Search Results (2)

This paper presents a hybrid qualitative–quantitative framework for assessing the technical feasibility and system readiness of emerging multimodal mobility concepts, with specific application to the Pods4Rail project. The methodology integrates expert-based Technology Readiness Level (TRL) assessment with a probabilistic System Readiness Level (SRL) estimation that incorporates uncertainties in both TRLs and Integration Readiness Levels (IRLs). The qualitative component uses expert judgment and visual heat maps to identify subsystem-specific maturity gaps, particularly in automation, digitalization, and sustainability. The quantitative component explicitly separates three methodological layers often treated implicitly in prior research: (i) the probabilistic model representing uncertainties in TRL and IRL, (ii) the uncertainty-propagation problem linking these variables to system-level readiness, and (iii) the Monte Carlo algorithm employed to solve this problem. This structure enables the derivation of SRL distributions that reflect uncertainty more realistically than deterministic approaches, allowing statistical analysis of different characteristics of these distributions and exploratory sensitivity analysis. Results show that the Pods4Rail system is positioned between SRL 1 and SRL 2, corresponding to concept refinement and technology development stages. While hardware-related subsystems such as the Transport Unit and Rail Carrier Unit exhibit relatively higher maturity, planning, logistics, and operational management functionalities remain at early development stages. By combining interpretative insight with statistical rigor, the proposed framework offers a transparent and reproducible approach to early-phase readiness assessment. Its transferability makes it suitable for other innovative mobility systems facing similar challenges of incomplete information, uncertain integration pathways, and high conceptual complexity. Full article

Contemporary research indicates that student creativity is crucial to the success of arts education. Self-regulated learning has become one of educational psychology’s most critical research areas. However, there is limited research on creativity in arts education in self-regulated learning. Therefore, this study aims to define the creativity characteristics that determine the quality of students’ work. This study implemented a creative competition in painting and composition for first-year undergraduates. It was conducted at a Chinese university with the participation of 178 first-year students aged 18 to 26. It evaluated the characteristics of creativity during the three main phases of the task: planning, execution, and completion. We investigated the subject by employing semi-open questionnaires (n = 178) and using the content analysis method and quantitative analysis. According to the competition results, the students with the highest scores in flow, inspiration, and idea generation in the performance phase had the best quality work. In the forethought phase, analogical thinking and idea generation worked best for most students, while in the performance phase, flow sense, idea generation, and idea manipulation worked best. Data on creativity characteristics at different work phases and final quality might adequately guide and organize educational procedures. These findings can serve as a theoretical foundation for quantifying the creativity phase in self-regulated learning and offer arts educators a reference for creativity instruction. Full article