Computing tools for learning and teaching data literacy

用于学习和教授数据素养的计算工具

• 批准号: RGPIN-2018-05072
• 负责人: Chevalier, Fanny
• 金额: $ 2.84万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=750023
• 关键词: Computing; tools; learning; teaching; data

Data literacy is a fundamental part of evidence-informed reasoning because it empowers individuals with the ability to understand, find, collect, interpret, visualize, and support arguments using data. Due to a lack of training in data literacy, people have limited ability to interpret data-centric reports, which can be a serious handicap since a great deal of valuable information is conveyed through statistical charts and data visualization. In an era where data is deemed to be the most valuable resource "the oil of the digital era" promoting data literacy is essential to cultivate an informed citizenry capable of critical thinking, reasoning, and knowledge-based decision making.The human-computer interaction and visualization communities have a history of developing methods, tools, and technologies to support learners in acquiring various skills. While a plethora of tools have been designed to support users in collecting, manipulating, and interpreting data, less attention has been devoted to developing educational tools that support learners in creating foundations for life-long data literacy. A human-computer interaction approach could address this gap and have tremendous benefits in education practice, through the design, implementation, and evaluation of educational tools and interventions that leverage modern technologies, such as pen-and-touch, tangible and virtual and augmented reality user interfaces.This research proposal supports my long-term research goals, which focus on the development of innovative technology-mediated data literacy educational programs. Toward these goals, I will focus on two main objectives:(1) Basic data literacy: Defining and refining of a set of core skills and progression levels of data literacy, to characterize how individuals acquire data literacy and understand pedagogical strategies for instilling data literacy. Developing and evaluating innovative technology-mediated interventions to support data literacy training at an early age.(3) Critical thinking: Defining and refining of a set of cognitive and perceptual biases, as well as visual distortion techniques that can undermine interpretation of data-driven reports. Developing and evaluating innovative technology-mediated interventions to support the teaching and learning of critical thinking with data.This research proposal has the ambition and potential to yield significant advances from theoretical, technical, and empirical standpoints in computer science research by proposing new methods and tools supporting data literacy education at an early age. The outcomes of this program have the potential for near-term societal and long-term economical benefits derived from the development of tools aiming at developing individuals' critical and data-driven thinking, helping children to become informed citizens, and preparing them for careers in data science.

数据素养是证据推理的基本部分，因为它使个人能够理解、发现、收集、解释、可视化和支持使用数据的论点。由于缺乏数据素养培训，人们解释以数据为中心的报告的能力有限，这可能是一个严重的障碍，因为大量有价值的信息是通过统计图表和数据可视化来传达的。在一个数据被认为是最有价值的资源的时代，促进数据素养对于培养具有批判性思维、推理和基于知识的决策能力的有见识的公民至关重要。人机交互和可视化社区有开发方法、工具和技术的历史，以支持学习者获得各种技能。虽然已经设计了过多的工具来支持用户收集、处理和解释数据，但对开发支持学习者为终身数据素养奠定基础的教育工具的关注较少。通过设计、实施和评估利用现代技术的教育工具和干预措施，例如笔触、有形、虚拟和增强现实用户界面，人机交互方法可以弥补这一差距，并在教育实践中产生巨大的好处。这项研究建议支持我的长期研究目标，即专注于开发创新技术中介的数据素养教育项目。为了实现这些目标，我将重点关注两个主要目标：(1)基本数据素养：定义和提炼一套数据素养的核心技能和进步水平，以表征个人如何获得数据素养，并理解灌输数据素养的教学策略。开发和评估创新的技术中介干预措施，以支持早期的数据素养培训。(3)批判性思维：定义和提炼一套认知和知觉偏差，以及可能破坏数据驱动报告解释的视觉扭曲技术。开发和评估创新的技术中介干预措施，以支持数据批判性思维的教和学。这项研究提案有雄心和潜力，通过提出支持早期数据素养教育的新方法和工具，从理论、技术和经验角度在计算机科学研究方面取得重大进展。该项目的成果有可能从开发工具中获得短期的社会和长期经济效益，这些工具旨在培养个人的批判性和数据驱动型思维，帮助儿童成为知情的公民，并为他们在数据科学领域的职业生涯做好准备。