Doing pedagogical research in engineering

This is a book

Agile Processes in Software Engineering and Extreme Programming

This open access book constitutes the proceedings of the 21st International Conference on Agile Software Development, XP 2020, which was planned to be held during June 8-12, 2020, at the IT University of Copenhagen, Denmark. However, due to the COVID-19 pandemic the conference was postponed until an undetermined date. XP is the premier agile software development conference combining research and practice. It is a hybrid forum where agile researchers, academics, practitioners, thought leaders, coaches, and trainers get together to present and discuss their most recent innovations, research results, experiences, concerns, challenges, and trends. Following this history, for both researchers and seasoned practitioners XP 2020 provided an informal environment to network, share, and discover trends in Agile for the next 20 years. The 14 full and 2 short papers presented in this volume were carefully reviewed and selected from 37 submissions. They were organized in topical sections named: agile adoption; agile practices; large-scale agile; the business of agile; and agile and testing

Proceedings of the GPEA Polytechnic Summit 2022: Session Papers

Welcome to GPEA PS 2022 Each year the Polytechnic Summit assembles leaders, influencers and contributors who shape the future of polytechnic education. The Polytechnic Summit provides a forum to enable opportunities for collaboration and partnerships and for participants to focus on innovation in curriculum and pedagogy, to share best practices in active and applied learning, and discuss practice-based research to enhance student learning. This year a view on the aspects of applied research will be added. How to conduct research in a teaching first environment and make use of this. Which characteristics of applied research are important to be used in teaching and vice versa?The Summit will – once again - also provide an opportunity to examine the challenges and opportunities presented by COVID-19 and will offer us all an opportunity to explore the ways in which we can collaborate more effectively using our new-found virtual engagement skills and prepare for a hybrid future. PS2022 Themes: Design (Programmes, Curriculum, Organisation);Practice-Based Learning;Applied Research; Employability and Graduate Skills; Internationalisation, Global Teaching & Collaboration and Sustainability Theme

Rethinking Productivity in Software Engineering

Get the most out of this foundational reference and improve the productivity of your software teams. This open access book collects the wisdom of the 2017 "Dagstuhl" seminar on productivity in software engineering, a meeting of community leaders, who came together with the goal of rethinking traditional definitions and measures of productivity. The results of their work, Rethinking Productivity in Software Engineering, includes chapters covering definitions and core concepts related to productivity, guidelines for measuring productivity in specific contexts, best practices and pitfalls, and theories and open questions on productivity. You'll benefit from the many short chapters, each offering a focused discussion on one aspect of productivity in software engineering. Readers in many fields and industries will benefit from their collected work. Developers wanting to improve their personal productivity, will learn effective strategies for overcoming common issues that interfere with progress. Organizations thinking about building internal programs for measuring productivity of programmers and teams will learn best practices from industry and researchers in measuring productivity. And researchers can leverage the conceptual frameworks and rich body of literature in the book to effectively pursue new research directions. What You'll Learn Review the definitions and dimensions of software productivity See how time management is having the opposite of the intended effect Develop valuable dashboards Understand the impact of sensors on productivity Avoid software development waste Work with human-centered methods to measure productivity Look at the intersection of neuroscience and productivity Manage interruptions and context-switching Who Book Is For Industry developers and those responsible for seminar-style courses that include a segment on software developer productivity. Chapters are written for a generalist audience, without excessive use of technical terminology. ; Collects the wisdom of software engineering thought leaders in a form digestible for any developer Shares hard-won best practices and pitfalls to avoid An up to date look at current practices in software engineering productivit

A quality oriented approach towards information requirement determination in equivocal situations

Analysis of users’ needs is one of the key determinants of any system’s success and the foundation of requirement determination process. Yet because of the complexity of human’s needs, the process of requirement determination for developing systems to meet human’s needs is often ad hoc and poorly understood (Browne & Ramesh, 2002). Poor execution of Information Requirement Determination (IRD) will almost guarantee the failure of the final project, as a result a significant portion of requirement determination activities are dedicated to determining users’ information level requirements (Hickey & Davis, 2004) which in this study is referred to as IRD. There is no commonly accepted IRD method for all situations and therefore IRD methods are leaning toward specialised methods, designed for specific contexts and situations (Siau & Rossi, 2011). However a significant proportion of IRD literature is focused on organisational context while there are other complex contexts which require researchers’ attention. One such situations for which no specialised IRD method could be found in the literature is the context of “Individual Decision Making in Equivocal Situations (IDMES)” which in this study is defined as: Contexts in which an individual should make important decisions in complex and equivocal situations he/she is not an expert in. Examples of IDMES could be identified in healthcare where a patient who is not a trained healthcare professional has to choose between several available treatments for a serious health problem. Complexity of decisions a patient needs to make is comparable to the complex decisions that a manager must make in an organisation. The differentiation is that patients are not healthcare specialists but managers are specialists of the area in which they make decisions. In such situations providing higher amount of information to users may actually increase the uncertainty they face (e.g. overloading a patient with information). Therefore, in developing information systems for supporting decision making in such contexts, extra attention should be paid to determining other characteristics of users’ information needs, namely: quality and source. To establish a theoretical foundation for the IRD method required in this context, a conceptual model labelled as Quality Requirement Determination (QRD) model has been generated in this study. To develop the QRD model, two concepts of Information Quality (IQ) and Information Seeking Behaviour (ISB) have been leveraged. Although both IQ and ISB are mature topics, their applications in IRD methods are not very well studied (Gharib & Giorgini, 2015; Savolainen, 2007, 2008; Sonnenwald, Wildemuth, & Harmon, 2001). To evaluate the QRD model, it has been applied to the case of parenting children with autism. This case has been selected because it meets all the characteristics of IDMES, namely because: 1) autism cause and cure are unknown and therefore selecting from the array of available interventions “is a nightmare for desperate parents” (Crawford, 2013, p. 53). 2) Parents must individually make decisions in a context in which they are not trained experts even though over time they develop a certain level of practical experience. Seventeen parents were interviewed about their information seeking behaviours when they needed to decide on interventions necessary for a specific problem. The results of the data analysis confirm the existence of the relationships between perceived information needs, source preference behaviour and quality requirements proposed in the QRD model. The information requirements which arose from the case of parenting children with autism is embodied in the QRD presentation matrix. It leverages a nine cell matrix with each cell representing a cognitive role played by the information sources in the users’ information horizon1 . The QRD presentation matrix along with the QRD model and associated data collection and analysis techniques are called QRD method. To evaluate the usability of determined information by the QRD method, results of an instrumental case study were presented to a group of IS practitioners. The selected IS practitioners have been chosen from variety of expertise involved in developing information systems to reflect the maximum variety of opinions. The interview results demonstrated the value of the QRD method for a number of key practical activities in the IRD process, namely: context study, problem definition, quality requirement analysis, quality implementation, designing information flow and user interface design

A quality oriented approach towards information requirement determination in equivocal situations

Analysis of users’ needs is one of the key determinants of any system’s success and the foundation of requirement determination process. Yet because of the complexity of human’s needs, the process of requirement determination for developing systems to meet human’s needs is often ad hoc and poorly understood (Browne & Ramesh, 2002). Poor execution of Information Requirement Determination (IRD) will almost guarantee the failure of the final project, as a result a significant portion of requirement determination activities are dedicated to determining users’ information level requirements (Hickey & Davis, 2004) which in this study is referred to as IRD. There is no commonly accepted IRD method for all situations and therefore IRD methods are leaning toward specialised methods, designed for specific contexts and situations (Siau & Rossi, 2011). However a significant proportion of IRD literature is focused on organisational context while there are other complex contexts which require researchers’ attention. One such situations for which no specialised IRD method could be found in the literature is the context of “Individual Decision Making in Equivocal Situations (IDMES)” which in this study is defined as: Contexts in which an individual should make important decisions in complex and equivocal situations he/she is not an expert in. Examples of IDMES could be identified in healthcare where a patient who is not a trained healthcare professional has to choose between several available treatments for a serious health problem. Complexity of decisions a patient needs to make is comparable to the complex decisions that a manager must make in an organisation. The differentiation is that patients are not healthcare specialists but managers are specialists of the area in which they make decisions. In such situations providing higher amount of information to users may actually increase the uncertainty they face (e.g. overloading a patient with information). Therefore, in developing information systems for supporting decision making in such contexts, extra attention should be paid to determining other characteristics of users’ information needs, namely: quality and source. To establish a theoretical foundation for the IRD method required in this context, a conceptual model labelled as Quality Requirement Determination (QRD) model has been generated in this study. To develop the QRD model, two concepts of Information Quality (IQ) and Information Seeking Behaviour (ISB) have been leveraged. Although both IQ and ISB are mature topics, their applications in IRD methods are not very well studied (Gharib & Giorgini, 2015; Savolainen, 2007, 2008; Sonnenwald, Wildemuth, & Harmon, 2001). To evaluate the QRD model, it has been applied to the case of parenting children with autism. This case has been selected because it meets all the characteristics of IDMES, namely because: 1) autism cause and cure are unknown and therefore selecting from the array of available interventions “is a nightmare for desperate parents” (Crawford, 2013, p. 53). 2) Parents must individually make decisions in a context in which they are not trained experts even though over time they develop a certain level of practical experience. Seventeen parents were interviewed about their information seeking behaviours when they needed to decide on interventions necessary for a specific problem. The results of the data analysis confirm the existence of the relationships between perceived information needs, source preference behaviour and quality requirements proposed in the QRD model. The information requirements which arose from the case of parenting children with autism is embodied in the QRD presentation matrix. It leverages a nine cell matrix with each cell representing a cognitive role played by the information sources in the users’ information horizon1 . The QRD presentation matrix along with the QRD model and associated data collection and analysis techniques are called QRD method. To evaluate the usability of determined information by the QRD method, results of an instrumental case study were presented to a group of IS practitioners. The selected IS practitioners have been chosen from variety of expertise involved in developing information systems to reflect the maximum variety of opinions. The interview results demonstrated the value of the QRD method for a number of key practical activities in the IRD process, namely: context study, problem definition, quality requirement analysis, quality implementation, designing information flow and user interface design

The Nature of the Relationships between Social Networks, Interpersonal Trust, Management Support, and Knowledge Sharing

Purpose – Past research has shown that, by implementing knowledge sharing, an organisation can maintain its long-term competitive advantage. Hence, this research will explore the nature of the relationships between social networks, interpersonal trust, management support, and knowledge sharing. Methodology/approach – In order to achieve the above purpose, semi-structured interviews were used to gather qualitative data. Interviewee participants included top and middle managers and frontline employees. The total number of participants included in the research was 25, equally representing five companies. The core business of all the companies was large-scale manufacturing. A grounded theory approach was used to analyse the data, augmented by the computer-assisted qualitative data analysis software, Nvivo. Findings – The results reveal that social networks facilitate knowledge sharing in diverse ways. These ways are: the use of multiple communication styles, brainstorming and problem solving, learning and teaching, training, employee rotation, and consultation. In addition, the data from the interviews suggests that, through various factors, the level of interpersonal trust, influences the extent to which employees are willing to share knowledge. These factors are organisational, relational, and individual factors. Furthermore, this study shows that both middle and top managers can play significant roles in facilitating knowledge sharing between employees. These roles are: encouragement of participation in decision-making, provision of recognition, breaking down of barriers, building up of teams, providing training or assigning others to do training, encouragement of training, communication, learning, putting knowledge into practice in the form of processes, and movement of employees. Research contributions – Six models were developed from the qualitative analysis of the field data. The brainstorming and problem solving model identifies various steps for brainstorming and problem solving which influence social networks and knowledge sharing. The model of learning and teaching explains how social networks can be built based on the receivers’ levels of knowledge, namely, the novice, competent, expert, and proficient levels. The model of factors influencing social networks and knowledge sharing illustrates various factors. These are: using multiple communication strategies, brainstorming and problem solving, learning and teaching, training, employee rotation, and consultation. The model of factors influencing interpersonal trust describes three factors for achieving such trust: organisational, relational, and individual factors. This model also elaborates on three factors that negatively influence interpersonal trust. These are division between departments, team conflict, and a sense of vulnerability. The model of the role of management teams in encouraging participation in decision-making elaborates on levels of decision-making among employees and the way in which knowledge flows between top and middle management and frontline employees. The integrative model deciphers the relationships between social networks, interpersonal trust, management support, openness, and knowledge sharing. In addition, the relationships between each area of emphasis and knowledge sharing are included in the model. Based on this model, a survey questionnaire was developed. These models provide new insights into the relationships between social networks, interpersonal trust, management support, and knowledge sharing. By applying these models to appropriate field situations, both practitioners and academics may be able to improve current practices relating to how knowledge is shared and evolves within organisations

Evaluating the Effectiveness of Trust Signals in the eHealth Sector: A Multi-Stakeholder Approach

The Internet gives patients the opportunity to be better informed, have ownership over their data, and, therefore, be empowered in the medical decision-making process. All of these new forms of patient empowerment through eHealth, however, require the patients’ trust in online service. Existing literature provides a solid foundation regarding the development of trust in social encounters. What is more, the understanding of trust related to more general online services, such as e-commerce is advanced, too. Regarding eHealth in particular, however, there are substantial gaps in the literature. What is more, all existing studies have one pitfall in common. None of them investigates trust as a reciprocal, evolving system that is based on recurring interactions between trustee and truster. Studies either focus on the individual view of the trustee or the truster but fail to analyse the potential dynamics of a trust signal and its evolution. This led me to research questions that aim to identify trust-evoking factors specific to eHealth, on the one hand, and develop an understanding of the evolution and sustainability of communication between trustee and truster. I applied a mixed-methods approach in order to answer my research questions. This allowed me to use qualitative methods to explore a variety of trust antecedents that are unique to eHealth, develop hypotheses, and then test the derived hypotheses through a quantitative study. One surprising insight of this study is that the risk perception of the overall service offer can determine the level of trust in a service even before entering the website. Risk perception proved to be a more crucial indicator of perceived trustworthiness than presence of trust signals on the website. This allows the conclusion that both researchers and policy makers should differentiate between high-risk and low-risk eHealth services instead of approaching all services under the unifying umbrella of eHealth. Another key finding is that users judge the trustworthiness of eHealth websites depending on their “fit”. For eHealth providers that means that in order to increase trust in their service they need to mimic the offline experience as much as possible

Rethinking Productivity in Software Engineering

Get the most out of this foundational reference and improve the productivity of your software teams. This open access book collects the wisdom of the 2017 "Dagstuhl" seminar on productivity in software engineering, a meeting of community leaders, who came together with the goal of rethinking traditional definitions and measures of productivity. The results of their work, Rethinking Productivity in Software Engineering, includes chapters covering definitions and core concepts related to productivity, guidelines for measuring productivity in specific contexts, best practices and pitfalls, and theories and open questions on productivity. You'll benefit from the many short chapters, each offering a focused discussion on one aspect of productivity in software engineering. Readers in many fields and industries will benefit from their collected work. Developers wanting to improve their personal productivity, will learn effective strategies for overcoming common issues that interfere with progress. Organizations thinking about building internal programs for measuring productivity of programmers and teams will learn best practices from industry and researchers in measuring productivity. And researchers can leverage the conceptual frameworks and rich body of literature in the book to effectively pursue new research directions. What You'll Learn Review the definitions and dimensions of software productivity See how time management is having the opposite of the intended effect Develop valuable dashboards Understand the impact of sensors on productivity Avoid software development waste Work with human-centered methods to measure productivity Look at the intersection of neuroscience and productivity Manage interruptions and context-switching Who Book Is For Industry developers and those responsible for seminar-style courses that include a segment on software developer productivity. Chapters are written for a generalist audience, without excessive use of technical terminology. ; Collects the wisdom of software engineering thought leaders in a form digestible for any developer Shares hard-won best practices and pitfalls to avoid An up to date look at current practices in software engineering productivit

From Bugs to Decision Support – Leveraging Historical Issue Reports in Software Evolution

Software developers in large projects work in complex information landscapes and staying on top of all relevant software artifacts is an acknowledged challenge. As software systems often evolve over many years, a large number of issue reports is typically managed during the lifetime of a system, representing the units of work needed for its improvement, e.g., defects to fix, requested features, or missing documentation. Efficient management of incoming issue reports requires the successful navigation of the information landscape of a project. In this thesis, we address two tasks involved in issue management: Issue Assignment (IA) and Change Impact Analysis (CIA). IA is the early task of allocating an issue report to a development team, and CIA is the subsequent activity of identifying how source code changes affect the existing software artifacts. While IA is fundamental in all large software projects, CIA is particularly important to safety-critical development. Our solution approach, grounded on surveys of industry practice as well as scientific literature, is to support navigation by combining information retrieval and machine learning into Recommendation Systems for Software Engineering (RSSE). While the sheer number of incoming issue reports might challenge the overview of a human developer, our techniques instead benefit from the availability of ever-growing training data. We leverage the volume of issue reports to develop accurate decision support for software evolution. We evaluate our proposals both by deploying an RSSE in two development teams, and by simulation scenarios, i.e., we assess the correctness of the RSSEs' output when replaying the historical inflow of issue reports. In total, more than 60,000 historical issue reports are involved in our studies, originating from the evolution of five proprietary systems for two companies. Our results show that RSSEs for both IA and CIA can help developers navigate large software projects, in terms of locating development teams and software artifacts. Finally, we discuss how to support the transfer of our results to industry, focusing on addressing the context dependency of our tool support by systematically tuning parameters to a specific operational setting