1,720,965 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Using systems mapping to understand design framing
Get PDFDesign is a cognitive activity that involves an iterative process of problem definition, analysis, solution synthesis, and evaluation. These are necessary for grappling with the complex and ill-structured nature of design problems, that are shaped and focused by those who attempt to solve them. Early parts of the design process require designers to select into view elements of the problem that they deem important for generating solutions. These elements are interconnected and dynamic, shifting criteria and constraints that the designer must consider as they explore the design space. This exploration process is commonly referred to as problem framing, which is essential to the success of creating solutions to design problems.
One useful way that designers can understand the complexity inherent to design problems is by using systems thinking. Systems are commonly thought of as sets of components or parts with interrelations between them which, when arranged in a particular way, carry out a specific purpose. Systems thinking is the way that we understand those system components and the interrelations in order to create interventions, which are often used to move the system outcomes in a more favourable direction. As such, systems thinking has emerged as a promising approach to aid in designers’ understanding of complex design problems.
This thesis proposes a novel research approach to understand design framing activity using a system thinking lens. In particular, I use a common system thinking tool – systems mapping – which is often used to visualize complex situations in order to gain clarity of the elements that are important. I use the systems mapping approach on verbal protocols of designers engaging with design problems in two separate design contexts, in order to retrospectively understand their framing activity. The system map visualizations are analyzed from a wide variety of perspectives, highlighting the novel approach’s use to understand design behaviour.
The method and analyses conducted suggest that these system maps offer a representation of the design framing activity that occurs in each session. Furthermore, small communities of related nodes could represent design frames, used by the designers to create targeted solutions to the design problem. In addition, a temporal analysis on the development of nodes and system dynamics indicates these elements are developed mostly in the early parts of the session, highlighting when framing of the problem occurs. Finally, by assigning ownership of each element added to the system map, the contributions made by each participant can be visualized and analyzed to demonstrate the group’s collective understanding of the problem.
In conclusion, the efficacy of the approach for understanding design framing activity in particular stages of the design process is emphasized. That is, the system mapping approach is well suited to visualize the framing activity that occurs in open-ended problem contexts, where designers are more focused on problem finding and analyzing rather than specifying details of their solutions. Several future research avenues for which the approach would be useful are proposed, with the goal of testing systems mapping in a wider range of problem contexts
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
An exploratory study of experiences of design at hackathons
Get PDFHackathons are popular events where participants “hack” together a project, from ideation through to the final presentation, in 24-48 hours. It is typical for hackathons to be tech-centric; therefore, the attendees tend to be mostly computer programmers, designers, and engineers. Hackathons have been hosted by communities, corporations, and educational institutions with goals of producing artifacts or products, networking, and learning. Hackathons are inherently collaborative, as attendees typically work together in small groups. The participants depend on team skills to complete their projects in the short event time frame.
Hackathons hold a lot of potential for design research; however, the community has been slow to recognize the potential research opportunities. The existing research on design at hackathons is limited, despite the consideration of hackathons as a setting where participants engage in design activity. Motivated by the popularity of hackathons and the lack of significant research on design at hackathons, this thesis presents an exploratory research of hackathon participants’ experiences of design at these unique events. The research is motivated by three main research questions: 1) what are the characteristics of the design process followed by hackathon participants, 2) how does the design process at hackathons differ from more typical design projects, and 3) how does team composition impact the design experience at hackathons?
To answer these research questions, 16 semi-structured interviews were conducted with participants who had collectively participated in 65 hackathons. The transcripts of the interviews underwent a thematic analysis, a methodology that identifies themes in the dataset. Codes were assigned to interview transcripts, resulting in 90 codes on 684 excerpts. The codes were then clustered thematically to identify five major themes: the typical hackathon experience, design at hackathons, collaboration, evaluation of hackathons, and miscellaneous. These themes informed the findings of the study and their presentation in this thesis.
Interview results suggest that the main stages of the design process at hackathons are ideation, building, and pitch preparation and delivery. While some research, including user research, and design iteration activities may occur, the short time frame of the hackathon severely limits these activities and forces participants to instead prioritize the building phase. Further, due to the continuous nature of the event, participants are not able to take significant breaks from their design tasks, thus not benefiting from potential incubation periods. It is concluded that while hackathons share many characteristics of the design process with more typical design projects, the nature of these events causes the design processes to be adapted in significant ways.
Team composition is found to be highly influential in the projects and processes of hackathon teams. Participants’ motivations for attending hackathons - to win, network, learn, or have fun - play a role in what activities they participate in at the events and how they approach their hackathon design project. Motivations for attending, along skills and interest are an important factor considered in team formation. Hackathon teams tend to comprise of three roles: developer, designer, and business analyst, which are determined based on knowledge and experience. The interviews reveal conflict between developers and designers based on their desired approaches to the hackathon design process. Whereas developers are eager to begin building almost immediately, designers encourage a more thorough progression through the design process.
The contributions of this thesis hold implications for hackathon participants and organizers, design researchers, and design educators. The research frames hackathons as design-centered settings that generate rich data. As an exploratory study, the research builds a foundational understanding of design at hackathons, offering a new direction for design research and prompting a number of future research opportunities
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Automating Protocol Analysis with Generative AI: Classifying Questions in Design Review Meetings Using GPT-4
No full textThis study investigates the extent to which generative AI can classify question utterances in verbal protocols of design according to Eris' (2004) taxonomy utilizing in-context learning (ICL). Specifically, it examines the impact of various factors on classification, including the size of the prompt data, contextual information inclusion, prompt engineering strategies, cross-dataset applicability, and cross-model evaluation. The findings of this research could pave the way for more widespread adoption of AI in design research, transforming how protocols are analyzed and interpreted, ultimately leading to more efficient and accurate insights into cognitive processes during design activities.
A series of experiments was conducted to evaluate the performance of GPT-4, a state-of-the-art generative AI model, in this context. The experiments involved utilizing ICL by providing the AI model on a dataset of human-labeled questions and testing its ability to classify new questions according to predefined categories. The findings indicate that GPT-4 performs reasonably well in categorizing stand-alone question utterances, achieving alignment with human-sourced labels in many cases. Moreover, GPT-4 also shows promising generalization capability across the datasets used in this study. The study also highlights the potential of using the less expensive proprietary LLM, Claude 3.5, for similar tasks without a significant drop in performance, making it a more accessible option. The results also imply that classification accuracy depends on the dataset quality, indicating that performance may improve with a higher-quality dataset. However, the results also reveal that providing additional context does not always enhance, and in some cases even diminishes, the model's performance, highlighting the challenges of context-dependent classification tasks.
The implications of these findings suggest that while generative AI shows promise as a tool for automating protocol analysis, there are significant limitations that must be addressed to fully leverage its capabilities in design research. In conclusion, this research contributes to the growing body of knowledge on the application of AI in design research, proposing several directions for future research aimed at refining the use of artificial intelligence in qualitative analysis
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