Paul Montuoro is a psychometrician and educational measurement researcher with a PhD in Education and almost twenty years of experience in education spanning statistical agencies, teaching, academic research, and large-scale assessment programs. Paul's professional career began with the Australian Bureau of Statistics (ABS) graduate program following a First Class Honours degree. He subsequently completed an undergraduate degree in Education and worked as a primary and secondary school teacher, before a growing interest in attachment theory and its impact on the teacher-student relationship led him to pursue a PhD. During and after his doctoral work at La Trobe University, Paul conducted research on classroom management, student behaviour, and critical theory — published in various journals, including the British Journal of Educational Psychology, the Journal of Educational Research, and as chapters in edited volumes.
Paul completed his Master's degree after his PhD, which is where things took an unexpected turn. Using the Rasch model, he debunked the very scales he had employed in his PhD — instruments that had been used in educational and clinical psychology for over three decades to measure attachment style — demonstrating that they were not unidimensional. This led to intensive work with Stephen Humphry at the University of Western Australia, where Paul held a Research Fellow position for five years. Most notably they published in the Logistic Measurement Function (LMF), a theoretical extension of the Rasch model that satisfies Rasch's criteria for measurement while allowing varying discrimination among item sets. Their collaborative publications in Frontiers in Education and the Journal of Psychoeducational Assessment also span differential item functioning, construct validity, cumulative order, and the pairwise model. Paul is also co-author of an early OECD Education Working Paper on AI scoring for international large-scale assessments using deep learning and multilingual PISA data.
Paul's current research is at the frontier of measurement theory. He is preparing a large-scale simulation study demonstrating the advantages of the Rasch model over the two-parameter logistic (2PL) model, showing that the property of specific objectivity — which gives the Rasch model its invariant measurement units — also yields substantially better parameter recovery than 2PL estimation, even when data are generated from a 2PL process. Separately, he is investigating how the Rasch model captures exponential growth patterns observed in brain development, drawing on parallels with Julian Huxley's work on exponential growth in biological systems.
Since 2017, Paul has been Chief Psychometrician at Janison, where he leads psychometric work across various programs, including Academic Assessment Services (AAS) programs and the Post-Secondary Academic Measure (PSAM), a Year 12 analysis and reporting platform used by more than 40 schools across HSC, VCE, QCE, and IB pathways. He is also working with the New Zealand Ministry of Education on the establishment of their national testing program. Paul has also worked with 3P Learning to assist with the development of curriculum mapping technologies and a novel machine learning method called Feature-rich Iterative Residual Boosting (FIRB), which significantly improves the accuracy of automated writing marking.
