Design Artifacts Research Articles

Approach to Formalizing Software Projects for Solving Design Automation and Project Management Tasks

GitHub and GitLab contain many project repositories. Each repository contains many design artifacts and specific project management features. Developers can automate the processes of design and project management with the approach proposed in this paper. We described the knowledge base model and diagnostic analytics method for the solving of design automation and project management tasks. This paper also presents examples of use cases for applying the proposed approach.

What are the pedagogical characteristics of elementary emergency e-learning? Crosschecking learning activities’ analysis with perspectives of teachers, students and parents

This research examined the pedagogical characteristics of emergency online learning in elementary schools. The study adds to the educational technology literature, exploring the opportunities and challenges for students by triangulating analysis of learning activities with perspectives of teachers, students, and parents. Thematic analysis of the interviews with 22 teachers, 21 students, and 10 parents revealed 913 statements grouped into categories and subcategories. Furthermore, 93 learning activities were analyzed based on the recent e-CSAMR framework that combines the SAMR and collaboration models. Participants reported development of student independence, responsibility, and learning autonomy, while adversely mentioned feelings of disconnection and lack of social communication. However, analysis of learning activities reflected mostly basic rather than advanced techno-pedagogical levels of the original SAMR model and revealed that they did not sufficiently incorporate collaborative activities or design of learning artifacts. Theoretical implications supported the e-CSAMR framework and identified optimal components for emergency learning within the framework. The results highlight the need to integrate collaborative learning into distance online learning and suggest that appropriate support and training can transform challenges into pedagogical opportunities.

Making sustainability transitions in collaborative spaces of making: Exploring opportunities and limitations in Turin

In recent years, makerspaces and FabLabs have proliferated in urban settings. Such venues provide shared workspace, (digital fabrication) tools, and knowledge, lowering the barriers for citizens to engage in DIY (Do It Yourself), and the design and building of artefacts. In recent years, scholars have hailed the return of small-scale manufacturing, independent craft production and making practices to cities. This shift is by some seen as pre-figuring a more progressive and inclusive discourse on urban development, one that is attentive to local communities’ productive needs and opportunities, and that moves us away from the hitherto dominant consumption-centred paradigm of the creative city (Carr & Gibson, 2016; Grodach, 2017; Grodach et al., 2017). Drawing on empirical data collected in Turin in 2021, the paper investigates how and under what conditions community-led spaces centred on making may hold potential as sites of urban vitalism, reconfiguring production and consumption in more democratic, inclusive and sustainable ways. The findings consider a number of emerging tensions, relating to questions of regulating open access, managing community participation, and negotiating project-based versus changing habitual practices.

Do Simple Analytical Models Capture Complex Fractured Bedrock Hydraulics? Oscillatory Flow Tests Suggest Not.

Fractured sedimentary bedrock aquifers represent complex flow systems that may contain fast, fracture-dominated flow paths and slower, porous media-dominated flow paths. Thus, characterizing the dynamics of flow and transport through these aquifers remains a fundamental hydrogeologic challenge. Recent studies have demonstrated the utility of a novel hydraulic testing approach, oscillatory flow testing, in field settings to characterize single bedrock fractures embedded in low-porosity sedimentary bedrock. These studies employed an idealized analytical model assuming Darcian flow through a nondeforming, constant-aperture, nonleaky fracture for data interpretation, and reported period-dependent effective fracture flow parameters. Here, we present the application of oscillatory flow testing across a range of frequencies and inter-well spacings on a fracture embedded in poorly cemented sedimentary bedrock with considerable primary porosity at the Field Site for Research in Fractured Sedimentary Rock. Consistent with previous studies, we show an apparent period-dependence in returned flow parameters, with hydraulic diffusivity decreasing and storativity increasing with increasing oscillation period, when assuming an idealized fracture conceptual model. We present simple analyses that examine non-Darcian flow and borehole storage effects as potential test design artifacts and a simple analytical model that examines fluid leakage to the surrounding host rock as a potential hydraulic mechanism that might contribute to the period-dependent flow parameters. These analyses represent a range of conceptual assumptions about fracture behavior during hydraulic testing, none of which account for the measured responses during oscillatory flow testing, leading us to argue that other hydraulic processes (e.g., aperture heterogeneity and/or fracture hydromechanics) are necessary to accurately represent pressure propagation through fractured sedimentary bedrock.

A design concept of big data analytics model for managers in hospitality industries.

The hospitality and tourism sector has long played a significant role in Australia's economy, especially in regional areas. Due to the onslaught of COVID-19, numerous businesses have experienced lockdowns, restrictions, and closures due to the fact that people's activity in restaurants, shopping centers, and recreational destinations was restricted, and many other places went into hibernation. After about 2years since the outbreak, businesses in this sector are gradually starting to reopen and revitalize themselves, but in order to have better decision support about the future of this sector, thus being able to plan, businesses are suffering from an effective analytics solution due to the lack of broken data trends. Starting from fresh day-to-day real-time big data, the study aims to develop a new data analytics model, adopting the design science research methodology, which can provide invaluable options and techniques to make prediction easier from immediate past datasets. This study introduces an innovative design artifact as a big data solution for hospitality managers to utilize analytics for predictive strategic decision-making in post-COVID situation. The artifact can also be generalized for other sectors with tailoring aspects which are subject to further studies. The proposed artifact is then compared with other design artifacts related to big data solutions where it outperforms them in terms of comprehensiveness. The proposed artifact also shows promises for primarily available UGC in managers' decision support aids.

Developing Special Product Development Models

This development research aims to develop a customized product development model with a content structure: Model Name, Framework, and Procedure (explanation of steps in the Framework). This Development Research uses a Design-Based Research Model with the steps: 1. Identification of Problems and Needs, 2. Identification of Goals, 3. Artifact Design and Development, 4. Artifact Test, 5. Artifact Test Evaluation, 6. Artifact Communication. Data were collected through interviews and questionnaires and were processed using descriptive statistics. Development Research succeeded in developing a custom product development model (Customized) which was later named the Collaborative Model, along with a Framework and Explanation of Research and Development Procedures to be carried out. Collaborative Model: Customized Product Development Model was developed only from the identification of problems and needs of a special product development model for the academic community of one university in Malang. It is suggested to the next researcher to develop a development model for specific products that begins with identifying the problems and needs of academics from many tertiary institutions. Collaborative Model: Customized Product Development Model is used by experimenters to conduct research and development. The pilots stated that the model was very effective. Collaborative Model: Customized Product Development Model will be very useful, considering that there is no similar model in Indonesia that is easy to understand and speaks Indonesian.

Metaverse‐Based Learning Through Children's School Space Design

AbstractMetaverse is understood with technological terms such as augmented reality, lifelogging, mirrored worlds, and virtual worlds, and using a metaverse platform is considered an emerging form of learning. Yet, its pedagogical features, such as self‐learning, collaborative learning, and learning‐by‐doing, are identical to those of online learning. In this study, we argue that metaverse‐based learning refers to a new reality learners create by assuming that the existence of reality is different in the metaverse. We extracted six educational values in epistemological and ontological senses, reviewing the four realities of the metaverse, including virtual reality, augmented reality, mixed reality, and extended reality, which is a way to avoid technological determinists'; approach to education. Based on the values – bottom‐up, collaboration, authorship, ownership, interconnectivity, and community, primary school children's (year 5 & 6) groups (n = 20) redesigned 20 assigned school spaces such as classroom teacher office, science room, and music room on their chosen metaverse platforms. Throughout the thematic analysis of design artifacts, activity scenarios, and reflection & presentation, we discovered four themes: collaborative learning with co‐ownership and co‐authorship; being interconnected with all living and non‐living things; co‐participants with different roles; and transdisciplinary research‐driven learning, which is used to articulate a framework for metaverse‐based learning, which is different from online learning.

Towards a Value Co-Creation Process in Collaborative Environments for TVET Education

The appearance of the COVID disruption has proved the need for rapid innovations in education, with new value proposition(s) able to capture the new activities involving value co-creation in the education service systems. This paper introduces a conceptual framework for skills building in collaborative TVET online communities that integrates the Collaborative Knowledge Sharing Environment (CKSEnv), an ontology-based collaborative development of knowledge-intensive services, as a possible main driver for value co-creation amongst actors in the after-pandemic TVET education. CKSEnv’s usability and usefulness in achieving its goals is evaluated. Quantitative and qualitative data collected through interviews have revealed respondents’ interest in topics such as the sustainability, usefulness, usability, value co-creation, and technical functionality of the proposed development. Both the utility and simplicity proved to have the most significant impact on CKSEnv adoption and usage. A new service design artifact is created, the smart service model canvas in the TVET online communities, to explain the new value co-creation process, which is able to fill gaps in describing the role of ICT in supporting the TVET training cycle. This research may ground further explorations related to the development of TVET online communities, while the CKSEnv is still in the evaluation stage. The practical implications of this study express the need for new value co-creation processes with specific activities that use technology-driven innovations, able to establish such newly created value, through smart educational services.

Generating multiple conceptual models from behavior-driven development scenarios

Researchers have proposed that generating conceptual models automatically from user stories might be useful for agile software development. It is, however, unclear from the state-of-the-art what a consistent and complementary set of models to generate is, how these models can be generated such that relationships and dependencies in a set of related user stories are unveiled, and why these models are useful in agile software development projects. In this paper, we address these questions through a Design Science research study. First, we define four stylized versions of Unified Modeling Language (UML) diagrams (i.e., use case diagram, class diagram, activity diagram, state machine diagram) that will be the target of the model generation. Although these stylized UML diagrams have a reduced abstract syntax, they offer different perspectives on the software system in focus with potential usefulness for requirements and software engineering. Second, we develop an automated model generation approach based on different design artifacts including a Natural Language Processing (NLP) tool that implements our approach. Key to our solution is the use of the Behavior-Driven Development (BDD) scenario template to document user stories. Using an example set of BDD scenarios as source of the model generation, we demonstrate the feasibility of our approach via the NLP tool that implements our approach. Third, we conduct an empirical study with experts in agile software development involving the researcher-guided interactive use of our tool to explore the use of the generated models. This study shows the perceived usefulness of the models that our tool can generate and identifies different uses and benefits of the models for requirements analysis, system design, software implementation, and testing in projects that employ agile methods.

Examining User Heterogeneity in Digital Experiments

Digital experiments are routinely used to test the value of a treatment relative to a status quo control setting — for instance, a new search relevance algorithm for a website or a new results layout for a mobile app. As digital experiments have become increasingly pervasive in organizations and a wide variety of research areas, their growth has prompted a new set of challenges for experimentation platforms. One challenge is that experiments often focus on the average treatment effect (ATE) without explicitly considering differences across major sub-groups — heterogeneous treatment effect (HTE). This is especially problematic because ATEs have decreased in many organizations as the more obvious benefits have already been realized. However, questions abound regarding the pervasiveness of user HTEs and how best to detect them. We propose a framework for detecting and analyzing user HTEs in digital experiments. Our framework combines an array of user characteristics with double machine learning. Analysis of 27 real-world experiments spanning 1.76 billion sessions and simulated data demonstrates the effectiveness of our detection method relative to existing techniques. We also find that transaction, demographic, engagement, satisfaction, and lifecycle characteristics exhibit statistically significant HTEs in 10% to 20% of our real-world experiments, underscoring the importance of considering user heterogeneity when analyzing experiment results, otherwise personalized features and experiences cannot happen, thus reducing effectiveness. In terms of the number of experiments and user sessions, we are not aware of any study that has examined user HTEs at this scale. Our findings have important implications for information retrieval, user modeling, platforms, and digital experience contexts, in which online experiments are often used to evaluate the effectiveness of design artifacts.

Artificial Intelligence-Driven Talent Management System: Exploring the Risks and Options for Constructing a Theoretical Foundation

AI (Artificial intelligence) has the potential to improve strategies to talent management by implementing advanced automated systems for workforce management. AI can make this improvement a reality. The objective of this study is to discover the new requirements for generating a new AI-oriented artefact so that the issues pertaining to talent management are effectively addressed. The design artefact is an intelligent Human Resource Management (HRM) automation solution for talent career management primarily based on a talent intelligent module. Improving connections between professional assessment and planning features is the key goal of this initiative. Utilising a design science methodology we investigate the use of organised machine learning approaches. This technique is the key component of a complete AI solution framework that would be further informed through a suggested moderation of technology-organisation-environment (TOE) theory with the theory of diffusion of innovation (DOI). This framework was devised in order solve AI-related problems. Aside from the automated components available in talent management solutions, this study will make recommendations for practical approaches researchers may follow to fulfil a company’s specific requirements for talent growth.

Healing fabulations: a dialogic methodology for digital codesign in health research

ABSTRACT Recent research has highlighted the importance of responding to trauma and promoting healing when working with participants in sensitive contexts. This article presents a new methodology for design research on health topics which combines principles from narrative medicine (health storytelling) with codesign. In this collaborative, dialogic approach, participatory action research cycles of storytelling are used to inform a process of digital codesign, positioning participants as peer researchers. The resulting prototypes (termed healing fabulations) are a new type of design artefact which captures each participant’s lived experience while also extending it into a speculative future. Discussion of the methodology shows how the approach protects participant wellbeing during research on their health experiences, addresses common criticisms of digital design research, and explores the importance of visual metaphor and aesthetic in design for health. The article concludes with a discussion of the methodology’s replicability and use in future research.

Reconsidering Representation in College Design Curricula

The Future of Design Education working group on representation addressed the roles of data, maps, models, and interfaces as a continuum from representation to action. The article traces historical ideas of representation grounded by a linguistic paradigm to more recent approaches based on performance, embodiment, and sensory modalities other than vision. Discussions include the use of representations in the design process. Designers are able to use traditional forms of representation in the design of artifacts, such as sketches. These forms of representation are not sufficient for the design of systems. System design requires models that allow stakeholders to negotiate their view of a situation and design teams to iterate how things might work. Core ideas in the working group recommendations address issues of, substitution, formal rules, motivation, context dependency, materiality, provisionality, latency, performance, externalization, facilitation and negotiation, mediation, and measurement and evaluation. Discussions address the socio-political implications of representation and the expanding role of computing and data that call for a systems view.

Principles to Facilitate Social Inclusion for Design-Oriented Research

We develop principles that facilitate socially inclusive design-oriented research with marginalized groups. Building on the recognition that the research process must be informed by theoretical perspectives about social inclusion, our effort begins with an empirical investigation of a multiyear research project that designed several IT-based solutions for people with intellectual and developmental disabilities. We treat the efforts to design each solution as a “case,” capture primary data from multiple sources, and analyze it in light of three facets of social inclusion drawn from prior work: self-determination, belongingness, and social capital. The findings are interpreted to derive five principles for a socially inclusive design-oriented research process: (1) respecting multiperspective problem ownership and integrated solution design, (2) surfacing emic contributions to guide artifact design, (3) leveraging the support network to shape artifact design and refine research conduct, (4) customizing design-evaluate cycles with inclusive practices, and (5) pursuing authenticity in research collaborations. We elaborate each principle with connections to different facets of social inclusion, guidelines suggested by our empirical investigation, and a mapping against contemporary design-oriented research approaches. The five principles suggest key directions to facilitate a socially inclusive design-oriented research process when working with marginalized groups. The paper concludes with a discussion of implications for IS scholars, and pointers for using design-oriented approaches for greater social inclusion of marginalized populations.

Listen to the noise – Demonstrating an end to end multi-platform and multilingual sentiment analysis approach

This paper demonstrates a holistic approach for conducting multi-platform and multilingual sentiment analysis of a main stream football club in the United Arab Emirates. The paper reports first iterations of the research project which anticipates to build an automated sentiment analysis system for football clubs to detect and prevent a potential social media crisis at an early stage. The article illustrates a schematic of how state of the art machine learning algorithms, methods and techniques can be put together to provide a basis for automated data collection, classification, sentiment analysis and visual reporting. The article also presents that the time-consuming and costly process of human text labelling can be effectively replaced by lexicon-based sentiment analysis. This paper reports the complete process from data collection to visual reports to discuss challenges and opportunities associated with design and development of such artefacts.

Computer Game Scenario Representation: A Systematic Mapping Study

Background: Game scenario is an important factor for achieving player enjoyment; consisting a key business success factor. Additionally, the production of early design artifacts is crucial for the success of the development process. However, representing scenarios is a non-trivial task: (a) multiple aspects of the game need to be visualized; and (b) there is a plethora of representation approaches, out of which the game designer needs to select from. Aim: The goal of this work is to provide a panorama of the current scenario representation approaches, to aid game engineers in selecting the most fitting scenario representation approach and understand the existing designing options. Method: We have performed a Systematic Mapping Study, using 4 digital libraries, since the main goal can be achieved through study classification. By following an established search and filtering process, we have identified 717 articles, and analyzed in detail 95. Results: Diagrams are the most common generic approach to represent scenario; Game story is the most usual part of the scenario being represented; Characters are the most common component; and Transitions are the most usual connectors. Conclusion: Researchers may get useful information for empirically investigating several game engineering aspects; whereas game engineers can efficiently select the most fitting approach.

A guide for concurrent TMS-fMRI to investigate functional brain networks.

Transcranial Magnetic Stimulation (TMS) allows for the direct activation of neurons in the human neocortex and has proven to be fundamental for causal hypothesis testing in cognitive neuroscience. By administering TMS concurrently with functional Magnetic Resonance Imaging (fMRI), the effect of cortical TMS on activity in distant cortical and subcortical structures can be quantified by varying the levels of TMS output intensity. However, TMS generates significant fluctuations in the fMRI time series, and their complex interaction warrants caution before interpreting findings. We present the methodological challenges of concurrent TMS-fMRI and a guide to minimize induced artifacts in experimental design and post-processing. Our study targeted two frontal-striatal circuits: primary motor cortex (M1) projections to the putamen and lateral prefrontal cortex (PFC) projections to the caudate in healthy human participants. We found that TMS parametrically increased the BOLD signal in the targeted region and subcortical projections as a function of stimulation intensity. Together, this work provides practical steps to overcome common challenges with concurrent TMS-fMRI and demonstrates how TMS-fMRI can be used to investigate functional brain networks.

Generative prototypes to promote participation in the collaborative design of wearable health technologies

The potential of design artefacts as generative tools is well documented in the early stages of the design process. Yet, how prototypes continue to act generatively in the later stages is less well understood. This paper shares observations from two projects spanning the entire design process, from conceptual ideas to mass-produced objects. Through quotes and observations documenting participants interacting with prototypes, we illustrate the importance of designed physical artefacts as tools to promote expansive conversations with end-users. We find that generative prototypes foster empathy; support decision-making and communication across disciplines; allow participants to enact use and explore user experience within the early stages of a design process and provide permission to imagine possible futures. These findings encourage design practitioners to think about using high-fidelity generative prototypes throughout the design process as a powerful tool for design thinking, collaboration, and co-creation that embrace speculation and playful creativity.

Visual Representation of Indonesian Culture in Character Design HololiveID Virtual Youtuber

The purpose of this study is to identify visual representations of Indonesian culture that are applied to the virtual character design of Hololive Indonesia (HololiveID) Virtual Youtuber (vTuber). To obtain data, qualitative research methods will be performed as well as observation. This cultural representation can analyze using narrative-visual analysis and semiotics. Through visual-narrative and semiotic analysis, the visual elements of the HololiveID vTuber character design will be identified and analyzed to classify the design of Indonesian cultural artifacts that the character is trying to adapt. As a virtual youtuber, the character design itself will represent their visual identity. The discourse on the visual adaptation of Indonesian cultural elements has become an interesting phenomenon to study. The impact on Japanese popular culture fans among Indonesian people can be seen from the enthusiasm that emerged when this was a trend. Cultural visual adaptation can be used as a media to introduce a traditional culture by the means of popular culture. From this analysis, it can be concluded how the HololiveID vTuber character design lifts and represents Indonesian culture into its visual identity. The result of this present research shows HololiveID generation two’s character design is proven to have Indonesian cultural design as their visual Identity, mostly their design using batik to represent the Indonesian culture and requires a deeper level of understanding of the Indonesian cultural artefact itself.

Scalar trajectories in design: The case of DIY cloth face masks during the COVID-19 pandemic

The article examines an artefact of everyday design – the Do-It-Yourself (DIY) cloth face mask employed against respiratory infections – to interrogate scale and scalar relationships. This lens reveals new perspectives on how practice-based design research can mobilize scale in more nuanced ways. The authors propose that DIY face masks, as artefacts of mundane design engagements both with material (cloth and thread) and with sharing of knowledge (about design, craft and practice), globally and within local networks and communities, direct our attention to scale as a matter of relations, engagements and emergent trajectories. Through empirically led exploration combined with approaching making as sensemaking, the article highlights the multiplicity of design artefacts emerging in DIY mask design spanning several scales and introduces the notion of scalar trajectories across multiple design engagements.