A Method to Semi-Automatically Identify and Measure Unmet Requirements in Learner-Created State Machine Diagrams

Takuma Kimura, Shinpei Ogata, Erina Makihara, Kozo Okano
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Abstract

The UML (Unified Modeling Language) state machine diagram notation is challenging for learners to understand because of its complexity. Therefore, educators assign modeling assignments to learners to assess their understanding. If learners do not fully understand the notation, they may make errors in their diagrams. To improve learners’ understanding, educators provide the learners with explanations of what and why the diagrams unmet the requirements of the modeling assignments. However, the variety of content and layout in Learner-created diagrams can be challenging for educators to accurately and quickly identify the unmet requirements in each diagram. Therefore, this study proposes a method to semi-automatically identify and measure unmet requirements in Learner-created diagrams. The proposed method was applied to 38 state machine diagrams created by learners to evaluate its effectiveness. Consequently, the proposed method gave reasonable results for 37 out of 38 diagrams (approximately 97%).
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学习者创建的状态机图中半自动识别和度量未满足需求的方法
由于UML(统一建模语言)状态机图的复杂性,学习者很难理解它。因此,教育者给学习者布置建模作业来评估他们的理解。如果学习者不能完全理解符号,他们可能会在他们的图表中犯错误。为了提高学习者的理解,教育者会向学习者解释哪些图表不符合建模作业的要求,以及为什么不符合。然而,学习者创建的图表中内容和布局的多样性对教育者来说是一个挑战,他们很难准确、快速地识别每个图表中未满足的需求。因此,本研究提出了一种在学习者创建的图中半自动识别和测量未满足需求的方法。将该方法应用于学习者创建的38个状态机图,以评估其有效性。因此,该方法对38张图中的37张给出了合理的结果(约97%)。
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