How many ways can we teach data literacy?

Abstract

Academic Libraries are ideally positioned to teach data literacy. What is ‘data literacy’ in the first place? Is it the new information literacy? Will the ways we teach information literacy limit imaginative ways to teach data literacy?
 With those questions in mind, the Library of New York University Shanghai has explored multiple ways to teach data literacy to undergraduate students through university events, ‘for-class’ instruction and workshops, and online casebooks. (1) We initiated the yearlong series of events titled ‘Lying with Data’, inviting faculty across disciplines to each address one core data literacy question that students of data science may elude. (2) We offered workshops and in-class instruction that are up-to-date with the latest technology and that fit with the curriculum. (3) We created online casebooks on various topics in the data lifecycle, tackling user needs at different levels. Essential to our teaching activities are two core values: ‘let the quality speak for itself’, and ‘outreach by teaching’.

The development of statistical literacy among students: Analyzing messages in media articles with Gal's worry questions

“…Data that are conveyed in media articles can often be manufactured or cherry‐picked to justify biased views [4]. As such, students should be concerned about the legitimacy and authenticity of the article, the nature and credibility of the evidence supporting the information or conclusions conveyed, and be able to consider alternative interpretations of the findings communicated to them [11].…”

Going qual in: Towards methodologically inclusive data work in academic libraries

“…In the past decade, a number of academic libraries have turned their attention towards teaching data literacy and offering research data services, driven, at least in part, by the sense that the growing amount of data available online requires new skills (Corrall, 2012;Throgmorton, Norlander and Palmer, 2019;Burress, Mann and Neville, 2020). Within Library and Information Science, the growth in data availability and access has been seen as an opportunity for library staff to deploy their specific skills and expertise (Shields, 2004;Carlson et al, 2011), with the library as an ideal site of instruction around the use of data (Fontichiaro et al, 2017;Dai, 2019). Data literacy may be embedded into individual course instruction or student projects (MacMillan, 2015;Beauchamp and Murray, 2016;Widener and Slater Reese, 2016).…”

“…Some definitions are agnostic about the nature of data in data literacy, such as Prado and Marzal (2013) who define data literacy as 'the component of information literacy that enables individuals to access, interpret, critically assess, manage, handle and ethically use data ' (p. 126). Similarly, Dai (2019) takes a broad view of data literacy as 'critical thinking applied to evaluating data sources' (p. 2). Dai also explicitly positions statistical literacy as a 'companion' to data literacy (p. 2).…”

Collaborating with faculty on data awareness: A case study

“…The literature includes many examples and case studies of librarians who have incorporated data-related skills into courses, created new workshops, and other tools to help find, use, create and store data (Carlson et al, 2013;Dai, 2020;Frank & Pharo, 2016;Kellam & Thompson, 2016;Stephenson & Schifter Caravello, 2007). One well-known instance includes the Data Information Literacy (DIL) project, which "introduces a libraryled approach towards educating students about the data competencies they will need to be successful" (Carlson et al, 2013, p. 215) and ultimately, it led to the Data Information Literacy Program for academic librarians (https://www.datainfolit.org/dilguide).…”