Making trigger-action rules more comprehensible: Investigating which linguistic clues effectively guide non-programmers - Andrao, Margherita; Treccani, Barbara; Zancanaro, Massimo (International journal of human-computer studies, 2025)
Trigger-Action Programming is a commonly used paradigm in End-User Development interfaces, allowing users without programming experience to create new automation systems. Even if considered easy to grasp, this approach poses some challenges: non-programmers often confuse events (instantaneous occurrences) and states (prolonged occurrences), leading to critical errors in the definition of triggers. Although past research has already questioned the effectiveness of the typical if-then structure, there is a limited exploration of which specific linguistic cues might help or hinder users from distinguishing between events and states. Our study, involving 85 non-programmers, examines a broader pool of linguistic aspects, investigating (i) preferences for conjunctions and verbs when describing events and states and (ii) which conjunctions help users accurately differentiate these occurrences. Our results indicate that while participants tended to prefer temporally specific language, such as ”when” for events and ”while” for states, some of these conjunctions, like ”when”, may not support users in accurately identifying and differentiating events from states, similar to the generic ”if”. These findings underscore the role of specific language on non-programmers’ comprehension and mental representations of triggers. Designing interfaces with more easily graspable linguistic cues and mapping them at the system level may help guide non-programmer users in correctly structuring trigger-action rules. [Display omitted] •Linguistic confusion is a key challenge for easy to learn End-User Development.•Study non-programmers’ choices for verbs and conjunctions in trigger-action rules.•Preference for temporally specific conjunctions but verb form is also crucial.•If and When do not help non-programmers understand triggers’ temporal features.•Implications for the design of compositional and LLM-based interfaces are discussed.