causal inference Archives - EduTec Science

Educational Technology, like many other empirical research fields, needs to provide evidence for the causal effectiveness of their interventions. This is as important for establishing the efficacy of some novel educational technology as it is for theory-building. However, because educational research, especially field research, can be messy, tightly-controlled randomized experiments are not always the best option. Importantly, as our development paper shows, this does not mean that researchers should abandon all claims of causality. Instead, we highlight the importance of explicit causal reasoning, while equipping researchers with a tool to approach this daunting task systematically. Causal graphs (or Directed Acyclic Graphs = DAGs) are a low-barrier approach to reasoning about causality in all research contexts. Using a few construction rules, the resultant graphs allow researchers to figure out whether a…

Learning Analytics is an applied field of research with the goal of producing actionable knowledge to improve student learning. This requires knowledge about cause-and-effect. However, randomized experiments, the usual vehicle for causality, are not always feasible nor desirable. Researchers are then left with observational data, from which they are, understandably, hesitant to draw causal inferences. Fortunately, there has been a lot of progress on the topic of causality in the last two decades. One prominent framework uses Directed Acyclic Graphs (DAGs) to graphically reason about cause-and-effect and/or bias. This primer, authored by Joshua Weidlich, Dragan Gasevic, and Hendrik Drachsler, published in the Journal of Learning Analytics, introduces DAGs to Learning Analytics. Using fictitious and published examples, we show how DAGs are a principled approach to a) improve causal inferences for…

Tag: causal inference

New pub: Causal reasoning with causal graphs, published in ETRD

New Pub: Causal Inference and Bias in Learning Analytics