Search Results (34)

Objective: This study provides timely insights into how faculty perceive the role of generative AI in academic collaboration and offers a case study on aligning institutional policy with emerging technological opportunities in higher education. It investigates how generative artificial intelligence (AI) tools are perceived and utilized in the formation of academic research groups, focusing on faculty at the University of Jordan. Design/Methodology: A descriptive cross-sectional study involving a mixed-methods survey of 100 faculty members primarily principal investigators (PI) was conducted, gathering quantitative data on AI familiarity, usage across research group (RG) planning tasks, perceived benefits and risks, and qualitative feedback on recommended institutional actions. Findings: The results indicate moderate adoption of generative AI in RG formation, especially for creative and writing tasks, with younger and junior faculty significantly tending to be more optimistic about AI’s benefits (e.g., increased efficiency, improved content quality) than senior faculty, who reported having greater concerns. The top concerns identified include data privacy, academic integrity (plagiarism), the accuracy of AI outputs, and overreliance on AI at the expense of human expertise. Despite reservations, a large majority agree on the need for official policies and training to guide AI’s ethical and effective use. Conclusion: The findings underscore a generational divide in attitudes, suggesting targeted interventions to support senior academics and influence juniors’ interest. Institutions should craft clear guidelines, provide training, and ensure access to AI tools to facilitate interdisciplinary collaboration and innovation, while safeguarding academic standards. Full article

Project-based learning provides a common context for STEM education at all educational levels. However, before future chemistry teachers can implement it in their teaching, they need to have experience in completing complex projects by themselves. According to previous research, an engineering perspective in STEM projects has been difficult to implement. Therefore, this design-based research project focuses on producing pedagogical resources for conducting STEM projects based on authentic engineering practices. Through three-cycle design research, we crafted Excel templates that support a step-by-step framework for completing complex engineering projects and an evaluation matrix that includes formative and summative tools. The design solutions were validated through empirical problem analysis, which yielded qualitative insights into the possibilities and challenges of the produced tools. From this data, we formulated five best practices for teachers to focus on achieving successful project outcomes, with priority being to support the progress of the engineering approach and support it via guidance and peer collaboration. For future chemistry teachers, artificial intelligence tools offer support, especially for hardware assembly and software coding. The research produced educational artifacts that support conducting STEM projects in higher education and insights into their best practices. Since design solutions are based on research and real-life engineering practices, they are useful for all fields in higher education that conduct STEM projects and aim to teach authentic engineering skills. Full article

Prompt engineering (PE) has emerged as a transformative paradigm in software engineering (SE), leveraging large language models (LLMs) to support a wide range of SE tasks, including code generation, bug detection, and software traceability. This study conducts a systematic literature review (SLR) combined with a co-citation network analysis of 42 peer-reviewed journal articles to map key research themes, commonly applied PE methods, and evaluation metrics in the SE domain. The results reveal four prominent research clusters: manual prompt crafting, retrieval-augmented generation, chain-of-thought prompting, and automated prompt tuning. These approaches demonstrate notable progress, often matching or surpassing traditional fine-tuning methods in terms of adaptability and computational efficiency. Interdisciplinary collaboration among experts in AI, machine learning, and software engineering is identified as a key driver of innovation. However, several research gaps remain, including the absence of standardized evaluation protocols, sensitivity to prompt brittleness, and challenges in scalability across diverse SE applications. To address these issues, a modular prompt engineering framework is proposed, integrating human-in-the-loop design, automated prompt optimization, and version control mechanisms. Additionally, a conceptual pipeline is introduced to support domain adaptation and cross-domain generalization. Finally, a strategic research roadmap is presented, emphasizing future work on interpretability, fairness, and collaborative development platforms. This study offers a comprehensive foundation and practical insights to advance prompt engineering research tailored to the complex and evolving needs of software engineering. Full article

Virtual reality interaction design and story co-creation design for multiple users is an interdisciplinary research field that merges human–computer interaction, creative design, and virtual reality technologies. Story co-creation design enables multiple users to collectively generate and share narratives, allowing them to contribute to the storyline, modify plot trajectories, and craft characters, thereby facilitating a dynamic storytelling experience. Through advanced virtual reality interaction design, collaboration and social engagement can be further enriched to encourage active participation. This study investigates the facilitation of narrative creation and enhancement of storytelling skills in virtual reality by leveraging existing research on story co-creation design and virtual reality technology. Subsequently, we developed and evaluated the virtual reality card-based collaborative storytelling platform Co-Relay. By analyzing interaction data and user feedback obtained from user testing and experimental trials, we observed substantial enhancements in user engagement, immersion, creativity, and fulfillment of emotional and social needs compared to a conventional web-based storytelling platform. The primary contribution of this study lies in demonstrating how the incorporation of story co-creation can elevate storytelling proficiency, plot development, and social interaction within the virtual reality environment. Our novel methodology offers a fresh outlook on the design of collaborative narrative creation in virtual reality, particularly by integrating participatory multi-user storytelling platforms that blur the traditional boundaries between creators and audiences, as well as between fiction and reality. Full article

Since 1969, 55 years ago, Lunar Laser Ranging (LLR) has provided accurate and precise (down to ~1 cm RMS) measurements of the Moon’s orbit thanks to the Apollo and Lunokhod Cube Corner Retroreflector (CCR) Laser Retroreflector Arrays (LRAs) deployed on the Moon. Nowadays, the current level of precision of these measurements is largely limited by the lunar librations affecting the old generation of LRAs. To improve this situation, next-generation libration-free retroreflectors are necessary. To this end, the Satellite/lunar/GNSS laser ranging/altimetry and cube/microsat Characterization Facilities Laboratory (SCF_Lab) at the Istituto Nazionale di Fisica Nucleare—Laboratori Nazionali di Frascati (INFN-LNF), in collaboration with the University of Maryland (UMD) and supported by the Italian Space Agency (ASI), developed MoonLIGHT (Moon Laser Instrumentation for General relativity High-accuracy Tests), a single large CCR with a front face diameter of 100 mm, nominally unaffected by librations, and with optical performances comparable to the Apollo/Lunokhod LRAs of CCRs. Such a big CCR (hereafter, ML100) is mounted into a specifically devised, designed, and manufactured robotic actuator, funded by the European Space Agency (ESA), the so-called MoonLIGHT Pointing Actuator (MPAc), which, once its host craft has landed on the Moon, will finely align the front face of the ML100 towards the Earth. The (optical) performances of such a piece of hardware, MoonLIGHT+MPAc, were tested in/by the SCF_Lab in order to ensure that it was space flight ready before its integration onto the deck of the host craft. After its successful deployment on the Moon, additional and better-quality LLR data (down to ~ 1 mm RMS or better for the contribution of the laser retroreflector instrument, MoonLIGHT, to the total LLR error budget) will be available to the community for future and enhanced tests of gravitational theories. Full article

Craft-based methodologies have emerged as a vital human-computer interaction (HCI) approach, bridging digital and physical materials in interactive system design. This study, born from a collaboration between two research networks focused on affective design and interaction design, investigates how diverse professionals use craft-based approaches to transform design processes. Through carefully curated workshops, participants from varied backgrounds worked to identify specific problems, select technologies, and consider contextual factors within a creative framework. The workshops served as a platform for observing participant behaviors and goals in real-world settings, with researchers systematically collecting data through material engagement and visual problem-solving exercises. Drawing inspiration from concepts like Chindogu (Japanese “unuseless” inventions), the research demonstrates how reframing interaction design through craft-based methodologies can lead to more intuitive and contextually aware solutions. The findings highlight how interdisciplinary collaboration and sustainable and socially responsible design principles generate innovative solutions that effectively address user requirements. This integration of creative frameworks with physical and digital materials advances our understanding of meaningful technological interactions while establishing more holistic approaches to interactive system design that can inform future research directions in the field. Full article

The current research article focuses on safeguarding the knotted carpet weaving tradition in Guano, an endangered intangible cultural heritage (ICH) threatened by globalisation and a lack of intergenerational transmission. The research aims to revitalise this artisanal technique through a comprehensive safeguarding plan, using a participatory action research approach. Activities included in-depth interviews, workshops, and the documentation of seven key cultural practises related to the weaving, such as spinning, natural dyeing, and design. The study found that 86% of these practises are highly vulnerable. To address this, the research developed strategies to promote generational transmission, strengthen local collaboration, and connect the craft to territorial identity and sustainable tourism. Proposed actions include intergenerational education programmes, tourism initiatives, and local fairs to boost carpet marketing. The study contributes to the field of ICH by highlighting the role of cultural tourism in preserving at-risk artisanal techniques and community identity. It emphasizes the need for collaborative approaches to safeguard living heritage in a globalized world. The research findings underscore the importance of integrating traditional practices into modern contexts to ensure their long-term sustainability. Full article

This study sought to ascertain the necessity of crafting specialized multi-user interfaces for scenarios involving multiple users and to provide guidance for the design of multi-user human–computer interactions by identifying the disparities in the interaction behavior and user experience when employing a conventional one-user interface (OUI) recipe versus a multi-user interface (MUI) recipe in the context of family collaborative cooking. To address this objective, this study employed a before-and-after comparison approach. Subsequently, adult users submitted self-assessments of their experiences using the OUI and MUI. The evaluation tools included a user experience survey questionnaire and a Likert seven-point scale, including aspects such as visual confirmation, content, operation, and satisfaction. Post-experiment interviews were also conducted with family members. The MUI exhibited greater effectiveness in terms of visual confirmation, with the “layout” assuming a role analogous to that of “text” in facilitating visual confirmation. Moreover, the operation of the MUI was found to be somewhat enjoyable. Nevertheless, no significant disparities were observed between the OUI group and the MUI group concerning content readability and most operational aspects. Furthermore, the users described their satisfaction with the MUI to be superior to that of the OUI, offering fun, convenience, and a clear appearance. Findings from my research clearly demonstrate that it is both valuable and essential to design a dedicated MUI. Full article

In Romania, rural communities grapple with decades of depopulation and economic decline, endangering the natural and cultural richness of their landscapes. The implementation of Romania’s 2030 sustainable development plan presents an opportunity to reverse these trends by merging economic and community development with cultural preservation. This paper examines the potential for creating new livelihood opportunities through a program that integrates sustainable agrotourism with culturally appropriate vernacular architecture in Romania’s distinct rural regions. Focusing on two such regions characterized by significant rural population decline yet endowed with ecological services capable of supporting a diverse rural economy, we collaborated with an architect and landscape engineer to devise three specific and detailed agritourist housing scenarios. These scenarios draw upon local architectural forms harmonious with the vernacular landscape, providing accommodations for agrotourism guests and facilitating craft workshops for visitors interested in rural crafts and traditions. We evaluated the cultural appropriateness of the architectural designs through a social survey and assessed the broader social utility of the development plan via an expansive cost–benefit analysis, treating the project’s sustainability features as quasi-public goods. Such interdisciplinary endeavours are essential for effectively bridging conceptually driven social analysis with pragmatic design and planning strategies, essential for achieving sustainable futures for rural communities and landscapes, as exemplified by rural Romania. Full article

Wood is one of the main materials used in buildings and furniture worldwide. After a disaster, indeed, a considerable amount of timber waste is produced. Wood waste is generally downcycled—i.e., recycled into low-quality products, incinerated for energy production—or, worse, landfilled, but in a post-disaster situation, it not only represents a quantitative issue and an environmental hazard but also acquires a cultural, social, economic and emotional value, thus requiring more effective ways to be managed. The Katrina Furniture Project, led by Sergio Palleroni in 2006 for the regions hit by hurricanes Katrina and Rita, provides a valuable precedent. Through pilot initiatives in New Orleans, furniture design emerged as a resilient practice within the reconstruction process. Affected people were involved for six weeks in a collaborative design workshop, enabling the generation of income, the acquisition of professional skills and, moreover, the rebuilding of a sense of community through collective work and the intrinsic gathering value of the crafted objects. The research develops a desk analysis and an on-field survey to reflect on the social, cultural, economic and environmental impacts of this case study and on the role of furniture design for resilient wood waste upcycling. Finally, the paper discusses the “legacy” of such practices from a digital perspective, analyzing limitations and opportunities within current research in design and manufacturing. Full article

Open data provide the scientific community and other stakeholders with unrestricted access to data. Open data serve as a foundation for reproducing research findings, while also facilitating collaboration and enabling novel discoveries. However, open data practices are still not commonly applied. To contribute to the implementation of open data strategy in academia in Austria and beyond, a collection of local strategies from regional universities and higher education institutions in the Austrian provinces of Styria and Carinthia was compiled through workshop-based discussions between participants from research support service units at research-performing organizations. The collection was further organized into categories based on application time scenarios, target groups, and involved parties, as well as corresponding thematic focus. A strategic guide consisting of various measures has been developed to encourage the adoption of open data practices from an organizational standpoint. Designed for adaptability, it aims to be applicable and modifiable by all interested research and higher education institutions, regardless of their priorities and resources. Our guideline aids research organizations in crafting a tailored strategy to enhance their data dissemination practices, thereby increasing their research visibility and impact. Full article

The transition to Industry 4.0 and 5.0 underscores the need for integrating humans into manufacturing processes, shifting the focus towards customization and personalization rather than traditional mass production. However, human performance during task execution may vary. To ensure high human–robot teaming (HRT) performance, it is crucial to predict performance without negatively affecting task execution. Therefore, to predict performance indirectly, significant factors affecting human performance, such as engagement and task load (i.e., amount of cognitive, physical, and/or sensory resources required to perform a particular task), must be considered. Hence, we propose a framework to predict and maximize the HRT performance. For the prediction of task performance during the development phase, our methodology employs features extracted from physiological data as inputs. The labels for these predictions—categorized as accurate performance or inaccurate performance due to high/low task load—are meticulously crafted using a combination of the NASA TLX questionnaire, records of human performance in quality control tasks, and the application of Q-Learning to derive task-specific weights for the task load indices. This structured approach enables the deployment of our model to exclusively rely on physiological data for predicting performance, thereby achieving an accuracy rate of 95.45% in forecasting HRT performance. To maintain optimized HRT performance, this study further introduces a method of dynamically adjusting the robot’s speed in the case of low performance. This strategic adjustment is designed to effectively balance the task load, thereby enhancing the efficiency of human–robot collaboration. Full article

Recording large amounts of users’ sessions performed through 3D applications may provide crucial insights into interaction patterns. Such data can be captured from interactive experiences in public exhibits, remote motion tracking equipment, immersive XR devices, lab installations or online web applications. Immersive analytics (IA) deals with the benefits and challenges of using immersive environments for data analysis and related design solutions to improve the quality and efficiency of the analysis process. Today, web technologies allow us to craft complex applications accessible through common browsers, and APIs like WebXR allow us to interact with and explore virtual 3D environments using immersive devices. These technologies can be used to access rich, immersive spaces but present new challenges related to performance, network bottlenecks and interface design. WebXR IA tools are still quite new in the literature: they present several challenges and leave quite unexplored the possibility of synchronous collaborative inspection. The opportunity to share the virtual space with remote analysts in fact improves sense-making tasks and offers new ways to discuss interaction patterns together, while inspecting captured records or data aggregates. Furthermore, with proper collaborative approaches, analysts are able to share machine learning (ML) pipelines and constructively discuss the outcomes and insights through tailored data visualization, directly inside immersive 3D spaces, using a web browser. Under the H2IOSC project, we present the first results of an open-source pipeline involving tools and services aimed at capturing, processing and inspecting interactive sessions collaboratively in WebXR with other analysts. The modular pipeline can be easily deployed in research infrastructures (RIs), remote dedicated hubs or local scenarios. The developed WebXR immersive analytics tool specifically offers advanced features for volumetric data inspection, query, annotation and discovery, alongside spatial interfaces. We assess the pipeline through users’ sessions captured during two remote public exhibits, by a WebXR application presenting generative AI content to visitors. We deployed the pipeline to assess the different services and to better understand how people interact with generative AI environments. The obtained results can be easily adopted for a multitude of case studies, interactive applications, remote equipment or online applications, to support or accelerate the detection of interaction patterns among remote analysts collaborating in the same 3D space. Full article

This study was conducted among undergraduate students pursuing a Primary Education degree at the University of Zaragoza. Its primary aim was to enhance and elevate the quality of participation during theoretical sessions, thereby fostering meaningful learning that contributes to the improvement of academic performance among the participants. To achieve this objective, a quasi-experimental case study was meticulously crafted. This research design was structured to not only stimulate and augment participation but also to cultivate meaningful learning, ultimately enhancing students’ academic achievements. The study employed a comprehensive approach to monitor participation, utilizing observation records to track engagement levels, and anecdotal records to delineate the progression of sessions and the quality of responses. Through meticulous analysis, it can be deduced that the integration of thinking routines as a pedagogical tool in expository sessions significantly enhances student engagement. These routines effectively activate students’ prior knowledge, establishing meaningful connections with the subject matter at hand. Moreover, the incorporation of thinking routines has been observed to elevate the quality of student participation. By fostering reflective practices, aiding in the formulation of inquiries, promoting collaborative learning, and nurturing critical thinking skills, these routines play a pivotal role in enriching the educational experience and bolstering academic performance. Full article

The study aimed to investigate the competencies of 42 preservice science teachers from a rural university in crafting scientific investigations while utilising the constructivist learning theory as its theoretical foundation. Employing an explanatory sequential design, the research initially collected quantitative data through a pre-test, followed by an intervention in the experimental group, succeeded by a post-test phase. In order to enrich the quantitative findings, qualitative data in the form of student responses were analysed, offering a more comprehensive understanding of the preservice teachers’ proficiency in experimental design. Within the control group, no statistically significant variance emerged between the pre-test and post-test rankings, Z = −1.3, p = 0.190. In contrast, the experimental group exhibited noteworthy divergence. The Wilcoxon signed-rank test unveiled a substantial upsurge in post-test rankings when juxtaposed with the pre-test standings, Z = −4, p < 0.001. The qualitative data revealed that preservice teachers manifested a lack of familiarity with comprehension of the variables, strategies for ensuring investigation validity and reliability, and a coherent approach to gauging intervention impact. Emphasising the significance of these revelations, the study suggests plausible pathways for addressing these knowledge gaps via collaborative interventions, thus striving to effectively bridge the identified disparities. Full article