The paper introduces PreVR, a method for allowing the user of a VR application to preview a virtual environment (VE) around any number of corners. This way the user can gain line of sight to any part of the VE, no matter how distant or how heavily occluded it is. PreVR relies on a multiperspective visualization that implements a higher-order disocclusion effect with piecewise linear rays that bend multiple times as needed to reach the visualization target. PreVR was evaluated in a user study ($\mathrm{N}=88$) that investigates four points on the VR interface design continuum defined by the maximum disocclusion order $\delta$. In a first control condition (CC0), $\delta=0$, corresponds to conventional VR exploration with no preview capability. In a second control condition (CC1), $\delta=1$, corresponds to the prior art approach of giving the user a preview around the first corner. In a first experimental condition (EC3), $\delta=3$, so PreVR provided up to third-order disocclusion. In a second experimental condition (ECN), $\delta$ was not capped, so PreVR could provide a disocclusion effect of any order, as needed to reach any location in the VE. Participants searched for a stationary target, for a dynamic target moving on a random continuous trajectory, and for a transient dynamic target that appeared at random locations in the maze and disappeared 5s later. The study quantified VE exploration efficiency with four metrics: viewpoint translation, view direction rotation, number of teleportations, and task completion time. Results show that the previews afforded by PreVR bring a significant VE exploration efficiency advantage. ECN outperforms EC3, CC1, and CC0 for all metrics and all tasks, and EC3 frequently outperforms CC1 and CC0.

Contribution: A model for integrating data visualization into a multidisciplinary course. This innovative practice paper addresses the challenge of the need for data visualization literacy and the scarcity of time to introduce data visualization concepts and workflow in existing courses. Background: Data sensemaking is becoming a prerequisite for all data-driven activities, from engineering to agriculture and humanities. Students are encouraged to generate graphic visuals to support course deliverables (i.e., reports and presentations), interpret knowledge from data, and disseminate research results with little to no introduction to best practices for visually representing data. This article describes an innovative 16-week course introducing data visualization principles and best practices, visualization tools, GIS concepts, and hands-on experience with edge devices (i.e., NVIDIA Jetson, Raspberry Pi, and Arduino). The first eight weeks of the course were dedicated to data visualization principles and practices. The second half of the semester-long course introduced edge devices. Each student received a J2021-Edge AI Device with NVIDIA Jetson Xavier NX 8GB module. A USB WIFI emulator and a 256GB NVMe SSD were also provided with each device to enable wireless network connectivity and expand onboard storage, respectively. The edge device component of the course comprised several lab-based activities to introduce students to the Linux operating system, command line tools, virtual environments, Python programming language, sensor integration, communication protocols, machine learning, deep learning, computer vision, and application development. The rationale for the instructional approach was to allow students to make meaningful connections between data visualization concepts learned in class and their application to visualizing and analyzing data acquired using edge devices. Intended Outcomes: Students will demonstrate their knowledge and ability to apply data visualization principles to real-world data collected with edge devices, and the course serves as a model for developing interdisciplinary courses that benefit from basic knowledge of visualization concepts. Application Design: The course aims to meet the advanced data visualization needs of the College of Agriculture and Technology students. A higher education challenge grant from the United States Department of Agriculture-National Institute of Food and Agriculture has funded this effort. Findings: Students with little to no background in data visualization and the use of edge devices demonstrated the use of data visualization best practices and utilization of edge devices to complete a required semester project that included a research-quality paper formatted for conference submission.

Contribution: A pedagogical tool for teaching and learning data visualization. Since data visualization is such an extensive discipline, it is challenging for novice scholars to get started. The data visualization capacity (DVC) tool that we introduce in this work has a two-fold short-term utility: it can be employed as a resource for inexperienced teachers without formal training in pedagogy for developing learning objectives and outcomes for data visualization activities and assignments while also being a guide for novice visualizers learning the data visualization process. Background: Data visualization is one such discipline that is broadly applicable to various subject areas leading to many people, students as well as industry experts, looking to expand their skill set. Our goal is to introduce a complex, iterative process in an easy-to-understand, non-conflicting manner without over-whelming the students. Previous research suggests that interactive learning environments where students use guided tutorials allow even novice learners to solve difficult concepts effectively. Other similar applications for data visualization tend to focus on a specific, advanced concept rather than introductory material. Intended Outcomes: A data visualization capacity tool that acts as a study resource for anyone new to data visualization while supporting capacity building skills of students allowing them to transform data into insight. Application Design: This work extends the activity worksheets for teaching and learning data visualization published in the 2021 IEEE Computer Graphics and Applications special issue on Visualization Education and Teaching Visualization Literacy. We created a web-based application that is easy to access, use and update where the activity worksheets are part of a module based structure. We introduce each stage of the data visualization process in self-contained modules allowing the students to learn, test, self-asses, and review at a self-guided pace. To support teaching data visualization, the tool focuses on building factual and conceptual knowledge to better understand the role of each individual stage in addition to the iterative nature of the process. Findings: The results of the preliminary analysis by introducing the beta version of the tool to students enrolled in a data visualization course as a resource for a hackathon-like activity show that students who used the tool found it to be useful and report that the tool would be a good study resource for anyone new to data visualization. Test groups contained students from various disciplines and a majority of students expressed a positive outlook on the tool.

This Innovative Practice paper presents the redesign of an introductory data visualization college course to foster participation and engagement in an online setting. Four classroom exercises, referred to as “Zoom Experiences,” are described. Zoom Experiences varied depending on the topic being covered and were different each day to keep students' interest. Students were asked to indicate if they would recommend the “experience” (or not) using a 5-point Likert Scale ranging from: (1) I would definitely NOT recommend, to (5) I would definitely recommend the exercise. A total of 84 responses were analyzed. Analysis of responses indicate over 57% would recommend or highly recommend the activities, 35% would likely recommend, and 8% would not recommend the activities. The goal of the experiences was to help students stay engaged in an on-line element of a course originally designed for in-class participation.

This research to practice paper presents results of students' perception of a worksheet method for identifying appropriate data sources when developing research questions. Identifying reliable and trustworthy data sources takes time and experience. The purpose of this study is to help students plan, generate, and determine the availability of data for research. The worksheet was completed by 32 undergraduates enrolled in a data visualization course. Results show 53% of undergraduates who utilized the worksheet indicate the worksheet helped to identify primary data sources for their topic, 66% indicate the worksheet helped to identify secondary data sources, 59% indicate the worksheet helped to identify tertiary data sources, and 69% indicate the worksheet helped to assess if there is enough data for their research topic. This research informs scaffolding practices for undergraduate and graduate students as they learn and implement research methodology. Implications of this work will help students understand different types of data sources, the role each type of data source plays in developing a research plan, and how to determine the type of data needed to support their research.

This research-to-practice work in progress paper outlines the use of evidence-based practices and learning to enhance critical thinking skills in students through data visualization. Data visualization is a multi-stage process that enables the transformation of complex data into visual representations that inform without overwhelming its audience. The purpose of this study is to investigate how data visualization learning experiences enhances students' critical thinking skills. In this paper we identify the conceptualization of critical thinking in the data visualization process. A design-based research approach is used to empirically investigate the main research question: after participating in data visualization learning experiences, in what ways do students engage in design practices that enhance development of critical thinking skills? The working hypothesis is students experience greater learning gains when instructions include design challenges integrated with the data visualization process and mapped to critical thinking that requires them to exhibit higher-order-thinking skills. The first aim of the study is to identify critical thinking skills that are evident in the data visualization process. The second aim is to identify habits of the mind competencies that are evident in the data visualization process. The implications of this work will inform the implementation of the Paul-Elder critical thinking framework into the data visualization process with the goal of building essential intellectual traits in undergraduates. In this work, the data visualization process facilitates the logical structure of connected elements of higher-order thinking that relate to one another within the theoretical frameworks of critical thinking and habits of the mind. This research is significant because it informs the practice of engineering through a problem-solving activity and computing education by introducing data visualization as method for improving critical thinking skills; a requirement for STEM students, a desired skill for all students.

In this full paper, we describe a design activity method for developing research questions and present a study on student's perception to validate it. We examine, compare and discuss results from three different graduate student cohorts (first, second, and third semester Master's degree students) who used the worksheet method at different stages of their graduate careers. The method is designed to help students identify topics, think critically about the underlying questions to explore a topic, identify a problem to be addressed by the research, and identify data sources to facilitate the research effort. The four stages are introduced as an incremental scaffolding process. Preliminary results showed graduate students found the worksheets effective in helping to develop research questions. This work contributes to the development of research practices and pedagogy supported by sound research questions.

In this research-to-practice full paper, the results of an approach for transforming topic ideas into questions for developing research questions are presented. The first step in developing research questions is identifying an interesting topic. Once a topic is identified, the next challenge is to narrow the focus by formulating and asking questions that, when answered, will provide more depth to the topic. For the novice researcher, articulating what needs to be learned about a topic and what the reader should understand about the topic can be challenging. The purpose of this study is to assess students' perception of a method that is designed to challenge students to ask critical questions of their research topics to better understand what they know about the topic; what remains to be known and what their target audience should understand about the topic as a result of the research. An activity worksheet was designed to facilitate critical thinking about the process of questioning and posing questions as part of the developing research questions process. Students were asked to complete the worksheet then provide feedback on the usability of the activity worksheet. This work aims to answer the following research question, “How do students perceive the usability of the activity worksheet method for developing and evaluating questions about topic ideas?” The activity worksheet was completed by a 43 students across two sections of an undergraduate data visualization course in the Department of Computer Graphics Technology at Purdue University. After completing the worksheet students were asked to provide feedback on the usability of the worksheet, using a 5-point Likert scale: “1 - Strongly disagree,” “2 - Disagree,” “3 - Neutral,” “4 - Agree,” and “5 - Strongly Agree.” Students' overall perception of the worksheet approach was favorable/positive. The implications of this work will help students build skills in questioning and posing questions. This research is significant because it helps students answer critical questions about their topic, and further clarify the significance of a topic beyond their own interests. The contribution of this work is in helping students pose questions and ask questions that will strengthen their critical thinking skills in the practice of engineering and computer science.

In this research to practice paper, the results of an approach for transforming topic ideas into questions for developing a research problem statement are presented. The purpose of this study is to assess students' understanding of the research problem they pose to address. The goal is to motivate students to think beyond their own interests in the topic and consider the interests of a broader audience. An Activity Worksheet Method for transforming questions to a problem statement was developed. The worksheet asks students to articulate if the problem they plan to address is a practical or a conceptual problem. In this paper we present results from undergraduates who used the activity worksheet method to transform questions to a research problem statement. The main research question is "How do students perceive the usability of the Activity Worksheet Method for developing problem statements?" The activity worksheet was completed by 41 students enrolled in two sections of an undergraduate data visualization course in the Department of Computer Graphics Technology at Purdue University. After completing the worksheet, students were asked to provide feedback on the usability of the worksheet. Results show 68% of students responded positively when questioned on the usability of the worksheet. The responses were based on a 5-point Liker scale ranging from 1-5: Strongly Disagree (1), Disagree (2), Neutral (3), Agree (4) and Strongly Agree (5). The implications of this work will help students build skills in developing strong research questions that inform a practice that is required in engineering and computing education. The contribution of this work is in helping students to pose questions and ask questions that will strengthen their critical thinking skills in the practice of engineering and computer science.

In this Research Full Paper, the results of an approach for identifying research topics are presented. The initial step in developing research questions is identifying an interesting topic. The challenge is making the transition from an interest to a topic specific enough to support a research project. The purpose of this study is to assess students' perception of a method designed to help with identifying research topics. In this paper we examine, compare and present results from undergraduates who used the Activity Worksheet Method to identify research topics for semester projects. The main research question is "How do students perceive the usability of the activity worksheet method for identifying topics?" A higher order thinking framework and elements of information literacy framework are used to address two key important aspects of identifying topics: 1) articulating what is known and 2) identifying lack of knowledge about a topic. The activity worksheet for identifying topics was completed by 45 students enrolled in two sections of an undergraduate data visualization course at Purdue University. After completing the worksheet students were asked to provide feedback on the usability of the worksheet. This feedback was provided as a Likert scale rating from 1-5, with 1 being strongly disagree and 5 being strongly agree. Results show 63.7% of responses were "agree" or "strongly agree" that the worksheet is helpful in identifying topics. This research is significant because it helps students to think critically about topic selections for research projects. As students understand what they know and need to know about topics they choose, their understanding will inform the types of questions they ask in the next stage of the developing research questions process: transforming topics into questions. The contribution of this work is a methodical approach to assist, in any discipline, in helping students to develop sound research questions. The implications of this work will help students to build skills in recognizing a need for information and data to answer a specific research question -a practice that is required in engineering and computing education.

Visualization plays an important role in discovery and insight. As a tool, visualization is often times utilized as a light in a sea of data providing insight to large, complex datasets. The scientific community and society at large are the beneficiaries of the utility visualization brings. As more and more data is created and consumed persons with knowledge of the visualization process, applications, methods and techniques will continue to be in demand in all fields with data visualization needs. The purposes of this panel are: (1) to discuss the need for facilitating visualization capacity building: incorporating visualization early and often into computing and other educational programs to equip students with transferrable skillsets that are in demand in the global workforce and (2) to facilitate a discussion on what knowledge base is needed to build and strengthen visualization capacity of users in visualization application domains.