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Orthographies vary in complexity (the number of multi-letter grapheme-phoneme rules describing print-to-speech regularities) and unpredictability (the number of words which cannot be read correctly, even with at-ceiling knowledge of the rules). These are two constructs which underlie orthographic depth in European orthographies. It is unclear how each of these constructs affects reading acquisition. We aim to address this question, using an artificial orthography learning paradigm. In two pilot experiments, we manipulated the consistency of symbol-to-sound mappings: in one of the inconsistent conditions, vowel pronunciation was predictable from the subsequent letter, and in the other inconsistent condition, vowel pronunciation was unpredictable from the context. The results indicate that words with inconsistent mappings are more difficult to learn than words with consistent mappings only, though it is not clear whether there are any differences depending on whether the inconsistency is due to complexity or unpredictability. Adding an unpredictable component into an orthography might hamper the learning of complex rules. In a third, pre-registered study, we aim to follow up on the loose ends from the two pilot experiments with a well-controlled, larger experiment.