TY - GEN
T1 - Improvement of EduBPMN Transformation Rules from an Empirical Validation
AU - Díaz, Eduardo
AU - Panach, Jose Ignacio
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - EduBPMN method allows the generation of graphical components from a BPMN model complemented with the UML class diagram. This article proposes the improvement of five transformation rules of the EduBPMN method from an experiment developed in 2019, with the improved transformation rules an experiment was developed that was executed by 31 subjects where the results of two metrics were obtained, (i) the correctness of the rules, where the subjects had to map BPMN to graphic components intuitively through an experimental problem, had a positive result (87.50%), (ii) the satisfaction of the generalization of the rules, had a positive result in its Perceived Ease of Use (93%), Perceived Usefulness (95%), and Intention to Use (96%). This article provides positive results on the five new improved rules of the EduBPMN method, which is used to map BPMN to graphical components.
AB - EduBPMN method allows the generation of graphical components from a BPMN model complemented with the UML class diagram. This article proposes the improvement of five transformation rules of the EduBPMN method from an experiment developed in 2019, with the improved transformation rules an experiment was developed that was executed by 31 subjects where the results of two metrics were obtained, (i) the correctness of the rules, where the subjects had to map BPMN to graphic components intuitively through an experimental problem, had a positive result (87.50%), (ii) the satisfaction of the generalization of the rules, had a positive result in its Perceived Ease of Use (93%), Perceived Usefulness (95%), and Intention to Use (96%). This article provides positive results on the five new improved rules of the EduBPMN method, which is used to map BPMN to graphical components.
KW - BPMN
KW - Experiment
KW - Graphic components
KW - Transformation rules
UR - https://www.scopus.com/pages/publications/85199603397
U2 - 10.1007/978-3-031-63616-5_23
DO - 10.1007/978-3-031-63616-5_23
M3 - Contribución a la conferencia
AN - SCOPUS:85199603397
SN - 9783031636158
T3 - Communications in Computer and Information Science
SP - 299
EP - 315
BT - Information Management and Big Data - 10th Annual International Conference, SIMBig 2023, Proceedings
A2 - Lossio-Ventura, Juan Antonio
A2 - Ceh-Varela, Eduardo
A2 - Vargas-Solar, Genoveva
A2 - Marcacini, Ricardo
A2 - Tadonki, Claude
A2 - Calvo, Hiram
A2 - Alatrista-Salas, Hugo
PB - Springer Science and Business Media Deutschland GmbH
T2 - 10th Annual International Conference on Information Management and Big Data, SIMBig 2023
Y2 - 13 December 2023 through 15 December 2023
ER -