Computing tools for learning and teaching data literacy

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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.