Thinking with causal models: A visual formalism for collaboratively crafting assumptions

Ben Hicks, Kirsty Kitto, Leonie Payne, Simon Buckingham Shum

Research output: Book chapter/Published conference paperConference paperpeer-review

5 Citations (Scopus)


Learning Analytics (LA) is a bricolage field that requires a concerted effort to ensure that all stakeholders it affects are able to contribute to its development in a meaningful manner. We need mechanisms that support collaborative sense-making. This paper argues that graphical causal models can help us to span the disciplinary divide, providing a new apparatus to help educators understand, and potentially challenge, the technical models developed by LA practitioners as they form. We briefly introduce causal modelling, highlighting its potential benefits in helping the field to move from associations to causal claims, and illustrate how graphical causal models can help us to reason about complex statistical models. The approach is illustrated by applying it to the well known problem of at-risk modelling.

Original languageEnglish
Title of host publicationLAK22
Subtitle of host publication12th International learning analytics and knowledge conference (LAK22)
Place of PublicationNew York, United States
PublisherAssociation for Computing Machinery
Number of pages10
ISBN (Electronic)9781450395731
Publication statusPublished - 21 Mar 2022
Event12th International Learning Analytics and Knowledge Conference 2022: LAK 2022 - University of California, Irvine, Irvine, United States
Duration: 21 Mar 202225 Mar 2022 (Conference webpage) (Proceedings)

Publication series

NameACM International Conference Proceeding Series


Conference12th International Learning Analytics and Knowledge Conference 2022
Abbreviated titleLearning Analytics for Transition, Disruption and Social Change
Country/TerritoryUnited States
OtherThe 2022 edition of The International Conference on Learning Analytics & Knowledge (LAK22) will take place in Newport Beach, California! LAK22 is organised by the Society for Learning Analytics Research (SoLAR) with location hosts from the University of California, Irvine. LAK22 is a collaborative effort by learning analytics researchers and practitioners to share the most rigorous cutting edge work in learning analytics.

The theme for the 12th annual LAK conference is Learning Analytics for Transition, Disruption and Social Change. This theme brings to the forefront both the dynamic world situation in which learning analytics now operate and the potential role of learning analytics as a driving force for change within it. In a moment when questions about transparency, fairness, equity and privacy of analytics are being brought to the forefront in many areas of application, there is both an opportunity and an imperative to engage with these issues in support of ethical pedagogical transitions and transformative social justice. In addition, as LAK itself explores changing formats for knowledge exchange and generation, this theme offers the opportunity for reflection on how to make the conference more sustainable and accessible for people around the world.

The LAK conference is intended for both researchers and practitioners. We invite both researchers and practitioners of learning analytics to come and join a proactive dialogue around the future of learning analytics and its practical adoption. We further extend our invite to educators, leaders, administrators, government and industry professionals interested in the field of learning analytics and its related disciplines.
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