning and motivation theory to guide her research. Her approach is mainly quantitative, combining the use of learning analytics with self-reported surveys, with some experience in mixed methods research. Topics of her academic publications and presentations include:

  • Autonomous learning and achievement motivation in MOOCs;
  • Self-regulated learning and learning analytics;
  • Self-regulated learning and STEM education;
  • Confusion and self-regulated learning in digital learning environments;
  • Learning analytics and learning design.

Since 2018, Paula is the co-presenter of the workshop “Using Learning Analytics in Teaching”. This is a Melbourne CSHE professional development initiative in partnership with Learning environments for University of Melbourne teachers.

For more details on Paula's research please visit her Google Scholar and ResearchGate profiles.

Research grants

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.

Academic publications

de Barba, P. G., Malekian, D., Oliveira, E. A., Bailey, J., Ryan, T., & Kennedy, G. (2020). The importance and meaning of session behaviour in a MOOC. Computers & Education146. https://doi.org/10.1016/j.compedu.2019.103772

Broadbent J., Panadero E., Lodge J.M., de Barba P. (2020) Technologies to Enhance Self-Regulated Learning in Online and Computer-Mediated Learning Environments. In: Bishop M.J., Boling E., Elen J., Svihla V. (eds) Handbook of Research in Educational Communications and Technology. Springer, Cham. https://doi.org/10.1007/978-3-030-36119-8_3

Trezise, K., Ryan, T., de Barba, P., & Kennedy, G. (2019). Detecting Academic Misconduct Using Learning Analytics. Journal of Learning Analytics6(3), 90-104. https://doi.org/10.18608/jla.2019.63.11

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.

Conference participation

Oliveira, E. A., Conijn, R., De Barba, P., Trezise, K., van Zaanen, M., & Kennedy, G. (2020) Writing analytics across essay tasks with different cognitive load demands. In proceedings of ASCILITE 2020 (pp. 60).

De Barba, P., Elliott, K. & Kennedy, G. (2019). Students’ self-regulated learning skills and attitudes in online scientific inquiry tasks. In Y. W. Chew, K. M. Chan, and A. Alphonso (Eds.), Personalised Learning. Diverse Goals. One Heart. ASCILITE 2019 Singapore (pp. 407-412).

Malekian, D., Bailey, J., Kennedy, G., de Barba, P., & Nawaz, S. (2019). Characterising Students' Writing Processes Using Temporal Keystroke AnalysisInternational Educational Data Mining Society.

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.

Outreach articles

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.