Linking Testing Activities with Success in Agile Development of Physical Products

Batliner, Martin; Boës, Stefan; Heck, Johannes; Meboldt, Mirko

doi:10.1016/j.procir.2022.05.228

Cited by 3 publications

(4 citation statements)

References 20 publications

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“…Moreover, our study aligns with Batliner et al (2022) who identified early and ongoing investment of time in testing as a predictor for project success. While Batliner et al (2022) focused specifically on testing, our study explored the overall solution effort and its association with product quality.…”

Section: Discussionsupporting

confidence: 90%

“…Our findings support the importance of a prompt transition from problem formulation to solution generation, facilitating iterative design processes involving idea generation, testing and evaluation (Darke 1979; Lloyd & Scott 1995; Ball & Christensen 2019; Batliner et al 2022). Ball & Christensen (2019) argue that teams should move quickly into the solution space, as speculative solution ideas aid in formulating design problems.…”

Section: Discussionsupporting

confidence: 70%

See 1 more Smart Citation

Learning by doing? The relationship between effort, learning effect and product quality during hackathons of novice teams

Martins Pacheco,

Geisler,

Bajramovic

et al. 2024

Des. Sci.

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Design education prepares novice designers to solve complex and challenging problems requiring diverse skill sets and an interdisciplinary approach. Hackathons, for example, offer a hands-on, collaborative learning approach in a limited time frame to gain practical experience and develop problem-solving skills quickly. They enable collaboration, prototyping and testing among interdisciplinary teams. Typically, hackathons strongly focus on the solution, assuming that this will support learning. However, building the best product and achieving a strong learning effect may not be related. This paper presents the results of an empirical study that examines the relationship between product quality, learning effect and effort spent in an academic 2-week hackathon. Thirty teams identified user problems in this course and developed hardware and mechatronic products. This study collected the following data: (1) effort spent during the hackathon through task tracking, (2) learning effect through self-assessment by the participants and (3) product quality after the hackathon by an external jury. The study found that the team effort spent has a statistically significant but moderate correlation with product quality. The correlation between product quality and learning effect is statistically insignificant, suggesting that for this setting, there is no relevant association.

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Section: Discussionsupporting

confidence: 90%

Section: Discussionsupporting

confidence: 70%

Learning by doing? The relationship between effort, learning effect and product quality during hackathons of novice teams

Martins Pacheco,

Geisler,

Bajramovic

et al. 2024

Des. Sci.

View full text Add to dashboard Cite

show abstract

“…A non-influencing pattern was the amount of iterations, which seemingly contradicts results of Batliner et al (2022), who indicate that more testing activities correlate with success in design. However, this might also result from the different study setups, as participants in the study of Batliner et al (2022) were able to do many more product development activities in their semester project compared to the focus on testing in this study.…”

Section: Discussionmentioning

confidence: 58%

“…the stages of the prototypes (Barhoush et al, 2019). Study environments that address the comparability through many similar tasks, which are conducted in parallel project based learning environments (Batliner et al, 2022), however the time consuming aspects remain (Grauberger et al, 2019). The problem is, that insights regarding testing activities to gain specific design knowledge are difficult to research, as testing activities often take place over a long period and are therefore difficult to capture.…”

Section: Introductionmentioning

confidence: 99%

Identifying Successful Approaches During Testing Activities in Engineering Design

et al. 2023

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Testing activities to gain specific design knowledge play an essential role in engineering design, when a structure needs to be developed, for which knowledge from analytical models or documentation is missing. As research into these testing activities is difficult, few insights into successful approaches exist.In this contribution, we investigate testing activities to gain specific design knowledge through a laboratory task, where 10 engineering students optimize a system using a web-based process chain including rapid prototyping and testing. Design and testing data are acquired from 110 prototypes in 3 hours. A differentiation of performance is conducted and approaches of high- and low-performers are investigated to identify patterns.Based on these patterns, hypotheses, and metrics indicating successful and non-successful approaches are derived as basis for development of metrics for testing to gain specific design knowledge. A successful approach was overstep the limit, where participants accept destruction of their system to identify boundaries. An unsuccessful approach was the change of many parameters in later tests. These hypotheses and their metrics can then be used in development and validation of support for testing.

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Classification and Evaluation Framework of Automated testing tools for agile software: Technical Review

Mosleh,

Ameen Al-Khulaidi,

Gumaei

et al. 2024

2024 4th International Conference on Emerging Smart Technologies and Applications (eSmarTA)

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Linking Testing Activities with Success in Agile Development of Physical Products

Cited by 3 publications

References 20 publications

Learning by doing? The relationship between effort, learning effect and product quality during hackathons of novice teams

Learning by doing? The relationship between effort, learning effect and product quality during hackathons of novice teams

Identifying Successful Approaches During Testing Activities in Engineering Design

Classification and Evaluation Framework of Automated testing tools for agile software: Technical Review

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