Exploring how users engage with hybrid process artifacts based on declarative process models: a behavioral analysis based on eye-tracking and think-aloud

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Exploring how users engage with hybrid process artifacts based on declarative process models : a behavioral analysis based on eye-tracking and think-aloud. / Abbad Andaloussi, Amine; Zerbato, Francesca; Burattin, Andrea; Slaats, Tijs; Hildebrandt, Thomas T.; Weber, Barbara.

In: Software and Systems Modeling, Vol. 20, 2021, p. 1437–1464.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Abbad Andaloussi, A, Zerbato, F, Burattin, A, Slaats, T, Hildebrandt, TT & Weber, B 2021, 'Exploring how users engage with hybrid process artifacts based on declarative process models: a behavioral analysis based on eye-tracking and think-aloud', Software and Systems Modeling, vol. 20, pp. 1437–1464. https://doi.org/10.1007/s10270-020-00811-8

APA

Abbad Andaloussi, A., Zerbato, F., Burattin, A., Slaats, T., Hildebrandt, T. T., & Weber, B. (2021). Exploring how users engage with hybrid process artifacts based on declarative process models: a behavioral analysis based on eye-tracking and think-aloud. Software and Systems Modeling, 20, 1437–1464. https://doi.org/10.1007/s10270-020-00811-8

Vancouver

Abbad Andaloussi A, Zerbato F, Burattin A, Slaats T, Hildebrandt TT, Weber B. Exploring how users engage with hybrid process artifacts based on declarative process models: a behavioral analysis based on eye-tracking and think-aloud. Software and Systems Modeling. 2021;20:1437–1464. https://doi.org/10.1007/s10270-020-00811-8

Author

Abbad Andaloussi, Amine ; Zerbato, Francesca ; Burattin, Andrea ; Slaats, Tijs ; Hildebrandt, Thomas T. ; Weber, Barbara. / Exploring how users engage with hybrid process artifacts based on declarative process models : a behavioral analysis based on eye-tracking and think-aloud. In: Software and Systems Modeling. 2021 ; Vol. 20. pp. 1437–1464.

Bibtex

@article{a025357cb919475fb3d4ccc8d188e04a,
title = "Exploring how users engage with hybrid process artifacts based on declarative process models: a behavioral analysis based on eye-tracking and think-aloud",
abstract = "Process design artifacts have been increasingly used to guide the modeling of business processes. To support users in designing and understanding process models, different process artifacts have been combined in several ways leading to the emergence of the so-called “hybrid process artifacts”. While many hybrid artifacts have been proposed in the literature, little is known about how they can actually support users in practice. To address this gap, this work investigates the way users engage with hybrid process artifacts during comprehension tasks. In particular, we focus on a hybrid representation of DCR Graphs (DCR-HR) combining a process model, textual annotations and an interactive simulation. Following a qualitative approach, we conduct a multi-granular analysis exploiting process mining, eye-tracking techniques, and verbal data analysis to scrutinize the reading patterns and the strategies adopted by users when being confronted with DCR-HR. The findings of the coarse-grained analysis provide important insights about the behavior of domain experts and IT specialists and show how user{\textquoteright}s background and task type change the use of hybrid process artifacts. As for the fine-grained analysis, user{\textquoteright}s behavior was classified into goal-directed and exploratory and different strategies of using the interactive simulation were identified. In addition, a progressive switch from an exploratory behavior to a goal-directed behavior was observed. These insights pave the way for an improved development of hybrid process artifacts and delineate several directions for future work.",
keywords = "Behavioral analysis, DCR graphs, Eye-tracking, Hybrid process artifacts, Process models, Think-aloud",
author = "Amine Abbad Andaloussi and Francesca Zerbato and Andrea Burattin and Tijs Slaats and Hildebrandt, {Thomas T.} and Barbara Weber",
year = "2021",
doi = "10.1007/s10270-020-00811-8",
language = "English",
volume = "20",
pages = "1437–1464",
journal = "Software and Systems Modeling",
issn = "1619-1366",
publisher = "Springer",

}

RIS

TY - JOUR

T1 - Exploring how users engage with hybrid process artifacts based on declarative process models

T2 - a behavioral analysis based on eye-tracking and think-aloud

AU - Abbad Andaloussi, Amine

AU - Zerbato, Francesca

AU - Burattin, Andrea

AU - Slaats, Tijs

AU - Hildebrandt, Thomas T.

AU - Weber, Barbara

PY - 2021

Y1 - 2021

N2 - Process design artifacts have been increasingly used to guide the modeling of business processes. To support users in designing and understanding process models, different process artifacts have been combined in several ways leading to the emergence of the so-called “hybrid process artifacts”. While many hybrid artifacts have been proposed in the literature, little is known about how they can actually support users in practice. To address this gap, this work investigates the way users engage with hybrid process artifacts during comprehension tasks. In particular, we focus on a hybrid representation of DCR Graphs (DCR-HR) combining a process model, textual annotations and an interactive simulation. Following a qualitative approach, we conduct a multi-granular analysis exploiting process mining, eye-tracking techniques, and verbal data analysis to scrutinize the reading patterns and the strategies adopted by users when being confronted with DCR-HR. The findings of the coarse-grained analysis provide important insights about the behavior of domain experts and IT specialists and show how user’s background and task type change the use of hybrid process artifacts. As for the fine-grained analysis, user’s behavior was classified into goal-directed and exploratory and different strategies of using the interactive simulation were identified. In addition, a progressive switch from an exploratory behavior to a goal-directed behavior was observed. These insights pave the way for an improved development of hybrid process artifacts and delineate several directions for future work.

AB - Process design artifacts have been increasingly used to guide the modeling of business processes. To support users in designing and understanding process models, different process artifacts have been combined in several ways leading to the emergence of the so-called “hybrid process artifacts”. While many hybrid artifacts have been proposed in the literature, little is known about how they can actually support users in practice. To address this gap, this work investigates the way users engage with hybrid process artifacts during comprehension tasks. In particular, we focus on a hybrid representation of DCR Graphs (DCR-HR) combining a process model, textual annotations and an interactive simulation. Following a qualitative approach, we conduct a multi-granular analysis exploiting process mining, eye-tracking techniques, and verbal data analysis to scrutinize the reading patterns and the strategies adopted by users when being confronted with DCR-HR. The findings of the coarse-grained analysis provide important insights about the behavior of domain experts and IT specialists and show how user’s background and task type change the use of hybrid process artifacts. As for the fine-grained analysis, user’s behavior was classified into goal-directed and exploratory and different strategies of using the interactive simulation were identified. In addition, a progressive switch from an exploratory behavior to a goal-directed behavior was observed. These insights pave the way for an improved development of hybrid process artifacts and delineate several directions for future work.

KW - Behavioral analysis

KW - DCR graphs

KW - Eye-tracking

KW - Hybrid process artifacts

KW - Process models

KW - Think-aloud

U2 - 10.1007/s10270-020-00811-8

DO - 10.1007/s10270-020-00811-8

M3 - Journal article

AN - SCOPUS:85087518307

VL - 20

SP - 1437

EP - 1464

JO - Software and Systems Modeling

JF - Software and Systems Modeling

SN - 1619-1366

ER -

ID: 271620741