Improving Model-Driven Engineering Through Understanding Human Factors

Core Concepts

Incorporating human factors, such as diversity, collaboration, and cognitive aspects, is crucial for the success and adoption of Model-Driven Engineering (MDE) in practice.

Abstract

The content discusses the importance of considering human factors in Model-Driven Engineering (MDE) and proposes a research agenda to address this gap. Key insights include: Factors of Modeller Experience (MX): Identified technical, non-technical, and inherent factors that influence the modelling experience, such as language complexity, tool usability, and modeller motivation. Proposed to validate the relevance of these factors through empirical studies and map them to different modelling workflows. Collaboration and MDE: Discussed how models can be used to support communication and collaboration between different roles in software projects. Identified key characteristics of models that can hinder or benefit communication, such as formality and acceptance. Proposed a research agenda to investigate why models are not effectively used for communication and to derive guidelines for enhancing models to facilitate cross-role collaboration. Diversity and Inclusion in MDE: Identified diversity dimensions, such as age, background, and cognitive diversity, that may affect modelling practices and tool design. Proposed research directions, including universal design for MDE, awareness of biases in modelling tools and languages, and the effects of diversity on the modelling process. Highlighted the need to develop inclusive teaching practices and new tools to address the diverse needs of MDE stakeholders. Modelling Human Factors: Discussed the potential of using models to represent and analyse human factors, such as values, in software engineering. Proposed a systematic approach to incorporate human values into the software development process. Teaching Human-aware MDE: Identified pedagogical challenges in teaching MDE, such as the lack of confidence in modelling skills and the need for structured thinking. Suggested strategies to address these challenges, including providing constructive feedback, teaching structured thinking, and fostering an appreciation for the value of modelling. The content emphasizes the need for the MDE community to be more aware of and supportive of human factors to improve the success and adoption of MDE in practice.

Stats

"Models aim to enable practitioners to communicate about software designs, make software understandable, or make software easier to write through domain-specific modelling languages." "Several recent studies indicate that human factors play a role in the success of MDE." "Modelling is not an objective process, but various technical and non-technical factors affect the individual modelling experience." "Various different contexts or workflows need to be considered in MDE research to allow for more precise conclusions to be drawn." "Education in MDE needs to mirror research efforts in the sense that educators (1) need to understand the effect of human factors on modeller (and student) experience, and (2) need to convey the importance of these human factors to the student population, so that knowledge transfer to practice takes place." "Human factors are increasingly important in SE research and practice. Therefore, the community needs to apply their MDE-related knowledge and experience to models of human factors in SE."

Quotes

"Models aim to enable practitioners to communicate about software designs, make software understandable, or make software easier to write through domain-specific modelling languages." "Several recent studies indicate that human factors play a role in the success of MDE."

Key Insights Distilled From

Human Factors in Model-Driven Engineering: Future Research Goals and Initiatives for MDE

by Gris... at arxiv.org 04-30-2024

https://arxiv.org/pdf/2404.18682.pdf

Deeper Inquiries

How can the MDE community effectively collaborate with other disciplines, such as psychology and human-computer interaction, to better understand and integrate human factors into MDE research and practice?

To effectively collaborate with other disciplines, such as psychology and human-computer interaction, the MDE community can take several steps: Interdisciplinary Workshops and Seminars: Organize workshops and seminars that bring together experts from different disciplines to discuss and exchange ideas on how human factors can be integrated into MDE research. This can help in fostering collaboration and sharing of knowledge. Joint Research Projects: Collaborate on joint research projects that focus on the intersection of MDE and human factors. By working together on specific research topics, experts from different disciplines can leverage their expertise to gain a deeper understanding of how human factors impact MDE. Cross-Disciplinary Training Programs: Develop training programs that incorporate aspects of psychology and human-computer interaction into MDE education. This can help MDE practitioners gain a better understanding of human behavior and cognition, leading to more user-centric design practices. Shared Resources and Tools: Create shared resources and tools that facilitate collaboration between disciplines. This could include shared databases, modeling frameworks, or visualization tools that enable researchers to work together on projects that involve human factors. Publication in Interdisciplinary Journals: Encourage researchers to publish their work in interdisciplinary journals that cater to both MDE and human factors. This can help in disseminating research findings to a wider audience and promoting cross-disciplinary collaboration. By actively engaging with experts from psychology and human-computer interaction, the MDE community can enhance its understanding of human factors and incorporate this knowledge into MDE research and practice effectively.

How can the MDE community effectively collaborate with other disciplines, such as psychology and human-computer interaction, to better understand and integrate human factors into MDE research and practice?

To effectively collaborate with other disciplines, such as psychology and human-computer interaction, the MDE community can take several steps: Interdisciplinary Workshops and Seminars: Organize workshops and seminars that bring together experts from different disciplines to discuss and exchange ideas on how human factors can be integrated into MDE research. This can help in fostering collaboration and sharing of knowledge. Joint Research Projects: Collaborate on joint research projects that focus on the intersection of MDE and human factors. By working together on specific research topics, experts from different disciplines can leverage their expertise to gain a deeper understanding of how human factors impact MDE. Cross-Disciplinary Training Programs: Develop training programs that incorporate aspects of psychology and human-computer interaction into MDE education. This can help MDE practitioners gain a better understanding of human behavior and cognition, leading to more user-centric design practices. Shared Resources and Tools: Create shared resources and tools that facilitate collaboration between disciplines. This could include shared databases, modeling frameworks, or visualization tools that enable researchers to work together on projects that involve human factors. Publication in Interdisciplinary Journals: Encourage researchers to publish their work in interdisciplinary journals that cater to both MDE and human factors. This can help in disseminating research findings to a wider audience and promoting cross-disciplinary collaboration. By actively engaging with experts from psychology and human-computer interaction, the MDE community can enhance its understanding of human factors and incorporate this knowledge into MDE research and practice effectively.

How can the MDE community effectively collaborate with other disciplines, such as psychology and human-computer interaction, to better understand and integrate human factors into MDE research and practice?

To effectively collaborate with other disciplines, such as psychology and human-computer interaction, the MDE community can take several steps: Interdisciplinary Workshops and Seminars: Organize workshops and seminars that bring together experts from different disciplines to discuss and exchange ideas on how human factors can be integrated into MDE research. This can help in fostering collaboration and sharing of knowledge. Joint Research Projects: Collaborate on joint research projects that focus on the intersection of MDE and human factors. By working together on specific research topics, experts from different disciplines can leverage their expertise to gain a deeper understanding of how human factors impact MDE. Cross-Disciplinary Training Programs: Develop training programs that incorporate aspects of psychology and human-computer interaction into MDE education. This can help MDE practitioners gain a better understanding of human behavior and cognition, leading to more user-centric design practices. Shared Resources and Tools: Create shared resources and tools that facilitate collaboration between disciplines. This could include shared databases, modeling frameworks, or visualization tools that enable researchers to work together on projects that involve human factors. Publication in Interdisciplinary Journals: Encourage researchers to publish their work in interdisciplinary journals that cater to both MDE and human factors. This can help in disseminating research findings to a wider audience and promoting cross-disciplinary collaboration. By actively engaging with experts from psychology and human-computer interaction, the MDE community can enhance its understanding of human factors and incorporate this knowledge into MDE research and practice effectively.