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Unlocking Insights: A Modular Approach to Data Visualization Education with the Data Visualization Capacity Tool
The present era of industrial growth, along with the rise in big data, has led to an increase in the demand for data-savvy professionals employing visualization techniques and software to fully leverage the value of this data. Since data visualization is an expansive and intricate field, it leads to challenges for novice learners as they seek to understand it. The Data Visualization Capacity (DVC) Tool is an online learning platform designed to enhance data visualization literacy amongst learners. The DVC Tool encompasses fundamental principles and techniques essential for proficient data visualization, by including external resources, quizzes, and tutorials in a distance-based modular format.
This study investigates the usability of the DVC Tool using a mixed-methods approach combining quantitative analysis of Google Analytics data, System Usability Scale (SUS) questionnaires, and qualitative insights from usability testing sessions and interviews. The research aims to assess the effectiveness of the DVC Tool across diverse user profiles and identify strategies for optimizing user experience. User studies were conducted with participants from various backgrounds and experience in data visualization to gain insight into the strengths and weaknesses of the DVC Tool, as well as gain recommendations for effective learning strategies and user experience design. The findings reveal a high overall usability rating for the DVC Tool, with users from various educational backgrounds and levels of expertise expressing satisfaction with its functionality and organization. The SUS usability scores indicate a mean usability score of 81.8, highlighting the tool's effectiveness in providing a user-friendly learning experience for all users across diverse profiles. Interviews also give insight into the importance of clear organization, visual aids, and custom learning plans to enhance the learning experience of the student.
In general, this research contributes to the advancement of data visualization education by providing insights into effective instructional strategies and components of digital learning platforms. The findings offer practical implications for educators and developers looking to enhance data visualization literacy among learners, while also addressing theoretical gaps in usability research within the field.
History
Degree Type
- Master of Science
Department
- Computer Graphics Technology
Campus location
- West Lafayette