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Data visualizations, including timelines, maps, and graphs, are often used to present social and political information in the media. Students need to learn how to make sense of data visualizations and recognize when they are being used to mislead, or when they advance white supremacist views. In this study, we used critical race analysis to examine history lessons from four widely-used websites in order to determine if they provided opportunities for students to acquire critical data literacy skills and understand how they presented race and racism in data visualizations. Findings reveal that many lessons miss opportunities to include data visualizations, and, when included, they offer little guidance for helping students understand them. In addition, data visualizations rarely spotlight race or racism, thereby making racial issues and the experiences of marginalized people invisible. We offer advice for teaching data literacy in social studies that centers race and racism. [ABSTRACT FROM AUTHOR]

AbstractUndergraduate economics programs prepare students for future careers by developing competency working with data, or data literacy. Our research examined the data literacy components of undergraduate economics programs at R1 and R2 universities in the United States (N = 190). We developed a protocol with core data skills and coded course and program learning outcomes. Economics programs provided a strong foundation in finding, analyzing, communicating, and applying data but generally lacked explicit training in evaluating sources, understanding types of data, and ethical data practices. We created a dashboard to help economics programs benchmark and create plans to increase data literacy. [ABSTRACT FROM AUTHOR]

Data literacy is typically described in a decontextualized manner, and many data literacy frameworks are detached from the "messy" realities of everyday life. In the present study, we selected a specific context (recreational running), specific data technology (self-tracking devices), and specific viewpoint (accuracy of data and analyses) to construct a substantial theory of (one form of) contextual data literacy. The research question is: How does recreational runners' everyday data literacy appear in relation to the accuracy of measurements and analyses of self-tracking devices? Through an abductive analysis of qualitative survey data (N = 1057), we identified the data literacy actions that runners engaged with when assessing the accuracy of data in relation to their subjective needs, objectives, and life situations. The first-order data literacy actions (comparison and evaluation) captured how runners assessed and analyzed the accuracy of data, and they took place mainly in the immediate context of running. The second-order data literacy actions (acceptance, adaptation, and optimization) were the result of the runners' reflections on what they sought from running and how they valued data, as well as their broader life situation. [ABSTRACT FROM AUTHOR]

Data literacy for students in nonquantitative fields is important as statistics become the grammar of research and how the world's decisions are made. Statistics courses are typically offered by mathematics or statistics departments or by social and natural sciences such as economics, political science, psychology, and biology. Here we discuss how to construct a statistics course for students in nonquantitative fields, with a goal of integrating statistical material with students' substantive interests, using student-focused teaching methods and technology to increase student involvement. We demonstrate this kind of hybrid course with the example of an introductory applied statistics class, taught at both the University of Toronto's Anne Tanenbaum Center for Jewish Studies and the United States Naval Academy. [ABSTRACT FROM AUTHOR]

It is expected that public policy should be based on evidence rather than on any ideology, or any pre-decided goal. Public policymaking should ideally be 'evidence-based.' Data and information constitute evidence. Data needs to be processed and analysed to be used as evidence. To process and analyse data, we need data literacy. The Covid-19 crisis revealed the importance of data and data literacy for sound policy decisions. In the post-pandemic world, data literacy will be an essential skill for policymakers and civil servants. Data literacy should be an essential part of the relevant undergraduate and post-graduate degree curriculums, but also of the in-service training programmes for civil servants. [ABSTRACT FROM AUTHOR]

The article investigates what happens in the platform economy from the point of view of the algorithm-mediated relations established between corporations, governments, and users. From an assemblage approach, the article argues that a new order is emerging whose most salient feature is the collaborative alliances between governments and users versus the large corporations behind the platforms. A direct consequence of this is increasing regulation of platforms' economic activities. Based on the survey of four legal cases, the article applies a mapping method to identify the capacities exercised by the components of this algorithmic assemblage and observe that, while big tech corporations continue to occupy a central position, users and governments are pushing for the assemblage's reterritorialisation and, hence, their Deperipheralisation. Considering this novel trend, the article concludes that the most politically relevant pillar of the new identity of the algorithmic assemblage is a new social contract centred on data rights, literacy, and sovereignty. [ABSTRACT FROM AUTHOR]

This work reports on the implementation of a self-contained data-literacy exercise designed for use in undergraduate classes to help students practice data literacy skills such as interpreting and evaluating evidence and assessing arguments based on data. The exercises use already developed data-visualizations to test and develop students' ability to evaluate arguments based on data presented visually. Moreover, the exercises are designed to teach students positive lessons from evaluating flawed examples of data usage. We show that repeated use of these exercises has the potential to help students develop tools they can use across multiple contexts when evaluating data. Student feedback and panel survey data show that students like to learn using these tools and they report increased comfort levels in working with data. The paper argues that instructional tools like these data visualization exercises are a quick and effective tool for teaching data literacy skills and that they have significant utility in non-research-methods courses. [ABSTRACT FROM AUTHOR]

Universities are increasingly interested in providing courses that equip students with data science skills and engage experiential learning, particularly in the social sciences. However, these courses can be costly to implement and time-consuming for instructors to develop. This article describes an integrative learning model for teaching computational social science skills to undergraduate students. There are three elements to the model: content delivery through collaborative learning, skill development in an applied lab setting, and student mentorship. I apply this model to an experiential course where undergraduate students learn to create and conduct a national public opinion poll. The model addresses the need for university classes that equip undergraduate students with computational social science skills, and provides a pathway for training student researchers as teaching assistants for future courses. This model builds the research capacity of faculty, graduate assistants, and undergraduates, invests in data science by providing an infrastructure for the collection of large scale data over time, and integrates experiences inside and outside of the classroom. This model is replicable at other institutions and will be of benefit to programs seeking to implement best practices and maximize learning effectiveness through research integration. [ABSTRACT FROM AUTHOR]

Given the lack of data-literate talent in business organizations, there is a need to develop more effective data literacy education at university level. With the aim of informing improvement, a systematic, quantitative literature review of data literacy education was undertaken. The review of 71 articles revealed that data literacy education predominantly relies on existing learning theories and teaching strategies, lacks empirical studies, and lacks agreement about what competencies constitute data literacy. These findings highlight the need for empirical research to establish what needs to be taught and how it can be best taught. [ABSTRACT FROM AUTHOR]

Contemporary research on preservice teachers' data use opportunities, coursework, and interventions typically focuses on preservice teachers' perceptions about data use comfort, confidence, and preparedness. Despite the contribution of such research to understanding the efficacy of approaches to teacher preparation, understanding preservice teachers' underlying conceptions about data and data use is critical to responsive teacher preparation. However, these conceptions are elusive as preservice teachers do not routinely engage in authentic data use practices. In the present study, I develop a novel methodological approach for uncovering preservice teachers' conceptions about data. Then, I use this framework to investigate how achievement classifications and accountability pressure manifest in preservice teachers' instructional decision-making. Findings suggest preservice teachers have a general propensity for differentially allocating instructional resources to their lowest achieving students and respond to accountability pressure by shifting these resources toward students approaching proficiency criterion and those closest to achievement thresholds. Findings have implications for how teacher preparation programs may leverage preservice teachers' conceptions as a foundation for the development of data literacy, iterative instructional improvement, professional inquiry, and accountable leadership. [ABSTRACT FROM AUTHOR]

With the exponential increase in the volume of data available in the 21st century, data literacy skills have become vitally important in work places and everyday life. This paper provides a systematic review of available data literacy assessments targeted at different audiences and educational levels. The results can help researchers and practitioners better understand the current state of data literacy assessments in terms of issues related to 1) educational levels and audiences; 2) data literacy definitions and competencies; 3) assessment types and item formats; and 4) reliability and validity evidence. The results from the present review led us to conclude that teaching and assessing data literacy is still an emerging field in education. Therefore, high-quality assessment tools are greatly needed to provide valuable insights for students and instructors to monitor progress as well as facilitate and support teaching and learning. [ABSTRACT FROM AUTHOR]

Data preparation (also called "wrangling" or "cleaning") – the evaluation and manipulation of data prior to formal analysis – is often dismissed as a precursor to meaningful engagement with a dataset. Here, we re-envision data preparation in light of calls to prepare students for a data-rich world. Traditionally, curricular statistics explorations involve data that are derived from observations that students record themselves or that reflect familiar, relatively closed systems. In contrast, pre-constructed public datasets are much larger in scope and involve temporal, geographic, and other dimensions that complicate inference and blur boundaries between "signal" and "noise." As a result, students have fewer opportunities to consider sources of variability in such datasets. Due to these constraints, we argue that data preparation becomes an important site for students to reason about variability with public data. Through analyses of repeated task-based interviews with five pairs of adolescent participants, we find that specific actions during data preparation, such as filtering data or calculating new measures, presented opportunities to engage leaners with variability as they prepared and analyzed several public socioscientific datasets. More broadly, our study highlights some changes to theory and curriculum in statistics education that are necessitated by a focus on "big data literacy". [ABSTRACT FROM AUTHOR]

In both data protection law and research of usable privacy, awareness and control over the collection and use of personal data are understood to be cornerstones of digital sovereignty. For example, the European General Data Protection Regulation (GDPR) provides data subjects with the right to access data collected by organisations but remains unclear on the concrete process design. However, the design of data subject rights is crucial when it comes to the ability of customers to exercise their right and fulfil regulatory aims such as transparency. To learn more about user needs in implementing the right to access as per GDPR, we conducted a two-step study. First, we defined a five-phase user experience journey regarding the right to access: finding, authentication, request, access and data use. Second, and based on this model, 59 participants exercised their right to access and evaluated the usability of each phase. Drawing on 422 datasets spanning 139 organisations, our results show several interdependencies of process design and user satisfaction. Thereby, our insights inform the community of usable privacy and especially the design of the right to access with a first, yet robust, empirical body. [ABSTRACT FROM AUTHOR]

The use of online literacy applications is proliferating in elementary classrooms. Using data generated by these applications is assumed to be helpful for teachers to identify struggling readers. Unfortunately, many teachers are unsure how to use and interpret the plethora of data from these apps. In this longitudinal study, we followed a cohort of students from kindergarten through first grade (n = 54). We then used quasi-simplex models to estimate the relation between five performance measures taken from an online literacy application and five reading related progress monitoring outcomes at four sequential time points controlling for previous achievement. Results suggest performance measures have more predictive power during kindergarten and the amount of time students were logged-in to the program was the most consistent predictor across outcomes and assessment periods. The number of interactions with the program was significantly related to students' decoding skills. We discuss how these results might be used to increase teachers' use of performance measures to adapt instruction. [ABSTRACT FROM AUTHOR]

The relationship between data literacy and business librarianship continues to grow in relevance as the conversation intensifies in higher education and the business world. Establishing shared vocabularies and mappings to foundational library professional documents is essential to moving the discourse forward. This article presents a mapping between seven baseline business data literacy competencies and the ACRL Framework for Information Literacy for Higher Education. [ABSTRACT FROM AUTHOR]

This column reviews publications in this column from 2019 through 2022. It identifies key themes and provides resources for informatics instructors. [ABSTRACT FROM AUTHOR]

In this paper, we put forward a theoretical framework for understanding data literacy in initial teacher education. We have come to understand that data literacy is non-linear, non-hierarchical, and requires pre-service teachers to be able to work with a range of data sources to respond to the complexities of a classroom. Knowledge, therefore, can be seen as interconnected rhizomes. These rhizomes grow and are retained or a pruned as a result of direct instruction and vicarious experiences. Three theories have been presented here that enable researchers to grasp the complexities of data literacy. These theories being Technological Pedagogical Content Knowledge (TPACK), Rhizomes of Knowledge, and Knowledge in Pieces. Through understanding that knowledge may be formed in interconnected rhizomes that are activated to complete a task, a potent standpoint is offered for understanding the dynamic nature of knowledge and knowledge development in pre-service teacher education. [ABSTRACT FROM AUTHOR]

Data science is a highly interdisciplinary field that comprises various principles, methodologies, and guidelines for the analysis of data. The creation of appropriate curricula that use computational tools and teaching activities is necessary for building skills and knowledge in data science. However, much of the literature about data science curricula focuses on the undergraduate university level. In this study, we developed an introductory data science curriculum for an out of school enrichment program aimed at middle grade learners (ages 11-13). We observed how the participants in the program (n = 11) learned data science practices through the combination of nonprogramming activities and programming activities using the language R. The results revealed that participants in the program were able to investigate statistical questions of their creation, perform data analysis using statistics and the creation of data visuals, make meaning from their results, and communicate their findings. These results suggest that a series of learnercentered nonprogramming and programming activities using R can facilitate the learning of data science skills for middle-school age students. [ABSTRACT FROM AUTHOR]

This article develops a sociotechnical conceptualisation of data literacies in relation to citizens' data practices: highlighting the agentic, contextual, critical, and social aspects of data skills and competencies, it frames data literacies as both discursive and material. In order for civil society organisations to make sense of big, small, open and other data they need multiple skills, beyond the technical; it is, therefore, unhelpful to talk about a single form of data literacy. It is more helpful to consider how such literacies in the plural develop within the material social contexts of civic cultures, and how they can progress in tandem with critical awareness about the power aspects of data, so they can become central tenets of data advocacy. The primary purpose of the article is to move forward the debate around how to conceptualise data literacy – and to question how far the concept is useful in the first place. The article draws on empirical research and starts from the premise that it is imperative to develop frameworks and training schemes that enable civil society actors and publics more generally to use open data, to make data more relevant to stakeholders, and to support their engagement in policy debates around datafication. [ABSTRACT FROM AUTHOR]

Integrating data driven decision making into teacher preparation programs has been called for by several researchers in order to help lessen the barriers teachers face in using data in their teaching. This mixed methods study examined the perceptions of data use in education by pre-service teachers (N = 112) and perceived knowledge and skills required for successful use from both pre-service teachers (N = 6) and the faculty who educate them (N = 5). Results have implications for teacher preparation programs considering data literacy integration and for researchers aiming to understand the best ways to encourage data driven decision-making skills and knowledge in pre-service teachers. [ABSTRACT FROM AUTHOR]

Data literacy—the ability to comprehend, analyze, and interpret data and data visualizations—is inextricably linked to the goals of K–12 social studies education. In a society where data visualizations such as maps, charts, and graphs are used to communicate information about problems, policies, and trends, or persuade people to vote for a candidate or agenda, an informed citizen must also be a data-literate citizen. Unfortunately, little is known about how teachers view data literacy's role in social studies education or how well prepared they are to teach it. This study involved an online self-administered cross-sectional questionnaire of a sample totaling 262 practicing U.S. elementary and secondary teachers of social studies. Using mixed methods analyses, we address questions about teachers' practices, beliefs, and knowledge related to data literacy in social studies. The insight gained from this research establishes a foundation for work in social studies teacher preparation and professional development. [ABSTRACT FROM AUTHOR]

In this paper, we put forward the OTTO Model as a means for developing data literacy in pre-service teacher education. The OTTO Model was developed using a combination of quantitative and qualitative data drawn from a three-year study investigating the nature and development of pre-service teachers' data literacy. The aim of the study was to enable pre-service teachers to experience transformative learning during their practice-based professional experiences. Part of this process was to prepare pre-service teachers for their Teaching Performance Assessment (TPA). Requisite skills for TPAs require that pre-service teachers have a high level of assessment and data literacies in order to engage with the TPA tasks. Formative use of the OTTO Model can be embedded into initial teacher education courses allowing more targeted and specific use of data to assist pre-service teachers in developing these requisite literacies. [ABSTRACT FROM AUTHOR]

Increasingly, teachers are considered accountable for continuous improvement in student achievement. They are expected to integrate and analyse data from multiple sources in order to make decisions aimed at positively influencing student outcomes. Given the growing recognition of the importance of data-informed decision making in teaching, it is important to understand how teachers can best be supported in this. Currently, there is little research into how teachers can facilitate data literacy development for their in-school colleagues. This study employed an interpretive qualitative methodology to focus on the experiences of mathematics lead teachers (MLTs) in leading change to support the development of their colleagues. MLTs were found to use a range of tailored strategies, providing 'on the job' and 'just in time' support, and demonstrating evaluative and adaptive capabilities. They were found to provide leadership in the development of data-informed decision making through their collaborative approach. [ABSTRACT FROM AUTHOR]

The Leventhal Map & Education Center (LMEC) at the Boston Public Library (BPL) has expanded its activities in recent years to include educational and technical support for audiences working with geospatial data, tools and concepts. At the K-12 level, LMEC's Empowering Maptivists initiative engages Boston public high school students in a deep exploration of the uses of geospatial data and mapping in order to help foreground relevant community issues and propose possible solutions. In its role as a partner with the BPL, the LMEC also offers a suite of free, helpful resources for any library visitor, including one-on-one project support and digital guides geared toward decoding and translating the sometimes-complicated intricacies of geospatial data and tools. The LMEC's recently grant-funded Data Hub project accelerates this momentum by further expanding educational activities, and allowing the LMEC to build out the necessary technical infrastructure to support them, including a searchable and browsable digital library to hold geospatial data, as well as other learning materials for deciphering data. [ABSTRACT FROM AUTHOR]

Enhanced opportunities to use new techniques to derive insights from large volumes of data have potential to change the role of the law enforcement analyst. Alongside this growing potential is a push toward professionalisation for crime and intelligence analysis as an occupation. In this paper, we explore the extent to which existing descriptions of core competencies reflect skills identified as important by analysts and their managers. We draw on interviews with sixty-one analysts and supervisors from law enforcement agencies in Canada, the United States, and Australia. We confirm that existing descriptions of core competencies align with those identified by analysts and managers. We identify three considerations for present-day police organisations: the importance of data literacy and technical skills, the importance of self-motivation as a trait for analysts, and the core competencies of analyst supervisors. We complicate discussions about the importance of technological comprehension in light of software that automates components of analysis, illustrating how limits in data literacy translate to challenges for making effective use of new technologies. Next, we demonstrate how an ability to navigate interpersonal dynamics in police organisations is essential for analysts and analytic managers to be effective in their roles. We illustrate a reliance on individual-level motivation for competency-building over organisationally driven or standardised professionalisation. Finally, we contribute to limited scholarship addressing competencies for analyst supervisors and managers and discuss the implications of supervision for analyst skill development. [ABSTRACT FROM AUTHOR]

This article uses Kuhlthau's Information Search Process (ISP) to illustrate ways that librarians can assist students and collaborate with data providers to improve the data search process. Librarians and data providers share similar data literacy goals, and this paper pools the expertise of both groups to focus on strategies and interventions that support novice researchers. We explore our combined experiences and jointly step through students' research phases to examine how each group can contribute to improving that experience. We review students' data literacy needs throughout the research process through the lens of Kuhlthau's six-stage, iterative ISP. Kuhlthau's framework, rooted in empathy, maps to existing knowledge about what students do, think, and feel at various stages of the search process. We identify "zones of intervention" that are both consistent with Kuhlthau's research and are novel to data-rich research projects. [ABSTRACT FROM AUTHOR]

McGill University Library is undertaking a collaboration between three librarians and various faculty members from the Desautels Faculty of Management. The project seeks to better understand what data is available for business and finance, where that data is stored across the institution, and how its access can be better promoted and shared among the Faculty. The need to address data coverage and access was originally proposed as a project for the Faculty's committee on Teaching and Learning Resources. The project team is made up of two Business Librarians, a Data Librarian, an Associate Professor, and a Senior Faculty Lecturer. Progress on this project has been ongoing, though significant delays were caused by the COVID-19 pandemic and the resulting closure of the McGill University campus. [ABSTRACT FROM AUTHOR]

Based on an applied thematic analysis, this study identifies data literacy education practices in the business and economics librarian profession. Five themes emerged from the interviews: Roles and Responsibilities; Expertise; Pedagogy and Teaching; Professional Development; and, Institutional Support. This article is for librarians who find themselves working with data and those who want to do so. The insights shared from participants offer trajectories for administrators to support the work of data literacy education. The article's recommended future research directions section provides areas to build community and develop inquiry for interested researchers' ongoing work in data literacy instruction and academic librarianship. [ABSTRACT FROM AUTHOR]

This case study describes activities developed by academic librarians to provide data literacy opportunities to graduate and undergraduate business students. These opportunities were provided by a data-related program in the libraries and in-class activities. Topic modules for the data program and steps for course-related data visualizations and are discussed. Conclusions reached as to the impact and acceptance of these programs and future directions are presented. [ABSTRACT FROM AUTHOR]

Companies are looking to harness the power of data, both big and small, to take their business to new levels. One major hurdle for companies seeking to become data-centric is facing a lack of data literate talent for hire in the current market of recent college graduates. This article establishes a conversation about data literacy in business education, discusses the role of the librarian in this work, and proposes a set of data literacy competencies that librarians could help incorporate into business school education, as has been similarly seen in other disciplines. [ABSTRACT FROM AUTHOR]

"Doing economics" is an important theme of undergraduate economics programs. Capstone courses increasingly include instruction in "data literacy" and the STEM-related skills of quantitative and empirical methods. Because the professional discipline has moved in this direction and because of greater employer demand for these skills, data visualization is a key component of data literacy. Tableau is a free data visualization software widely used in the data analytics industry. In this article, the authors introduce an exercise that teaches the fundamental Tableau concepts and commands needed to create charts, assemble them in a dashboard, and tell a story of patterns observed in the data. The exercise assumes no prior experience in Tableau and is appropriate for undergraduate upper-level economics courses or an empirical methods course. [ABSTRACT FROM AUTHOR]

This article examines the social utility of the concept, 'data literacy'. Recent developments in the processes of datafication challenge long-held assumptions about privacy and the role of both state and commerce in individual lives. Typically, these have been addressed through: regulatory legal constraints underwritten by the nation state but are difficult to enforce at a global level; tactical resistance through forms of self-regulation and technical innovations, and; educational interventions, typically as 'literacy', which brings understanding of the new forms of digital control. The article considers the benefit of theorising digital data as a 'text' and reviews current educational models of data literacy, categorised here as formal, personal and folk pedagogies of data. The article concludes that while the analogy between print and data has many inconsistencies, the term has rhetorical benefits. However, to become a meaningful strategy 'data literacy' requires both a more complete theorisation and complex practical development. [ABSTRACT FROM AUTHOR]

How do we teach and learn with our students about data literacy, at the same time as Biesta (2015) calls for an emphasis on 'subjectification' i.e. 'the coming into presence of unique individual beings'? (Good Education in an Age of Measurement: Ethics, Politics, Democracy. Routledge) Our response to these challenges and the datafication of higher education, is a hands-on approach to building an open, collaborative pedagogy of data literacy, based on Bayesian Networks (BNs) (Pearl, J. 1985. Bayesian Networks: A Model of Self–Activated Memory for Evidential Reasoning. Los Angeles: University of California (Computer Science Department)). BNs can be used to merge subjective views of the learning process with objective data analysis from the learning environment; BNs are visual data constructs and, unlike other Machine Learning approaches that obfuscate and complexify, BNs can be developed to reveal relationships from observations. In this paper, we share ways in which teachers and students can work together in a praxis approach to use data to 'read the world' around them (Freire, P. 1970. Pedagogy of the Oppressed. New York: Continuum. 125). [ABSTRACT FROM AUTHOR]

As algorithmic decision-making and data collection become pervasive in higher education, how can educators make sense of the systems that shape life and learning in the twenty-first century? This paper outlines a systematic literature review that investigated gaps in the current framing of data and faculty development, and explores how these gaps prevent the formulation of potential pathways and principles for fostering educators' data literacy. The analysis of 137 papers through classification by relevant categories and key word mapping shows that there is little attention on higher education teachers. It also makes clear that most approaches to educators' data literacy address management and technical abilities, with less emphasis on critical, ethical and personal approaches to datafication in education. The authors conceptualize this situation as a 'complicated' approach to data literacy in the academic profession, as opposed to a complex vision which would bundle management and technical skills together with a critical, systemic approach to professional learning and data. [ABSTRACT FROM AUTHOR]

This study describes outcomes from a place-based, teacher-scientist partnership intended to support teacher use of authentic data for science and math instruction. Teachers worked with scientists in the field to practice collection and analysis of authentic data. This case study investigated how narrative structure and contextualisation were created and used by teachers to convey meaning from the scientists to students. Participant interviews, focus groups, and researcher notes were qualitatively analysed through production and testing of propositions. The results show that teacher narratives were based heavily on the scientists' narratives as informed by teachers' own field experiences and authentic data. Teachers served as participant-narrators in the narratives rather than central agents, and they used the elements of narrative structure to frame knowledge that is co-constructed by the scientists, teachers, and students. This model of transfer through story is described in detail along with implications for research and practice. [ABSTRACT FROM AUTHOR]

Information skills are essential in business contexts where information is plentiful and selecting, synthesizing and leveraging that information in decision making provides the competitive advantage. Information literacy is considered to be one of the most important graduate attributes, but do academic information skills translate into the business context? What information skill sets should educators focus on providing students to best equip them for the workplace? Interviews were conducted with employers and recent graduates working in Western Sydney. These conversations identified specific information tools, techniques and processes, which can inform practical curriculum innovations to assist business graduates to be work ready. [ABSTRACT FROM AUTHOR]

In economic development and other economics electives, students regularly encounter economic measures of absolute and relative deprivation, from poverty measures like the Foster-Greer-Thorbecke index to measures of distribution like the Gini index. By "doing economics," students practice applying economic measurement to real-world data and develop more general data literacy. The author proposes a series of exercises starting with stylized 10-household economies, proceeding to nationally representative cross-sectional surveys using MS Excel or Google Spreadsheets, and culminating in students applying their acquired data literacy to a team project. The data sources are easily tailored to alternative household surveys in low- and middle-income countries that include the required variables. Students learn data literacy through recognizing the properties of rectangular data, visualizing data appropriately, and creating aggregate economic measures. [ABSTRACT FROM AUTHOR]

Data driven pedagogy has been introduced into Australian schools over the last decade to improve student learning outcomes, but are teacher educators preparing preservice teachers to be data literate? We used a survey to investigate ready-to-graduate preservice teachers’ beliefs regarding their knowledge and skills in data literacy. Before entering a course on data literacy their belief responses indicated that they had basic data interpretation knowledge, but they were unsure of how to translate that knowledge into the classroom to improve student outcomes. The survey was administered again after a data literacy course, which included a five-week supervised professional experience task of observing data being used in schools to drive pedagogy. The post-course survey responses showed students increased confidence in their ability to interpret and use data, suggesting that a data literacy course linked to the professional experience task improves teachers’ sense of preparedness to use data in the classroom. Keywords: Data literacy; professional learning. [ABSTRACT FROM AUTHOR]

The rising prevalence of data visualizations in the political and economic spheres requires an increasingly data literate population. Data are used to persuade people how to vote, support policies, adopt arguments or agendas, and buy products. Furthermore, data literacy is a specialized literacy skill that students need to employ to make meaning within the academic disciplines. This article presents a study of over 3,000 data visualizations in 42 K-12 social studies textbooks, addressing the questions: How prevalent are data visualizations in social studies texts? How are data visually represented in social studies texts? What purpose do data visualizations serve in social studies texts? and To what degree do social studies texts support and encourage analysis of data visualizations? Findings reveal not only the important role that data visualizations play in communicating information within social studies materials but also implications for social studies research and instruction. [ABSTRACT FROM AUTHOR]

Current preservice teacher education practice related to data use has been deemed inadequate, in that it is unevenly distributed and often superficial. In response, this article describes a course-based classroom assessment data-literacy experience for preservice elementary teachers. Grounded in extant theory and research concerning data literacy and data use and interventions to promote data use processes among educators, the 6-hour experience involves preservice teacher scoring of teacher-developed assessments, and analyzing, interpreting, and making decisions based on these data. The pedagogical strategy’s design (objectives, materials, and activities) and implementation process are illustrated for the reader. It is hoped that members of the teacher education community will adopt or adapt the strategy for implementation with preservice teachers within other programs and institutions. In doing so, teacher educators can provide preservice teachers with rich, in-depth experiences by which to equip them for this salient but difficult facet of their professional practice. [ABSTRACT FROM PUBLISHER]

A number of trends are converging to drive the need for more informed teacher data use. These include advocacy for formative assessment and the need for teachers to account for student learning. In this context, assessment literacy and data literacy have emerged as a focus in research and professional development. Problematically, research signals that developing assessment/data literacy is challenging with evidence that teachers may not have mastered relevant aspects of mathematics and statistics. This paper reports lecturer, student teacher and school leader views of the role and requirements of data literacy using data from a larger study into how to foster student teacher mathematical thinking for the breadth of teacher professional work. Data were generated via interviews, surveys and document analysis. Findings suggest a concern and opportunity to develop assessment/data literacy as this calls on mathematical and statistical understanding. [ABSTRACT FROM PUBLISHER]

While some Canadian universities have a long history in the provision of data services, that was not the norm in Canada, especially in small universities and colleges. To maximize the use of data by students and researchers in academia, it was evident that increased education, resources, and tools were required to support those delivering data services on their campuses. To this end, the Data Liberation Initiative (DLI) Survival Guide was designed as a comprehensive reference tool, which complements an established regional training curriculum, whereby enabling librarians to effectively fulfill their role as a DLI Contact in their academic institutions. This case study will examine the history, current state, and recommended future direction of the Survival Guide. This article will also examine the challenges in understanding the drivers shaping academic service delivery and the ways in which the guide has evolved to remain current to the needs of the Canadian data community. [ABSTRACT FROM AUTHOR]

Research data management (RDM) skills are vital yet often untaught in graduate programs, especially in the social sciences. In this article, the authors present a case study of how a research data librarian and an education librarian partnered to provide targeted RDM instruction for a previously unconsidered student group: education doctoral students. They discuss the design, development, and implementation of this focused RDM support. Assessment data from a workshop and in-class sessions are presented and contextualized. From this information, the authors offer practical suggestions that other social science librarians can use to create similar workshops at their institutions. [ABSTRACT FROM AUTHOR]

The development of a student's ability to make data-driven decisions has become a focus in higher education (Schield 1999; Stephenson and Caravello 2007). Data literacy, the ability tounderstand and use data to effectively inform decisions, is a fundamental component of information competence (Mandinach and Gummer 2013; Stephenson and Caravello, 2007). This commentary highlights the structure of a data literacy course that aims to simultaneously teach problem-solving skills and Microsoft Excel skills through real-world examples and problem based learning. This commentary aims to provide insight to other educators teaching similar courses regarding using technology as a tool for developing a student's problem solving ability. [ABSTRACT FROM PUBLISHER]

This article explores tensions between the imaginaries and material hindrances that accompany the development of digital infrastructures for narrative exchange and public engagement. Digital infrastructures allow civil society organizations to become narrators of their community lives, and to express solidarity and recognition. Often full development and implementation of such infrastructures result in drastic changes to an organization's mode of operation. Drawing from empirical material collected during an action research project with an organization of community reporters in the North of England, here we examine the visions of ‘telling the story of the stories’ that motivated such changes, the experiments in web analytics and content curation that in practice realized these visions and the socio-economic contexts that constrained them. We attend to the wider social imaginaries about the digital as they help us understand better how social actors construct the worlds they want to inhabit within information society through mundane everyday practices. Examining how perceptions of digital engagement translate into such concrete practices is necessary in order to gain insight into the ways in which material infrastructures, such as resources and technologies, intertwine with social and cultural expectations about how life should be with digital technologies. [ABSTRACT FROM AUTHOR]

Building on a study conducted by the authors, this article provides strategies for teaching data literacy and outlines the case-based teaching method as an effective way of developing data-literate teachers. [ABSTRACT FROM AUTHOR]

Authentic scientific data, when richly contextualized, can provide the basis for compelling learning experiences. Many undergraduate students either do not have access to primary data, or if they do, the data are so abstract that student engagement is limited. Here, we describe contextual information and data-rich, student-centered activities we developed to give life to data sets from an intensely studied place, the Rocky Mountain Biological Laboratory (RMBL). The project Web site, Digital RMBL, highlights charismatic organisms, scientists, and long-term data sets as a tool for engaging students who are unable to physically visit a field station. The Biology of Climate Change module, the focus of this paper, has been tested in college-level classrooms by 10 collaborating faculty and 243 undergraduate students at a variety of colleges and universities across the nation. Authentic long-term data sets, primary literature, data visualizations, and a flexible format suitable for laboratory sections have led to very high usability ratings by collaborating faculty. In student surveys, a surprising number of undergraduate science majors (20%--30%) report that they have never worked with authentic scientific data--even at major research universities. The percentage of students who have not worked with data is much higher at collaborating 2 y institutions (60%--80%). The majority of students report that they appreciate the opportunity to explore long-term climate science data sets despite the frustrations they experience with the "messiness" of authentic scientific data. The impact of this climate change activity is achieved through engagement with people, place, and research subjects, followed by student-centered data exploration that builds personal interest and scientific discovery skills. This paper outlines one model in which scientists can meet funding agency requirements to share data publicly while providing excellent opportunities for improving climate and data literacy at the college level. [ABSTRACT FROM AUTHOR]

This article reports collaborative research study from a small university. Twenty-seven faculty members were interviewed to determine attitudes and behaviors pertaining to using data in the classroom and whether easier access to secondary data allows for integration into a broader range of courses. The results of this study suggest a lack of awareness and skill deficits among faculty. These findings provide insights for librarians interested in working with faculty in supporting and promoting the use of open data online analysis, along with traditional quantitative data services in the social sciences and professional disciplines. Preliminary strategies developed in the year following this research study are also discussed. [ABSTRACT FROM PUBLISHER]

This article discusses possible future directions for academic libraries in the post Web/Library 2.0 world. These possible directions include areas such as data literacy, linked data sets, and opportunities for libraries in support of digital humanities. The author provides a brief sketch of the background information regarding the topics and describes how a convergence of technologies and policies has made these directions more evident than in the past. [ABSTRACT FROM PUBLISHER]