Workshop as an Educational Intervention: Improving the Knowledge and Understanding of Data Visualization Accessibility for Visualization Creators

This research full paper presents front-end design activity with social studies pre-service teachers to inform the design of data visualization technology tools. Data visualizations are powerful tools that social studies teachers use to explore the narratives they want their students to learn. They can serve as evidence for historical arguments and prompts that start students on a path of inquiry. The ability to analyze, interpret, evaluate, and use data and data visualizations - known as data literacy - has become an increasingly important component of K-12 social studies education in recent years.While there are many technological innovations that have been developed to support engineering education in K-12 classrooms, adoption of these tools has been low. Our hypothesis is that adoption may improve if teachers are involved in the front-end design process of technology intended for use in their classrooms. This work describes the results of two Participatory Design (PD) sessions about data visualization with pre-service social studies teachers.In our design sessions, thirty-two pre-service teachers evaluated programming and non-programming data visualization experiences, and then told us what they would like in future data visualization tools. The Minimal Manual was used as a guide in the design of the activity sheets to scaffold use of the tools. After each PD session, we used conjecture mapping to process and analyze the data.Although there were minor design differences in the two PD sessions, the pre-service teachers' evaluations were surprisingly different from one another. These results suggest that PD sessions might be highly idiosyncratic, and we cannot reliably generalize from just a single PD session. We found that secondary focused pre-service teachers tended to be more interested in the data visualization tools than elementary focused pre-service teachers. Further sessions and analysis are necessary to make more reliable conclusions about the characteristics pre-service social studies teachers would like to see in a pedagogical tool they would consider adopting in their classroom. Our work informs other researchers who are considering PD for developing K-12 education interventions.

Using the theoretical frameworks of childhood studies and visual ethics, this article explores ethical ways of engaging children and young people in disseminating self-generated visual data (‘participatory dissemination’) over social media. The discussion draws on a research project carried out with a group of young people in an underserved community in South Africa. The project was an educational intervention that aimed to enable the participants to bring out their experiences with the HIV and AIDS pandemic in South Africa and to reflect on related issues through participatory video making. The methodological focus was on exploring visual ethics in the context of participatory dissemination. Despite a growing interest in social media, few studies have been conducted in relation to ethics in using social media as an outlet to disseminate visual data created by young people. This article contributes to addressing this knowledge gap. It is argued that (1) the process of remaking visual data can enhance the ethics of dissemination by offering young participants an opportunity to reflect on self-representation more carefully and (2) the verbal contextualisation of participant-generated visual data can contribute to a further clarification of young people’s ideas, thereby making dissemination more ethical. I am cautious, however, to overstate the significance of disseminating young people’s verbal and visual expressions without researchers’ discretion because such expressions may contribute to stigmatising the young people.

With the rapid growth of educational data, how to extract valuable information from multi-source heterogeneous data has become an important challenge in educational research. The existing technology applications are scattered and lack systematic integration, which makes it difficult for educational practitioners to comprehensively evaluate the applicability of different methods. This paper systematically reviews the research progress in student behavior analysis, academic prediction and educational intervention from four perspectives: cluster analysis, prediction model construction, association rule mining and data visualization. By integrating domestic and foreign empirical cases, it is found that: clustering algorithms can effectively divide student groups, but the initial center selection and mixed data type processing still need to be optimized; deep learning models perform well in dynamic prediction, but the lack of interpretability limits the direct application of educational decision-making; association rule mining reveals the complex interaction between cognitive style and learning behavior; data distillation bridges the gap between algorithm output and educational interpretability through visualization technology. This paper proposes an innovative path for technical collaboration and emphasizes the importance of interdisciplinary cooperation in solving ethical challenges such as data integrity and algorithm fairness.

It is estimated that approximately 820 million people are infected with Ascaris lumbricoides, and ascariasis infections are over 1.33 million, which is worrying as it can lead to morbidity by impairing the consumption of nutrients, as well as digestion and absorption due to intestinal obstruction. Knowing what research has been done on the subject is important for thinking about future steps to control and prevent helminths and their pathology. Evaluating international participation in research on A. lumbricoides with a view to highlighting the subject and associating these results with nursing practices related to health education, in order to help identify important aspects of the disease caused by this pathogen and to draw up educational interventions in communities, as well as obtaining support for future research. This is a descriptive, bibliometric study with a quantitative approach, carried out in five steps: research designer, compilation of bibliometric data, data analysis, data visualization and interpretation of results. To retrieve the data, scientific articles were searched for in the Web of Science™ (WoS) database. The search term used was "Ascaris lumbricoides". All the information available was downloaded in text file format for analysis using the RStudio Desktop software, linked to the R software (v.4.2.1). The Bibliometrix R package and its complementary graphical web interface, Biblioshiny, and the VOSviewer software were used for analysis. We analyzed 740 articles on A. lumbricoides, published between 1945 and 2023, in 324 scientific journals; Parasitology, Transactions of the Royal Society of Tropical Medicine and Hygiene and Experimental Parasitology were the journals that ranked first for publications on the subject, and the Journal of Cell Biology had the most cited article to date. It was observed that the years that produced the most were 2010 and 2011, both with 17 articles, with the peak number of citations being 510 per year, occurring in 2013. The United States is at the top of the article production ranking, and is also the country with the most collaborations, with Brazil in second place. It was possible to identify global research trends on A. lumbricoides, and it was shown that there is little research on the subject. In the long term, the data obtained can support further research and the development of strategies aimed at both prevention and the control and management of cases of infection by the parasite, on an ongoing basis, through health education; in this regard, nursing professionals are fundamental, as they are the main agents dispersing knowledge to prevent diseases such as ascariasis in the low-income population.

Early and accurate detection of dyslexia can dramatically impact how educational interventions are planned, enabling more effective assistance for individuals with reading and writing challenges (1). However, developing robust machine learning (ML) solutions for dyslexia detection requires a large, diverse corpus of dyslexic texts—something that can be difficult to obtain due to privacy, logistical, and sheer rarity constraints (2). In this study, we utilize a novel approach by using a Large Language Model (LLM)—namely Gemini 2.0 Flash—to generate synthetic dyslexic texts from a small corpus of 50 real “old dyslexic” texts. These synthetic texts, created in both German (DE) and US English (US), serve to enrich training data and improve classification performance (3). We focus on three essential tasks: (i) discriminating 50 normal (non-dyslexic) texts from 50 old dyslexic texts, (ii) discriminating 50 normal texts from 50 new synthetic dyslexic texts, and (iii) discriminating 50 old dyslexic texts from 50 new synthetic ones (4). Each classification scenario is examined through both supervised CatBoost classifiers and unsupervised clustering (K-Means, HDBSCAN). Our results show that while some tasks are straightforward (e.g., normal vs. synthetic dys), others such as distinguishing old dys from newly generated dys are more challenging, indicating that synthetic samples share numerous stylistic features with authentic dyslexic writing (5). This paper combines empirical analysis, data visualization, confusion matrix evaluation, and in-depth discussion of ML-based text classification strategies. In sum, we observe that LLM-based synthetic text generation can provide a valuable supplement to real-world data, supporting both research and potential real-world system deployments. Furthermore, the confusion matrices and F1-scores displayed in Figures 1–4 serve as an evidence-based narrative illustrating the strengths and limitations of synthetic data augmentation in dyslexia classification (6).

BackgroundVirtual reality (VR) could possibly alleviate complaints related to chronic musculoskeletal pain (CMP); however, little is known about how it affects pain-related variables on an individual level and how patients experience this intervention.ObjectiveThis study aimed to gain detailed insight into the influence of an at-home VR intervention for pain education and management on pain-related variables, and to explore its feasibility and general experience.MethodsThe study applied a single-case experimental design in which an at-home VR intervention was used for 4 weeks by patients with CMP who were on a waiting list for regular pain treatment. Outcome measures included pain-related variables, functioning, and objectively measured outcomes (ie, stress, sleep, and steps). Outcomes were analyzed using data visualization (based on line plots) and statistical methods (ie, Tau-U and reliable change index) on an individual and group level. In addition, a focus group was conducted to assess feasibility and general experience to substantiate findings from the single-case experimental design study. This focus group was analyzed using inductive thematic analysis.ResultsA total of 7 participants (female: n=6, 86%) with a median age of 45 (range 31‐61) years participated in this study. A dataset with 42 measurement moments was collected with a median of 280 (range 241‐315) data points per participant. No statistically significant or clinically relevant differences between the intervention and no-intervention phases were found. Results of the visual analysis of the diary data showed that patients responded differently to the intervention. Results of the focus group with 3 participants showed that the VR intervention was perceived as a feasible and valued additional intervention.ConclusionsAlthough patients expressed a positive perspective on this VR intervention, it did not seem to influence pain-related outcomes. Individual patients responded differently to the intervention, which implies that this intervention might not be suitable for all patients. Future studies should examine which CMP patients VR is effective for and explore its working mechanisms. In addition, future larger trials should be conducted to complement this study’s findings on the effectiveness of this intervention for patients with CMP and whether VR prevents deterioration on the waiting list compared with a control group.

Ward NK, Sorice MG, Reynolds MS, Weathers KC, Weng W, Carey CC. 2022. Can interactive data visualizations promote waterfront best management practices? Lake Reserv Manage. XX:XX–XX. Lake water quality management often requires private property owner engagement since land-use change generally occurs on private property. Educational components of lake management outreach must connect current property owner behaviors with future water quality. However, it may be challenging for property owners to associate their current behaviors with water quality outcomes due to the time lag between a behavior (e.g., fertilizer application) and a water quality outcome (e.g., decreased water clarity). Interactive data visualizations, characterized by user-determined selections that change visualization output, may be well suited to help property owners connect current behavior to future water quality. We tested the effectiveness of an online, interactive visualization as an educational intervention to alter property owners’ perspectives related to applying lawn fertilizer and installing waterfront buffers. We used cognitive psychology measures to quantify intervention effectiveness. Since property owners’ decision making may be driven by connections to their property, we also explored relationships between seasonal and permanent residents and intentions to apply fertilizer or install waterfront buffers and intervention effectiveness. Despite no significant difference in effectiveness between the interactive and noninteractive versions, the combined responses demonstrated a positive shift in behavioral beliefs and intentions related to lawn fertilizer application and waterfront buffer installation. Seasonal residents were less likely than permanent residents to apply lawn fertilizer before the intervention and more likely to shift their intentions after the intervention. This study provides evidence that brief educational interventions—regardless of their interactivity—can shift private property owner beliefs and intentions regarding lakefront property management.

The LSU AgCenter Healthy Communities Initiative: Community-Participatory Policy, Systems, and Environmental Change

IntroductionMathematics anxiety is a persistent barrier to effective learning, particularly in primary education. Understanding how this phenomenon has evolved in academic literature can help guide educational strategies and psychological interventions. This study aims to explore trends and key themes in research on mathematics anxiety in primary school students over a 45-year period.MethodsA bibliometric analysis was conducted using data retrieved from the Web of Science (WOS) and Scopus databases. The study included 404 articles published between 1979 and 2024. The analysis was performed using the RStudio environment with the Biblioshiny package. The research process involved study design, data collection, statistical analysis, data visualization, and interpretation.ResultsFindings indicate that research on mathematics anxiety in primary school remained limited for several decades but has gained substantial attention in recent years. The field demonstrates an interdisciplinary nature, with contributions from both psychological and educational research domains. Key authors, journals, institutions, and countries contributing to the field were identified, highlighting global academic interest.DiscussionThe results suggest a growing scholarly focus on the effects of mathematics anxiety, including how cognitive, emotional, and social factors contribute to its development and management. The interdisciplinary expansion reflects a deeper exploration into individual differences and their role in mathematics learning. These findings underscore the need for continued integrated research in addressing mathematics anxiety at early educational stages.

Clinical dashboard development and use for academic detailing in the U.S. Department of Veterans Affairs

Throughout COVID-19, health officials have relied on data visualizations to communicate urgent messages about the spread of the virus and preventative measures. Relatively few efforts have employed participatory engagement with communities who have experienced a disproportionate burden of COVID-19 illness to shape these communications. Sociologist W.E.B. Du Bois viewed data visualization as an approach to changing the way people think about themselves. This paper describes a community-engaged approach to data literacy skill-building with bilingual Latina learners in an adult English program in Northern California, Bay Area. The curriculum combines data visualization activities with language instruction and preventive health themes. Early work on COVID-19 in 2020–21 emphasized improving health knowledge and message interpretation but later shifted to a critical data literacy perspective, focusing on myth-busting, improving risk messaging in their own social networks, and supporting learners to see the power of their own experiences in data story-telling processes. This pedagogical approach, guided by Charles Brigg’s idea of communicative justice priorities, locates adult learners’ data visualization work as part of a broader effort to be included in the perspectives that shape knowledge production in today’s healthcare system. This approach can be used to examine disparities in information access in linguistically minoritized communities and guide future education interventions.

Influence of simulation on electronic health record use patterns among pediatric residents.

Generative artificial intelligence (AI) tools may soon be integrated into health care practice and research. Nurses in leadership roles, many of whom are doctorally prepared, will need to determine whether and how to integrate them in a safe and useful way. This study aimed to develop and evaluate a brief intervention to increase PhD nursing students' knowledge of appropriate applications for using generative AI tools in health care. We created didactic lectures and laboratory-based activities to introduce generative AI to students enrolled in a nursing PhD data science and visualization course. Students were provided with a subscription to Chat Generative Pretrained Transformer (ChatGPT) 4.0, a general-purpose generative AI tool, for use in and outside the class. During the didactic portion, we described generative AI and its current and potential future applications in health care, including examples of appropriate and inappropriate applications. In the laboratory sessions, students were given three tasks representing different use cases of generative AI in health care practice and research (clinical decision support, patient decision support, and scientific communication) and asked to engage with ChatGPT on each. Students (n = 10) independently wrote a brief reflection for each task evaluating safety (accuracy, hallucinations) and usability (ease of use, usefulness, and intention to use in the future). Reflections were analyzed using directed content analysis. Students were able to identify the strengths and limitations of ChatGPT in completing all three tasks and developed opinions on whether they would feel comfortable using ChatGPT for similar tasks in the future. All of them reported increasing their self-rated competency in generative AI by one to two points on a five-point rating scale. This brief educational intervention supported doctoral nursing students in understanding the appropriate uses of ChatGPT, which may support their ability to appraise and use these tools in their future work.

This article presents an overview and continuation of a study investigating how artist awareness and critical response might provide a better understanding of mindfulness and its practice within art education. While there are distinct advantages to mindfulness practices in education, these practices might also have problematic aspects, such as helping people conform to oppressive structures in education rather than questioning them. The pandemic of 2020–2021 accentuated student concerns with social, emotional, and mental health and illuminated possible benefits of mindfulness practice. Results show that preservice art education students used mindfulness and data visualization to connect art and self-inquiry. Important findings included the positive impact mindfulness practices had on students’ social–emotional learning and a refined distinction between mindfulness as a therapeutic educational intervention versus mindfulness an art educational experience.