Designing Narrative-Focused Role-Playing Games for Visualization Literacy in Young Children

Promises and Pitfalls: Using Large Language Models to Generate Visualization Items

Visualization items-factual questions about visualizations that ask viewers to accomplish visualization tasks-are regularly used in the field of information visualization as educational and evaluative materials. For example, researchers of visualization literacy require large, diverse banks of items to conduct studies where the same skill is measured repeatedly on the same participants. Yet, generating a large number of high-quality, diverse items requires significant time and expertise. To address the critical need for a large number of diverse visualization items in education and research, this paper investigates the potential for large language models (LLMS) to automate the generation of multiple-choice visualization items. Through an iterative design process, we develop the VILA (Visualization Items Generated by Large LAnguage Models) pipeline, for efficiently generating visualization items that measure people's ability to accomplish visualization tasks. We use the VILA pipeline to generate 1,404 candidate items across 12 chart types and 13 visualization tasks. In collaboration with 11 visualization experts, we develop an evaluation rulebook which we then use to rate the quality of all candidate items. The result is the VILA bank of ~1, 100 items. From this evaluation, we also identify and classify current limitations of the VILA pipeline, and discuss the role of human oversight in ensuring quality. In addition, we demonstrate an application of our work by creating a visualization literacy test, VILA-VLAT, which measures people's ability to complete a diverse set of tasks on various types of visualizations; comparing it to the existing VLAT, VILA-VLAT shows moderate to high convergent validity (R = 0.70). Lastly, we discuss the application areas of the VILA pipeline and the VILA bank and provide practical recommendations for their use. All supplemental materials are available at https://osf.io/ysrhq/.

Does This Have a Particular Meaning? Interactive Pattern Explanation for Network Visualizations

This paper presents an interactive technique to explain visual patterns in network visualizations to analysts who do not understand these visualizations and who are learning to read them. Learning a visualization requires mastering its visual grammar and decoding information presented through visual marks, graphical encodings, and spatial configurations. To help people learn network visualization designs and extract meaningful information, we introduce the concept of interactive pattern explanation that allows viewers to select an arbitrary area in a visualization, then automatically mines the underlying data patterns, and explains both visual and data patterns present in the viewer's selection. In a qualitative and a quantitative user study with a total of 32 participants, we compare interactive pattern explanations to textual-only and visual-only (cheatsheets) explanations. Our results show that interactive explanations increase learning of i) unfamiliar visualizations, ii) patterns in network science, and iii) the respective network terminology.

Game-based learning in early childhood education: a systematic review and meta-analysis

Game-based learning has gained popularity in recent years as a tool for enhancing learning outcomes in children. This approach uses games to teach various subjects and skills, promoting engagement, motivation, and fun. In early childhood education, game-based learning has the potential to promote cognitive, social, and emotional development. This systematic review and meta-analysis aim to summarize the existing literature on the effectiveness of game-based learning in early childhood education This systematic review and meta-analysis examine the effectiveness of game-based learning in early childhood education. The results show that game-based learning has a moderate to large effect on cognitive, social, emotional, motivation, and engagement outcomes. The findings suggest that game-based learning can be a promising tool for early childhood educators to promote children's learning and development. However, further research is needed to address the remaining gaps in the literature. The study's findings have implications for educators, policymakers, and game developers who aim to promote positive child development and enhance learning outcomes in early childhood education.

Cultivating Visualization Literacy for Children Through Curiosity and Play

Fostering data visualization literacy (DVL) as part of childhood education could lead to a more data literate society. However, most work in DVL for children relies on a more formal educational context (i.e., a teacher-led approach) that limits children's engagement with data to classroom-based environments and, consequently, children's ability to ask questions about and explore data on topics they find personally meaningful. We explore how a curiosity-driven, child-led approach can provide more agency to children when they are authoring data visualizations. This paper explores how informal learning with crafting physicalizations through play and curiosity may foster increased literacy and engagement with data. Employing a constructionist approach, we designed a do-it-yourself toolkit made out of everyday materials (e.g., paper, cardboard, mirrors) that enables children to create, customize, and personalize three different interactive visualizations (bar, line, pie). We used the toolkit as a design probe in a series of in-person workshops with 5 children (6 to 11-year-olds) and interviews with 5 educators. Our observations reveal that the toolkit helped children creatively engage and interact with visualizations. Children with prior knowledge of data visualization reported the toolkit serving as more of an authoring tool that they envision using in their daily lives, while children with little to no experience found the toolkit as an engaging introduction to data visualization. Our study demonstrates the potential of using the constructionist approach to cultivate children's DVL through curiosity and play.

WeChat-based mobile health management for short-stature children with long-term growth hormone therapy: A nonexperimental study

Objective

To evaluate the role of a WeChat-based mobile platform in growth hormone therapy.

Method

Growth hormone therapy and health education information for height growth were embedded in a WeChat-based mobile platform, and the platform was evaluated through medical staff assessments, patient volunteer assessments and quantitative scoring criteria.

Results

In the medical staff evaluation, both clinicians and nurses had a positive attitude towards the mobile platform, believing that the design of the mobile platform was clearly visualized and easy to operate. In family volunteers' evaluations, the summary of β-testing results showed that 90-100% of parents had a positive attitude towards the WeChat-based mobile platform. Parents of the patients and doctors and nurses assessed the mobile platform by reviewing quantitative scoring standards developed by professional researchers. All scores were >16 (the average score was 18-19.3). Children treated with growth hormone therapy were included for compliance tracking for one year, and patient adherence was described in this study.

Conclusion

The interaction based on the WeChat platform and the health education of the public have greatly increased the interaction between doctors and patients, and improved patient satisfaction and compliance.

Identifying neural correlates of multidimensional, subjective gaming experiences during active gameplay

Studying how gaming experiences are encoded is important to understand the effects of gaming on the brain. Although studies have investigated neural correlates of gaming experiences, the brain patterns related to the full range of subjective experiences across different types of games are yet to be identified. The present study used three custom-made, immersive driving games with different input dynamics (controlling a car, a boat, or a spaceship) and different mechanics to assess subjective gaming experiences in a magnetic resonance imaging scanner. A correlational analysis identified several brain networks associated with different subjective gaming experiences, including visual and attentional processing networks. The contributions of these networks were further validated using meta-analysis-based functional term decoding. The results of the present study point to a range of perceptual, motivational, and control networks that are engaged during active gameplay.

A Taxonomy-Driven Model for Designing Educational Games in Visualization

Visualization literacy of the broader audiences is becoming an important topic, as we are increasingly surrounded by misleading, erroneous, or confusing visualizations. How can we educate the general masses about data visualization? We propose a twofold model for designing educational games in visualization based on the concept of constructivism and learning-by-playing. We base our approach on the idea of deconstruction and construction, borrowed from the domain of mathematics. We describe the conceptual development and design of our model through two games. First, we present a deconstruction-based game that requires the inspection, identification, and categorization of visualization characteristics (data, users, tasks, visual variables, visualization vocabulary), starting from a finalized visualization. Second, we propose a construction-based game where it is possible to compose visualizations bottom-up from individual visual characteristics. The two games use the same deck of cards with a simple design based on visualization taxonomies, popular in visualization teaching.