We are delighted to announce that Kirsty Kitto has joined CIC as a Senior Lecturer in Data Science. Kirsty brings a transdisciplinary approach to the challenge of modelling, and deploying data science applications in complex social systems (such as learning), and is respected internationally within the Complex Systems, Learning Analytics, and ExperienceAPI (xAPI) communities.
We’ll let her introduce herself!
I create novel computational and mathematical approaches to the modelling of cognition in context. I do this by looking for new ways in which we can understand the interplay between humans, their natural and built environments, and the socio-technical information systems that they create. My research enables the creation of technologies that enhance sensemaking and therefore decision making in an increasingly complex and interconnected world. This program of work requires the generation of new transdisciplinary knowledge at the intersection of mathematics, cognitive science, physics, education and data science. I have completed five majors (in theoretical physics, mathematics, philosophy, computer science and Spanish), obtaining a BSc (Hons I), a BA, and a BCompSci in the process. The degree I was seeking did not exist at the time so I had to create it for myself. I currently supervise students with backgrounds in physics, mathematics, computer science, and applied linguistics.
I completed my PhD in Theoretical Physics in 2006 with a thesis titled: Modelling and Generating Complex Emergent Behaviour. Since then I have worked as an Associate Lecturer at Flinders (redesigning physics labs and lecturing), and as a Postdoctoral Fellow and finally Senior Research Fellow on a number of research projects at QUT. My research at QUT commenced over 10 years ago with an ARC funded Discovery Project (DP0773341: The Quantum Mechanics of Semantic Space). This project made use of intriguing similarities between the mathematical structures of quantum theory and recent models of distributional semantics (e.g. Hyperspace Analogue to Language, and Latent Semantic Analysis) to develop new approaches to information retrieval that were grounded in cognitively well founded models of the user.
After two years of research, I was able to secure my own ARC Discovery Project as lead Chief Investigator, as well as an Australian Postdoctoral Fellowship for a project that combined and extended these two streams of research (DP1094974: Generalised Quantum Models of Complexity with Application to Cognitive Systems). At the same time I was named as an investigator on a FP7 Marie Curie IRSES project (N° 247590: Quantum Theory of Context Representation for Information Access and Retrieval), which helped me to continue building my international network of collaborators. My work during this period has served to extend our notion of context in complex systems (Kitto, 2008) and how it affects cognition in scenarios involving language (e.g. Bruza, Kitto, Ramm & Sitbon 2015), memory (e.g. Nelson, Kitto, Galea, McEvoy & Bruza, 2013), and attitude change in a social context (e.g. Kitto & Boschetti 2013).
In addition to this ongoing theoretical research focus, I have also built up a strong reputation for innovation in learning and teaching while at QUT. In 2013-14 I participated in the design and implementation of QUT’s new flagship Imagine Science entry pathway into our Science degree, a compulsory first semester whole of course experience that made use of flipped design principles in QUTs brand new collaborative learning spaces. This work led to my partial secondment to the Office of the Deputy Vice Chancellor (Learning and Teaching) in continuing roles since late 2013. I was first selected into the Transform Project as a Transformational Learning and Teaching Fellow, and then to the Learning Futures team, where I worked on reimagining QUTs approach to online learning. As the sole person in the team with a strong background in mathematics and data science, I was put in charge of developing student facing Learning Analytics (LA) solutions for these projects. More recently, in 2016 I was seconded to the Assessment Quality and Standards team to work on a project aiming to find new ways of using student evaluations of teaching data using modern statistical methods.
While participating in the Transform Project I was able to secure funding from the Office for Learning and Teaching (OLT) in the Innovation and Development scheme for a project that is still in progress (ID14-3821: Enabling Connected Learning via Open Source Analytics in the Wild: Learning Analytics Beyond the Learning Management System). This project makes use of the Experience API (xAPI) a new educational data standard developed as a replacement for SCORM. As one of the earliest adopters of xAPI in learning analytics (Kitto, Cross, Waters & Lupton, 2015), I have pushed the boundaries of how this standard represents learning data, considering its semantics and need for eventual interoperability across multiple educational contexts in a world that will increasingly require lifelong learning. I have also developed learning design patterns that will help instructors to make use of the student facing LA solutions that we are creating. This will enable them to quickly construct novel pedagogies that depend upon giving students access to learning data that helps them to understand their own learning processes (Kitto, Lupton, Davis & Waters, 2016).
In 2015, my achievements in creating complex use cases for the xAPI standard led to an invitation to serve on the inaugural Board of Directors for the Data Interoperability Standards Consortium (DISC), which is taking responsibility for certification and conformance requirements in xAPI. In this role I work with vendors, government agencies, startups and standards bodies to help push the standard forwards. I have recently been awarded a new grant by Graduate Careers Australia (GCA) to create prototype tools that would enable university students to build their own xAPI based Personal Learning Record Stores. These will help them to both set employability related goals, and then track their progress towards achieving them, so building up fine grained evidence of their skills and capabilities that they can use in data supported portfolios when seeking employment.
Finally, as a deeply transdisciplinary academic, I have spent my academic career working across disciplinary silos. This brings with it a tendency to fall between the cracks in a traditional university structure. The launch of the new Faculty of Transdisciplinary Innovation signalled an opportunity to truly belong to a structure created for people like me, and I’m delighted to join CIC at this exciting time.
- Bruza, P. D., Kitto, K., Ramm, B. J., & Sitbon, L. (2015). A probabilistic framework for analysing the compositionality of conceptual combinations. Journal of Mathematical Psychology, 67, 26-38.
- Kitto, K. (2008). High end complexity. International journal of general systems, 37(6), 689-714.
- Kitto, K., & Boschetti, F. (2013). Attitudes, ideologies and self-organization: information load minimization in multi-agent decision making. Advances in Complex Systems, 16(02n03), 1350029.
- Kitto, K., Cross, S., Waters, Z., & Lupton, M. (2015). Learning Analytics beyond the LMS: the Connected Learning Analytics Toolkit. In Proceedings of the Fifth International Conference on Learning Analytics and Knowledge (LAK15). ACM, New York, NY, USA, 11-15.
- Kitto, K., Lupton, M., Davis, K., & Waters, Z. (2016). Incorporating student-facing learning analytics into pedagogical practice. In S. Barker, S. Dawson, A. Pardo, & C. Colvin (Eds.), Show Me The Learning. Proceedings ASCILITE 2016 Adelaide, pp. 338-347.
- Nelson, D. L., Kitto, K., Galea, D., McEvoy, C. L., & Bruza, P. D. (2013). How activation, entanglement, and searching a semantic network contribute to event memory. Memory & cognition, 41(6), 797-819.