Associate Professor Lorenzo Vigentini

Senior Academic Developer
PhD, MSc, PGCert, FHEA, CPsychol

Email: lorenzo.vigentini@nd.edu.au

  • Biography

    Lorenzo Vigentini is Associate Professor in the School of Health Sciences, partnering with the Innovation & Design team in the Division of the Vice-Chancellor (Education). A psychologist by training, with a PhD from the University of Edinburgh in educational data mining and e-learning, he has spent more than two decades working at the intersection of learning, technology and data in universities in the UK and Australia.

    Before joining Notre Dame in 2025 he was Academic Lead, Educational Intelligence and Analytics at UNSW Sydney (2016–2021), where he led the implementation of learning analytics and educational technology across the institution, co-led the Students as Partners initiative, and directed the data products underpinning quality assurance and enhancement. He subsequently worked in behavioural data analysis at ANSTO and led higher education and mental health training as Associate Director, Training and Education at HETI (NSW Health).

    At Notre Dame he works with colleagues on the re-design of Bachelor of Health Sciences courses for Blackboard Ultra and online delivery, and led the stakeholder discovery and analysis for a University-wide review of digital learning and teaching. He is a Fellow of the Higher Education Academy and a Chartered Psychologist, and has published extensively in learning analytics, educational technology and MOOCs.

    • Academic development and professional learning for university teachers — foundational teaching programmes, graduate certificates in university teaching and academic practice, and development programmes for graduate teaching assistants.
    • Learning design for blended and online delivery, including multi-campus and multi-modal course models, and MOOC design.
    • Assessment design and academic integrity, including assessment redesign in the context of generative AI.
    • Learning analytics, educational data science, and the evaluation of teaching.
    • Educational psychology: individual differences, approaches to learning and motivation.
    • Research methods and research supervision in education and computing.

  • Teaching areas

    • Research methodology and statistics in psychology and health
    • Computational approaches in cognition
    • Individual differences in personality, cognition and functioning across the lifespan
    • Learning, teaching and governance in HE

  • Research expertise and supervision

    Research expertise:

    AI, analytics and data mining; personalised feedback at scale; learning dashboards and data visualisation; student experience, evaluation and the student voice (including NLP applied to student comments); quantified self, individual differences, AI in higher education; VR/AR and immersive learning environments.

    Supervision interests:

    Available to supervise HDR candidates. Emphasis in Learning and teaching across disciplines, use and adoption of AI in health sciences and medicine, human analytics, technology-enhanced learning and living, philosophical and ethical implication of technology, evaluation approaches and innovation.

  • Books

    Edited volumes and proceedings (no authored monograph):

    • Vigentini, L. & Evans, C. (Eds.) (2015). The Relevance of Styles to Educational and Workplace Contexts — Proceedings of the XX ELSIN Conference. ISBN 978-80-263-0944-4.
    • Vigentini, L., Wang, Y., Paquette, L. & León Urrutia, M. (Eds.) (2017). MOOC analytics: live dashboards, post-hoc analytics and the long-term effects. Joint MOOCs workshops, LAK 2017. CEUR-WS Vol. 1967.

  • Book Chapters

    Selected contributions:

    • Vigentini, L., Swibel, B. & Hasler, G. (2021). A comparison of LA dashboards in schools and higher education: a focus on goal setting and support processes. In Muhittin & Ifenthaler (Eds.), Visualisations and Dashboards for Learning Analytics. Springer. doi:10.1007/978-3-030-81222-5_14
    • Arthars, N., Dollinger, M., Vigentini, L., Liu, D., Kondo, E. & King, D. (2019). Empowering teachers to personalize learning support. In Ifenthaler, Mah & Yau (Eds.), Utilizing Learning Analytics to Support Study Success. Springer.
    • Mirriahi, N. & Vigentini, L. (2017). Analytics of learner video use. In Siemens & Lang (Eds.), Handbook of Learning Analytics & Educational Data Mining. SoLAR.
    • Vigentini, L., Clayphan, A. & Zhang, X. (2016). Taming the MOOC data deluge with learning analytic dashboards. In Peña-Ayala (Ed.), Learning Analytics: Fundaments, Applications and Trends. Springer.
    • Vigentini, L., Mirriahi, N. & Kligyte, G. (2016). From reflective practitioner to active researcher: towards a role for learning analytics in higher education scholarship. In Spector, Lockee & Childress (Eds.), Learning, Design, and Technology: An International Compendium.

  • Journal Articles and Proceedings

    • Vigentini, L., Swibel, B. & Hasler, G. (2022). Developing a growth learning data mindset: a secondary school approach to creating a culture of data-driven improvement. Journal of Learning Analytics, 9(2), 87–104. doi:10.18608/jla.2022.7377
    • Vigentini, L., Liu, D. Y. T., Arthars, N. & Dollinger, M. (2020). Evaluating the scaling of a LA tool through the lens of the SHEILA framework: a comparison of two cases from tinkerers to institutional adoption. The Internet and Higher Education, 45, 100728.
    • Ford, R., Vigentini, L., Vulic, J., Chitsaz, M. & Prusty, B. G. (2019). A Massive Open Online Course (MOOC) on engineering mechanics: data analytics informing learning design and improvement. Australian Journal of Mechanical Engineering. doi:10.1080/14484846.2019.1596049
    • Pardo, A., Bartimote, K., Buckingham Shum, S., Dawson, S., Gao, J., Gašević, D., … Vigentini, L. (2018). OnTask: delivering data-informed, personalized learning support actions. Journal of Learning Analytics, 5(3), 235–249. doi:10.18608/jla.2018.53.15
    • Vigentini, L. (2009). Using learning technology in university courses: do styles matter? Multicultural Education and Technology Journal, 3(1), 17–32.
    • Under review: Vigentini, L. & D'Angelo, A. Team-work with a twist: engineering diversity for optimal outcomes in an International Business postgraduate course. Journal of Teaching in International Business. — Vigentini, L. & Bucic, T. Goal orientations in university students: a validation study of constructs and measurement stability of three instruments. Educational Psychology.

  • Conference Papers

    Selected from 31 peer-reviewed papers in ISBN proceedings:

    • Liang, Z-W. M. & Vigentini, L. (2019). Comparing virtual environments building tools: a framework and the evaluation of AWS Sumerian. IEEE TALE 2019. [Best Conference Paper Award]
    • Ford, R., Vigentini, L., Vulic, J., Chitsaz, M. & Prusty, B. G. (2016). Through engineers' eyes: a MOOC experiment. AAEE 2016. [Best Conference Paper Award]
    • Vigentini, L., Liu, D. Y.-T. & Lim, L. (2020). Personalising feedback at scale: lessons from practitioners. Companion Proceedings LAK'20.
    • Murray, T. & Vigentini, L. (2019). Moving in virtual environments: a non-Euclidean approach to improve presence and vection in VR. IEEE TALE 2019.
    • Liu, D. Y.-T., Vigentini, L., Kondo, E., Samnick, K. & Weeks, R. (2018). Trojan horse analytics: hooking educators on personalised feedback at scale at multiple Australian universities. Companion Proceedings LAK'18.
    • Mittal, A., Vigentini, L., Djatmiko, M., Prusty, G., Sharma, Y. & King, M. E. (2018). Mooc-O-Bot: using cognitive technologies to extend knowledge support in MOOCs. IEEE TALE 2018.
    • Bucic, T., Vigentini, L. & King, M. (2018). Juggling system and data streams to personalize feedback: the case of a large first year course. Companion Proceedings LAK'18.
    • Vigentini, L., Kondo, E., Samnick, K., Liu, D. Y., King, D. & Bridgeman, A. J. (2017). Recipes for institutional adoption of a teacher-driven learning analytics tool: case studies from three Australian universities. ASCILITE 2017.
    • Vigentini, L., León Urrutia, M. & Fields, B. (2017). FutureLearn data: what we currently have, what we are learning and how it is demonstrating learning in MOOCs. LAK 2017, 512–513. ACM.
    • McIntyre, S., Vigentini, L., Mirriahi, N. & Zhao, C. (2016). The journey towards goal driven learning in MOOCs — the Learning to Teach Online MOOC. LAK 2016.

  • Professional Affiliations

    • Fellow of the Higher Education Academy (FHEA, Advance HE) — since 2010; Research Associate of the HEA since 2012.
    • Chartered Psychologist (CPsychol) and Associate Fellow of the British Psychological Society (AFBPsS).
    • Member, Division of Teachers and Researchers in Psychology (BPS); Member, Mathematical, Statistical and Computing Psychology Section (BPS).
    • Member, Association for Learning Technology (ALT) — since 2009.
    • Member, Australasian Association of Institutional Research (AAIR) — since 2013.
    • Member, Society for Learning Analytics Research (SoLAR) — since 2014.
    • Member, IEEE — Computer Society, Education Society, and Society on Social Implications of Technology.

  • Community Engagement

    • Founder and lead, Learning Analytics and Educational Data Science research group, UNSW (from 2016), convening a fortnightly seminar series and establishing links with the Big Data in Health and Machine Learning groups.
    • Member, UNSW Human Research Ethics Advisory Panel (Social Science, Education and Law) from 2016; Chair in 2018.
    • Co-convenor of the international "Personalising feedback at scale" workshop series at the Learning Analytics and Knowledge (LAK) conference, 2018–2020.
    • Member of the Executive, Education, Learning, Styles and Individual Differences Network (ELSIN).
    • Led HETI's response to the TEQSA Request for Information on the challenges and opportunities of AI in higher education (2023–24).
    • External assessor for academic promotion (University of Sydney, 2016); reviewer for learning analytics and educational technology journals and conferences.

  • Awards

    • Collaborator in the Pearson–ACODE Award for Innovation in Technology Enhanced Learning (2017).
    • Best Conference Paper, IEEE Teaching, Assessment and Learning for Engineering (TALE) Conference (2019) — Liang & Vigentini, on comparing virtual-environment building tools.
    • Best Conference Paper, Australasian Association for Engineering Education (AAEE) Conference (2016) — Ford, Vigentini, Vulic, Chitsaz & Prusty, "Through Engineers' Eyes: A MOOC Experiment".
    • Nominated, Higher Education Academy (Psychology) Teaching Award (2008).
    • Certified WebCT Designer (full accreditation), 2005.

  • Other

    Selected research and project funding (as principal investigator or co-investigator):

    • 2018 — UNSW Students as Partners Program, co-lead in the PVC (Education) portfolio: AUD 1.2M.
    • 2016 — Office for Learning and Teaching SP16-5264, "Scaling the provision of personalised learning support actions for large student cohorts", co-investigator: AUD 350,000.
    • 2016 — UNSW PVC (Education) "Heroes Program" fund: AUD 190,000.
    • 2015 — UNSW "Skunkworks" learning analytics fund: AUD 120,000.
    • 2019 — UNSW DVC (Academic), "Biometrics in Learning & Teaching and VR": AUD 85,000.