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Tracie FarrellMember status icon

Research Associate
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Tracie Farrell is a research associate working with the Web Science research group at KMi. Her current research interests include the impact of new technologies on society and culture, in particular, the opportunities and challenges presented by communication and interaction at scale. Her research interests include epistemology, metacognition, self-regulated learning, technology-enhanced learning and digital pedagogy. Before starting her PhD, Tracie worked for 18 years in the non-formal education sector on issues related to human rights, leadership and citizenship.

Keys: metacognition, epistemology, self-regulated learning, analytics for learning








18 Oct 2022

17 Jun 2022

15 Jun 2022

08 Jun 2022

16 May 2022

View all 26 Articles


Publications | Visit External Site for Details Publications | doi 

Farrell, T., Alani, H. and Mikroyannidis, A. (2022) Mediating learning with learning analytics technology: guidelines for practice, Teaching in Higher Education, pp. 1-21

Publications | Visit External Site for Details Publications | doi 

Kbaier, D., Ismail, N., Farrell, T. and Kane, A. (2022) Experience of Health Professionals with Misinformation and Its Impact on Their Job Practice: Qualitative Interview Study, JMIR formative research, pp. (Early access)

Publications | Visit External Site for Details Publications | doi 

Kwarteng, J., Perfumi, S., Farrell, T., Third, A. and Fernandez, M. (2022) Misogynoir: Challenges in Detecting Intersectional Hate, Social Network Analysis and Mining (SNAM), 12

Publications | Visit External Site for Details  

Kwarteng, J., Perfumi, S., Farrell, T. and Fernandez, M. (2021) Misogynoir: Public Online Response Towards Self-Reported Misogynoir, The 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 21), Online

Publications | Visit External Site for Details  

Piccolo, L., Blackwood, A., Farrell, T. and Mensio, M. (2021) Agents for Fighting Misinformation Spread on Twitter: Design Challenges, Conversational User Interfaces CUI 2021, Online

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Dr. Siān Lindley
Microsoft Research Cambridge

Actions and their Consequences: Implicit Interactions with Machine Learned Knowledge Bases

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The Open University
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