Process models are structured representations of workflows in an organization that provide a powerful tool for facilitating communication and process redesign or improvement. Model comprehension is ...challenging for beginning modelers. This study scrutinizes the effect of token-animated process models on novice modelers’ comprehension in an experiment with 229 participants. The study is grounded in the theory of distributed cognition as well as other cognition theories. The results confirm the significant impact of token-animated models on comprehension. Several individual characteristics were found to be important as well. Given that the animations were well accepted, token animation can be considered a resourceful technique for pragmatic and educational purposes.
It is commonly accepted that simulation contributes to a better learning quality while also promoting successful transfer of the skills to real-world environments. However, the practical use of ...simulation is hampered by the difficulty of interpreting simulation results. This paper demonstrates the learning benefits in conceptual modeling of business requirements when using feedback-enabled simulation. The effects of feedback-enabled simulation on learning outcomes of novice learners were observed by means of experimental empirical studies. Three studies were conducted in the context of two master-level courses from two different study programs spanning two academic years. The findings show a significant improvement in students' conceptual model understanding and validation capabilities when using feedback-enabled simulation.
•We developed a feedback-enabled simulation environment for conceptual modeling of business requirements.•We designed experiments to test its effectiveness on learning outcomes of students.•We then replicated the experiment three times with different groups and cohorts.•The results confirmed the effectiveness of feedback-enabled simulation over traditional methods of teaching.
As many software development teams have started to adopt agile methods, a vast amount of valuable experiences have been reported on in both academic and industrial knowledge bases. This information ...has been used through various approaches to guide and help practitioners finding suitable practices for their software development projects. Nevertheless, not many of these approaches could gather the available experiences to make them systematically reusable and help practitioners understanding agile practices in depth. To the best of our knowledge, only one ontology has been created to solve this problem; some limitations related to its quality and usability make it nevertheless unqualified to serve the intended purpose. The aim of this paper is to build an expert system (i.e. an evidence-based tool) to ease agile practices adoption by efficiently and effectively providing information on them. Firstly, we improve the concepts and relationships in the aforementioned ontology and theoretically validate it using a large data-set of agile practices adoption experiences collected through a Systematic Literature Review (SLR). Secondly, we develop a supporting tool having a friendly Graphical User Interface (GUI) allowing to use the ontology as a concrete agile practice knowledge provider. Finally, we empirically validate the enhanced ontology and evaluate the supporting tool using a survey with agile experts. Our supporting tool can help practitioners to decide what practice to adopt, how to adopt it, how to solve practical issues, etc. The ontology and the tool materialize our contribution to the field of systematic agile practices adoption.
•Successful agile practice adoption requires an in depth understanding of its content.•Existing reports on agile practice adoption experiences are essentially unexploitable.•An ontology is used as an efficient solution to recycle practices adoption experience.•A corpus-based approach and a survey are used for validating the ontology.•An expert system supports practitioners querying knowledge on practice adoption.
A Product Configuration System (PCS) is a software system that facilitates the sales and production processes of defined customizable products. PCS are specific software developments in the sense ...that they are knowledge-intensive so that they require models to formalize the complex knowledge inherent to product configurations also leading to dependencies between software functionalities. Scrum is a widely used agile method, but its training has been the subject of little research. Model-driven development implicitly impacts the way development is conducted especially when adopting an agile method as Scrum. This paper, as exploratory research, evaluates Scrum training for PCS projects through a qualitative case study. The goal is to identify the elements that should be focused on within Scrum background training. This research first studies and assesses the training experiences at the case company. Then, it reports on respondents’ opinions about the strengths and challenges of applying Scrum in the mentioned context. The latter is based on multiple data sources: documentation, interviews, participant observations, and workshops. Issues in applicability lead to enhanced training support for learning how to (i) combine Scrum with the model-driven approach inherently required within PCS development, (ii) manage time and effort estimation on the basis of accurate artifacts and (iii) access key employees possessing domain or specific technical knowledge indispensable for pursuing the development.
In this study, we report on the students' evaluation of a self-constructed constructivist e-learning environment for statistics, the compendium platform (CP). The system was built to endorse deeper ...learning with the incorporation of statistical reproducibility and peer review practices. The deployment of the CP, with interactive workshops and group assignments, immerses students in a novel blended e-learning experience. Based on the Delone and McLean framework, we tested an explanatory success model with a sample of 607 business students, collected during three consecutive academic years. The results indicate that system quality and teacher support are the most important success factors, directly or indirectly contributing to a higher degree of relative advantage and satisfaction, both of which strongly determine continuous intention to use. The findings ascertain the usability and acceptance of the CP and promote a more radical constructivist approach to the teaching of statistics, but also other subjects.
•The work extends previous research on simulation benefits for model comprehension.•Our previous work shows positive effects for comprehension of structural aspects.•The extension includes assessment ...of the effectiveness for behavioral aspects.•Findings show significant positive effect on understanding system behavior.•The findings suggest that simulation is preferable over manual model inspection.
UML diagrams are the de facto standard for analysing, communicating and designing software systems, as well as automated code generation. However there is a certain degree of difficulty in understanding a system represented by means of UML diagrams.
Our previous research demonstrates a significant improvement in understanding the structural aspects of a system represented as a UML class diagram when using a feedback-inclusive prototype of a model. This paper extends our previous work with an empirical validation study for the effectiveness of the feedback-inclusive rapid prototyping (FIRP) method, on the comprehension of system dynamics represented as multiple interacting UML statecharts. Because models often combine structural and behavioural views that are highly intertwined, we additionally evaluate the effectiveness of the proposed method with respect to comprehension of the between-view consistency.
The FIRP environment was built following the principles of Design Science Research in Information Systems. This study targets the empirical validation of the effectiveness of the proposed technique using an experimental study method. Two experiments were conducted with the participation of 65 final-year master students in the context of different modelling courses from different study programs at KU Leuven using two two-group factorial experimental designs. The effectiveness of the FIRP method was measured by comparing students’ performance between the cycles with and without the use of the method, using the understandability (comprehension test results) as the dependent variable and the use of FIRP as the independent variable. Effects from unknown variables were neutralized by means of randomized group compositions. The effectiveness of FIRP was additionally assessed with respect to personal characteristics (age, gender, previous knowledge, self-efficacy) and user acceptance (perceived ease of use, perceived utility, preference, satisfaction).
The findings reveal a significant positive impact of the use of the prototyping technique on students’ comprehension of system dynamics represented as multiple interacting statecharts.
The findings provide empirical support for the advantage of the use of FIRP over manual inspection of interacting statecharts. The findings also suggest that the method is suitable for training system's analysis and modelling skills when UML statecharts are involved.
Beyond managing student dropout, higher education stakeholders need decision support to consistently influence the student learning process to keep students motivated, engaged, and successful. At the ...course level, the combination of predictive analytics and self-regulation theory can help instructors determine the best study advice and allow learners to better self-regulate and determine how they want to learn. The best performing techniques are often black-box models that favor performance over interpretability and are heavily influenced by course contexts. In this study, we argue that explainable AI has the potential not only to uncover the reasons behind model decisions, but also to reveal their stability across contexts, effectively bridging the gap between predictive and explanatory learning analytics (LA). In contributing to decision support systems research, this study (1) leverages traditional techniques, such as concept drift and performance drift, to investigate the stability of student success prediction models over time; (2) uses Shapley Additive explanations in a novel way to explore the stability of extracted feature importance rankings generated for these models; (3) generates new insights that emerge from stable features across cohorts, enabling teachers to determine study advice. We believe this study makes a strong contribution to education research at large and expands the field of LA by augmenting the interpretability and explainability of prediction algorithms and ensuring their applicability in changing contexts.
•SHAP exhibits two-fold utility in checking model stability and aiding study advice.•Success prediction models must be updated to ensure stable performance.•Changing learning contexts lead to distributional drift of LA indicators.•As the learning context changes, the importance of learning indicators shifts.•General activity and regularity indicators show the highest stability.
Setting up a Digital Transformation (DT) strategy is often done ad-hoc without guidance. Supporting frameworks can help. This paper aims to build and validate a conceptual model made of a generic set ...of most prominent DT strategic objectives. This representation is built out of a systematic literature review and refined/validated through expert opinions. Organisations can use it as reference to build their custom DT strategic objective set. An instantiation is shown on a Belgian hospital. The representation can be integrated into an existing IT development process for evaluating the alignment of new software with respect to the organisation's DT strategic objectives.
Pollution cost control is key to solve pollution problem. The paper takes pollution control cost of pollution control contract between management authority and pollutant discharge enterprise as ...research object, considers pollution control quality level, pollution control quality inspection and pollution control cost model, and establishes pollution control cost model of management authority and pollutant discharge enterprise, including rational constraints of pollutant discharge enterprise. And it analyzes principal-agent relationship between the two under condition of asymmetric information, and un-observability of pollution control level is shown as hiding information of sewage enterprises. In essence, it is problem of adverse selection in principal-agent. Pollution control cost of management is objective function. The first order condition of pollution control cost of sewage enterprise is transformed into state space equation, and optimal control of problem is solved by using maximum principle. In particular, management authority, as principal, uses pollution control provisions to reward, punish and encourage pollutant discharge enterprises as agents.
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