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Despite their wide adoption, industrial business process models often display a wide range of quality issues. While significant efforts have been undertaken to better understand factors impacting process model comprehension, only few studies focused on their creation. This paper presents a set of fixation patterns that have been derived from a modeling session with 120 participants during which the modelers' behavior was recorded in terms of eye movements as well as interactions with the modeling environment. The identified patterns can be used in the future as basis for automatic real-time detection of the activities a user is performing, an essential building block for the development of a neuro-adaptive environment for process modeling that is able to adapt to the task at hand and the user's individual processing capacities.
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Stored only when both papers are in the corpus — 28 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.