Collaborative Research: RETTL: Story Studio: Coaching Data Storytelling at Scale
Collaborative Research: RETTL: Story Studio: Coaching Data Storytelling at Scale
批准号:
2302795
负责人:
Lujie Chen
金额:
$36.96万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-08-01 至 2026-07-31
中文摘要
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英文摘要
Professionals in data science and analytics excel in data storytelling, a complex skill of communicating stories using data. If done well, data storytelling can enhance public understanding, decision-making, and action. However, postsecondary educators in data science have not been able to train data storytellers effectively at a large scale. To address this issue, researchers from the University of Alabama and the University of Maryland, Baltimore County, and learning scientists from SRI Education are working together on this project to create, develop, and test Story Studio. This platform aims to augment data science educators’ capacity to teach their students the skill of data storytelling.This project features four phases: 1) Extracting knowledge from data science professionals through structured interview methods grounded in Evidence-Centered Design and Cognitive Task Analysis, developing design patterns of key data storytelling steps and competencies, and engaging postsecondary educators and students in vetting the concept and design of Story Studio. 2) Iterative development and small-scale beta testing of Story Studio’s basic architecture for coaching elementary aspects of data storytelling. 3) Expanding beta testing to comprise more advanced Story Studio functionalities, namely, intelligent recommendations and assessments to support students in the story construction process. 4) Conducting classroom pilot studies of Story Studio in data science/analytics courses at two campuses and evaluating the new tool’s effectiveness in improving students’ data storytelling competencies. Research products about Story Studio will be disseminated through education and outreach activities such as storytelling workshops on the researchers’ university campuses, community college partnerships, and teacher training workshops. Finally, the software, algorithms, and de-identified log data will be shared through an open-source database, contributing to learning science and analytics research in data storytelling.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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