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Dr Roberto Martinez-Maldonado


Roberto Martinez-Maldonado (B.Eng., M. IT., Ph. D.) is a postdoctoral research associate in the Connected Intelligence Centre (CIC) at the University of Technology, Sydney (UTS), Australia, working with Prof. Simon Buckingham Shum. He obtained his doctorate degree in 2014 from the Computer Human Adapted Interaction Research Group (CHAI) at the University of Sydney, Australia.

He worked on Prof. Peter Goodyear’s Australian Research Council (ARC) Laureate Fellowship program – ‘Learning, technology and design: architectures for productive networked learning’ at Centre for Research on Computer Supported Learning and Cognition (CoCo) in the University of Sydney.

He is currently actively involved in a project which is a receiver of the last round of OLT grants (2016) titled: 'Scaling the Provision of Personalised Learning Support Actions to Large Student Cohorts'

Read my publications here: PUBLICATIONS


  • Australian Research Council (ARC) Assessor 
  • Member of the Association for Computing Machinery (ACM)
  • Member of the Society of Learning Analytics Research (SoLAR)
  • Member of the International Society of the Learning Sciences (ISLS)
  • Member of the International Educational Data Mining Society (IEDMS)
Image of Roberto Martinez-Maldonado
Research Fellow, Connected Intelligence Centre
Bachelor of Science in Computer Systems Engineering, Information Technologies Management, Learning Sciences, Artificial Intelligence, Educational Data Mining and HCI
+61 2 9514 1914

Research Interests

Human Computer Interaction, Surface Computing, Computer-Supported Collaborative Learning, Orchestration Technology, Learning Analytics, Artificial Intelligence, Educational Data Mining and Data Science.

Can supervise: Yes


Martinez-Maldonado, R., Anderson, T., Shum, S.B. & Knight, S. 2016, 'Towards supporting awareness for content curation: The case of food literacy and behavioural change', CEUR Workshop Proceedings, pp. 42-46.
Copyright © 2016 for the individual papers by the papers' authors.This paper presents a theoretical grounding and a conceptual proposal aimed at providing support in the initial stages of sustained behavioural change. We explore the role that learning analytics and/or open learner models can have in supporting life-long learners to enhance their food literacy through a more informed curation process of relevant-content. This approach grounds on a behavioural change perspective that identifies i) knowledge, ii) attitudes, and iii) self-efficacy as key factors that will directly and indirectly affect future decisions and agency of life-long learners concerning their own health. The paper offers some possible avenues to start organising efforts towards the use of learning analytics to enhance awareness in terms of: knowledge curation, knowledge sharing and knowledge certainty. The paper aims at triggering discussion about the type of data and presentation mechanisms that may help life-long learners set a stronger basis for behavioural change in the subsequent stages.
Martinez-Maldonado, R., Schneider, B., Charleer, S., Buckingham Shum, S., Klerkx, J. & Duval, E. 2016, 'Interactive surfaces and learning analytics: data, orchestration aspects, pedagogical uses and challenges', LAK '16 Proceedings of the Sixth International Conference on Learning Analytics & Knowledge, Sixth International Conference on Learning Analytics & Knowledge, ACM, Edinburgh, United Kingdom, pp. 124-133.
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The proliferation of varied types of multi-user interactive surfaces (such as digital whiteboards, tabletops and tangible interfaces) is opening a new range of applications in face-to-face (f2f) contexts. They offer unique opportunities for Learning Analytics (LA) by facilitating multi-user sensemaking of automatically captured digital footprints of students' f2f interactions. This paper presents an analysis of current research exploring learning analytics associated with the use of surface devices. We use a framework to analyse our first-hand experiences, and the small number of related deployments according to four dimensions: the orchestration aspects involved; the phases of the pedagogical practice that are supported; the target actors; and the levels of iteration of the LA process. The contribution of the paper is twofold: 1) a synthesis of conclusions that identify the degree of maturity, challenges and pedagogical opportunities of the existing applications of learning analytics and interactive surfaces; and 2) an analysis framework that can be used to characterise the design space of similar areas and LA applications.