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Dr Simon Knight


My research focuses on how people think about knowledge and its representation. In philosophy of education my dissertation (Masters, UCL) looked at the epistemological side of assessment policy. My current work takes an empirical approach to student epistemic cognition - thinking about what we know, and how - particularly in information seeking and writing contexts. I've explored this by exploring the collaborative dialogue of small groups of children (MPhil, Cambridge) and undergraduates (PhD, Open) when using a collaborative browser addon (Coagmento, developed by Rutgers University).

I maintain a full CV and publication list on my personal website (see link below).


  • Section Editor of the Journal of Learning Analytics (hot spot section)
  • Chartered member of the British Psychological Society (CPsychol)
  • Member of Society for Text and Discourse
  • Member of Philosophy of Education Society of Great Britain
  • Member of Society of Learning Analytics Research
  • Qualified Secondary Teacher (I primarily taught A-level philosophy and psychology in the UK)
Lecturer, Connected Intelligence Centre
B.Sc (Intl Hons, Leeds), PGCE (UCL), MA (UCL), MPhil (Cambridge), Ph.D
+61 2 9514 8908

Research Interests

My current research explores student writing practices (including information seeking, reading, note taking, writing processes, and peer and self-assessment of writing). I'm particularly interested in the relationship of these practices to ways of thinking about knowledge and evaluation (epistemic cognition) and collaborative knowledge practices (including co-writing, formative feedback, collaborative information seeking, etc.). I take a systemic approach in considering the policy and practice context of writing and its analysis.
Can supervise: Yes

I'm interested in supporting students very broadly in learning analytics, and particularly in topics around epistemic cognition and student writing.

I coordinate the 'Data Science for Innovation' subject in our Masters in Data Science and Innovation, and teach on/coordinate the undergraduate quantitative literacy subject 'Arguments, Evidence, and Intuition'


Buckingham Shum, S., Knight, S., McNamara, D., Allen, L., Betik, D. & Crossley, S. 2016, 'Critical Perspectives on Writing Analytics'.
Knight, S. & Anderson, T. 2016, 'Action-oriented, Accountable, and inter(Active) Learning Analytics for Learners', ACM Press.
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.
Gibson, A., Knight, S., Aitken, A., Buckingham Shum, S., Ryan, P., Jarvis, W., Nikolova, N., Tsingos-Lucas, C., Parr, A., White, A. & Sutton, N. 2016, 'Using Writing Analytics For Formative Feedback', UTS Teaching and Learning Forum, University of Technology, Sydney.
Knight, S., Buckingham Shum, S. & Littleton, K. 2013, 'Epistemology, Pedagogy, Assessment and Learning Analytics', Proc. 3rd International Conference on Learning Analytics & Knowledge, pp. 75-84.

Journal articles

Knight, S., Buckingham Shum, S., Ryan, P., Sándor, Á. & Wang, X. 2017, 'Academic Writing Analytics for Civil Law: Participatory Design Through Academic and Student Engagement', International Journal of Artificial Intelligence in Education.
View/Download from: UTS OPUS or Publisher's site
Research into the teaching and assessment of student writing shows that many students find academic writing a challenge to learn, with legal writing no exception. Improving the availability and quality of timely formative feedback is an important aim. However, the time-consuming nature of assessing writing makes it impractical for instructors to provide rapid, detailed feedback on hundreds of draft texts which might be improved prior to submission. This paper describes the design of a natural language processing (NLP) tool to provide such support. We report progress in the development of a web application called AWA (Academic Writing Analytics), which has been piloted in a Civil Law degree. We describe: the underlying NLP platform and the participatory design process through which the law academic and analytics team tested and refined an existing rhetorical parser for the discipline; the user interface design and evaluation process; and feedback from students, which was broadly positive, but also identifies important issues to address. We discuss how our approach is positioned in relation to concerns regarding automated essay grading, and ways in which AWA might provide more actionable feedback to students. We conclude by considering how this design process addresses the challenge of making explicit to learners and educators the underlying mode of action in analytic devices such as our rhetorical parser, which we term algorithmic accountability.


Gibson, A., Knight, S., Aitken, A., Buckingham Shum, S., Ryan, P., Jarvis, W., Nikolova, N., Tsingos-Lucas, C., Parr, A., White, A., Sutton, N. & Tsingos-Lucas, C. 2016, 'Using Writing Analytics For Formative Feedback'.
  • In the AWA project we collaborate with Xerox Research in Europe (XRCE)
  • Work from my PhD is in collaboration with:
    • Chirag Shah and Matthew Mitsui at Rutgers University InfoSeeking Lab http://www.infoseeking.org/
    • Dirk Tempelaar at Maastricht University,
    • Bart Rienties and Karen Littleton at the Open University, UK
  • We have active collaborations with the SOLET (Science of Learning and Educational Technology) lab at Arizona State University
  • We collaborate with a number of Australian universities