Feedback-Enabled MDA-Prototyping Effects on Modeling Knowledge

Abstract

This paper describes the effects of a feedback-enabled MDA prototyping tool on the validation cycle for conceptual models. We observe the effects of such prototyping method on learning outcomes of novice modelers. The impact is assessed based on the quality dimensions introduced by Conceptual Modeling Quality Framework (CMQF), more specifically with respect to semantic quality being affected by modeling knowledge. The current work proposes an extension to the techniques introduced in previous work in particular experimenting with the prototyping tool by novice modelers. A positive impact has been observed on the learning achievements of novice modelers improving both modeling and language knowledge.

Process-mining enabled feedback: “Tell me what I did wrong” vs. “tell me how to do it right”

“…if an execution of a business event fails a user receives a textual and graphical explanation prompting the parts of a model that cause the error. Empirical studies show that this simulation feedback can significantly improve the learning outcomes (Sedrakyan & Snoeck, 2012, 2013a, 2014aSedrakyan, Snoeck, & Poelmans, 2014). Finally, the modeling tool has been expanded with an experimental logging functionality allowing to record data on modeling and prototyping (also referred to as simulation) activities.…”

“…Since it would not be possible to actually track a human mind in our study, the concept of modeling effort was operationalized as the number of modeling activities as approximation of modeler's mental effort. Likewise, since it would not be possible to track the actual process of model validation in our studies, we made use of the simulation activities motivated by the fact that 1. simulation serves as an instrument for model validation and 2. the simulation feature used for this study was empirically proven to have a significant positive effect on novices' capabilities for validating the semantic conformance between a model and requirements statements (Sedrakyan & Snoeck, 2012, 2013aSedrakyan, Snoeck, & Poelmans, 2014). The concept of validation effort is therefore operationalized as the number of simulation activities throughout the modeling process.…”

Assessing the effectiveness of feedback enabled simulation in teaching conceptual modeling

“…The simulation feature used in this study is the improved version of the tool used in the course of several years of teaching. In our previous papers we already discussed a set of shortcomings and subsequent improvements (Sedrakyan & Snoeck, 2012, 2013a for conceptual model simulation. We will therefore dismiss the details related to the simulation environment as well as its implementation 3 .…”

“…The goal of the method is twofold: 1) providing assistance in validating semantic aspects while also gaining deeply understood knowledge from hands-on experience 2) allowing to detect design errors that result from misinterpreted use of modeling language constructs. The work proposes an extension to the techniques previously presented by ( Haesen & Snoeck, 2004;Sedrakyan & Snoeck, 2012, 2013a, 2013bSnoeck, Haesen, Buelens, De Backer, & Monsieur, 2007;Snoeck, Michiels, & Dedene, 2003). The methodology uses the UML as modelling language, but underneath it relies on the concepts of MERODE 1 , an Enterprise Information Systems engineering methodology developed at the university of Leuven, which follows the Model-Driven Architecture and Engineering approach.…”

Lightweight Semantic Prototyper for Conceptual Modeling

“…MERODE is based on the framework that overcomes the shortcomings of UML (being technically too complex for conceptual modelling and not precise enough for rapid prototyping). The framework is based on three kinds of model views (restricted class diagrams, interaction model, state charts) and uses a "consistency by construction" approach that completes missing model elements automatically thus allowing simple transformations [5,6,7]. A generated prototype supports the execution of business events by also providing textual and graphical feedback when and why the execution of a triggered business event is refused, thus making the links between a prototype and its design explicit.…”