University|12-06-2025

Causal diagrams

Causal diagrams are simple sketches of boxes and arrows that we use after reading to make the cause–effect relationships in a subject text visible. This very act of making things visible provides the hard evidence that good monitoring needs: instead of relying on reading speed or a comfortable sense of understanding, learners can immediately see where boxes are missing, arrows are uncertain, or relationships are off.

A recent study examined whether diagramming alone is enough—or whether an additional, explicit self-assessment of one’s own diagrams makes things even better. The design was large-scale: 427 learners were randomly assigned to three conditions—diagramming, diagramming plus self-assessment, or a neutral control task.

The result is clear and at the same time surprisingly sober: both diagramming conditions led to significantly higher metacognitive accuracy—both relative (How well do my per-text judgments match my later test results?) and absolute (How large is my over-/underestimation error?)—compared with the control. However, no difference emerged between diagramming alone and diagramming plus self-assessment. Apparently, many learners already evaluate their diagrams informally as they go. Moreover, when collected, the self-assessments were more precise than pure comprehension judgments and strongly correlated with them. The effects were at the monitoring level. Test performance itself did not improve significantly in this study—an indication that the primary benefit here lies in better-calibrated judgments and thus better learning decisions.

What this means for practice:

After reading a subject text, it’s worth having a brief, consistent diagramming slot of a few minutes. Learners sketch the central concepts and relationships, then take a quick look at their sketch and answer for themselves the simple question, “What am I still missing—and where exactly?” This mini-routine is usually enough to noticeably raise metacognitive accuracy. Additional, detailed self-assessment instructions are optional. What’s crucial is that the diagram drives the decision about what to restudy: instead of rereading everything, learners target the passages that show gaps in the picture—a solid time saver.

Why this works is well explained by theory: diagrams force explication. Anyone who has to draw relationships generates diagnostic cues that are much more tightly linked to genuine understanding than diffuse impressions such as reading fluency or topic familiarity. This pulls metacognitive judgments closer to reality—and where judgments are more precise, restudy decisions become more accurate. This is the lever for more durable learning: better calibration leads to better priorities.

Source

Pijeira-Díaz, H. J., van de Pol, J., Channa, F., & de Bruin, A. (2023). Scaffolding self-regulated learning from causal-relations texts: Diagramming and self-assessment to improve metacomprehension accuracy? Metacognition and Learning, 18(3), 631–658. https://doi.org/10.1007/s11409-023-09343-0