Data Literacy

Data are increasingly important in central facets of modern life: academics, professions, and society at large. Educating aspiring minds to meet highest standards in these facets is the mandate of institutions of higher education. This, naturally, includes the preparation for excelling in today’s data-driven world. In recent years, an intensive academic discussion has resulted in the distinction between two different modes of data related education: data science and data literacy education. As a large number of study programs and offers is emerging around the world, data literacy in higher education is a particular focus of this paper. These programs, despite sharing the same name, differ substantially in their educational content, i.e., a high plurality can be observed. This paper explores this plurality, comments on the role it might play and suggests ways it can be dealt with by maintaining a high degree of adaptiveness and plurality while simultaneously establishing a consistent educational “essence”. It identifies a skill set, data self-empowerment, as a potential part of this essence. Data science and literacy education are still experiencing changeability in their emergence as fields of study, while additionally being stirred up by rapid developments, bringing about a need for flexibility and dialectic.

List of Contributors. Editorial Advisory Board. Preface. Introduction - Information Literacy and Information Behaviour, Complementary Approaches for Building Capability. Transforming Information Literacy for Higher Education in the 21st Century: A Lifelong Learning Approach. Curriculum and Curriculum Integration of Information Literacy in Higher Education. The Construction of Information and Media Literacy in Education Policy: A Study of Singapore. Information Literacy in Higher Education: Research Students' Development in Information Search Expertise. Mediating Culture: Media Literacy and Cultural Awareness The Representation of Race and Ethnicity in Maya and Miguel. Empowering Professional Practices of a Community of e-Learners: Special Education Teachers in Alaska and their Information Literacy Conceptions. Information Literacy of Undergraduate Students in Thailand: A Case of the Faculty of Arts, Silpakorn University, Thailand. Building Partnerships for Information Literacy among HE Institutions in African Universities: Opportunities and Challenges - A Case Study. Perspectives on Legal Education and the Role of Information Literacy in Improving Qualitative Legal Practice. Information Literacy in the Business School Context: A Story of Complexity and Success. Workplace Reflections of Information Literacy Training: The Case of the Agriculture and Health Sectors in Tanzania. Workplace Information Literacy: It's Different. Diversifying Information Literacy Research: An Informed Learning Perspective. The Use of Participatory Techniques in the Communication of Information for Communities: Information Literacy and Collaborative Work for Citizenship Development. About the Authors. Developing People's Information Capabilities: Fostering Information Literacy in Educational, Workplace and Community Contexts. Library and Information Science. Developing People's Information Capabilities: Fostering Information Literacy in Educational, Workplace and Community Contexts. Copyright page. Index.

Accessing, using and managing data is increasingly recognized as an important learning outcome in higher education. Approaches to data literacy have typically been informed by information literacy. New approaches to information literacy have emerged that address how information is used in the different disciplinary contexts in which people learn and work. Successful approaches to data literacy will also need to address contextual concerns. Informed learning is an approach to information literacy that purposefully addresses contextual concerns by suggesting pedagogic strategies for enabling students to use information in ways that support discipline‐focused learning outcomes. As part of an ongoing investigation, we advance data informed learning as a framework for data literacy in higher education that emphasizes how data are used to learn and communicate within disciplinary learning contexts. Drawing from informed learning, we outline principles and characteristics of data informed learning, and suggest future directions to investigate ways that data are used in real‐world environments.

This research aims to explore the level of artificial intelligence (AI) literacy and ethical awareness among university students in Indonesia, focusing on their understanding of AI as well as the ethical challenges associated with its use in education and daily life. Using a mixed-methods approach, this study collected quantitative data through a survey involving 300 students from various universities in Indonesia and qualitative data through in-depth interviews with 30 selected respondents. The results show that although AI literacy among students from engineering majors is quite high, students from non-engineering majors show lower understanding. In addition, there are significant concerns regarding ethical issues such as data privacy, algorithmic bias, and the social impact of AI. The study also identified several key challenges, including the lack of integration of AI literacy in higher education curricula and limited training related to AI ethics. Based on these findings, this study recommends the need to strengthen a curriculum that includes AI literacy and comprehensive ethics education in all departments. This research contributes to the development of a more inclusive and responsible education policy in facing the digital era in Indonesia.

As higher education undergoes rapid digital transformation, digital literacy has become a foundational competency for students and faculty. This systematic review synthesizes the ways in which pedagogical innovations and institutional strategies support digital literacy in higher education. We draw on 62 empirical studies published between 2014 and 2025, following PRISMA reporting standards. We identify eight thematic domains: teacher identity, learner agency, pedagogical innovations, institutional strategies, faculty competence, student engagement, assessment practices, and implementation barriers. The synthesis is grounded in DigComp, DigCompEdu, the Technology Acceptance Model, and connectivism. Flipped classrooms, gamification, and multimodal instruction are consistently associated with improvements in digital competence and student motivation. Faculty development and institutional leadership are pivotal enablers of sustainable digital literacy integration. Persistent challenges include infrastructure limitations, policy misalignment, and cultural resistance, particularly in under-resourced settings. This review offers policy-relevant insights for curriculum design and institutional reform, advocating for context-responsive strategies to integrate digital literacy. Limitations include reliance mainly on Scopus-indexed literature and heterogeneity of study designs, which precluded meta-analysis. We recommend longitudinal and comparative studies to examine long-term impacts.

This study aims to describe the understanding of geography literacy and student experience with landscape recognition observations using an ethnometodology perspective. The subject of this study was the chairman of each landscape recognition practice group student geography education program from University of Jember. The results of this study that geography literacy has a dimension of relevance to geographic skills in representing contextual phenomena and places from landscape recognition observation activities. The results of both observational studies provide research experience, motivation, critical and scientific thinking skills for students represented in the mapping of the area.
 Keywords: Geography Literacy, Student Experience, Ethnometodology
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Quantitative literacy has been recognized as an important skill in the higher education and workforce communities, focusing on problem solving, reasoning, and real‐world application. As a result, there is a need by various stakeholders in higher education and workforce communities to evaluate whether college students receive sufficient training on quantitative skills throughout their postsecondary education. To determine the key aspects of quantitative literacy, the first part of this report provides a comprehensive review of the existing frameworks and definitions by national and international organizations, higher education institutions, and other key stakeholders. It also examines existing assessments and discusses challenges in assessing quantitative literacy. The second part of this report proposes an approach for developing a next‐generation quantitative literacy assessment in higher education with an operational definition and key assessment considerations. This report has important implications for higher education institutions currently using or planning to develop or adopt assessments of quantitative literacy.

This study examines trends in digital literacy research within higher education from an Islamic perspective while identifying opportunities for its development. Employing a Systematic Literature Review (SLR) method, 188 articles were sourced from Scopus, Sinta 1, and Sinta 2 databases, with 37 articles published between 2019 and 2024 meeting the inclusion criteria for analysis. Guided by the PRISMA framework, the review ensured the validity and reliability of findings, while bibliometric analysis was conducted using VOSviewer 1.6.20. The analysis revealed a sharp increase in publications during 2021, attributed to the rapid digital transformation of higher education amid the COVID-19 pandemic. However, it also highlighted a significant gap in integrating Islamic education with digital technology, despite its potential to improve learning outcomes and quality. The majority of publications originated from Indonesia, China, and Russia, with both quantitative and qualitative approaches dominating the methodologies. These findings offer valuable insights into the evolving landscape of digital literacy in higher education and emphasize the critical need for further research to advance its holistic development.

The study aimed to design and analyze the three-layer structure of themes (comprehensive, organizing, and basic) in the ecotourism curriculum with a focus on promoting environmental literacy in higher education. This exploratory mixed-method study was conducted in two phases: qualitative and quantitative. In the qualitative phase, semi-structured interviews were conducted with 18 experts and faculty members in ecotourism, tourism, and curriculum studies. The data were analyzed using network-based thematic analysis. In the quantitative phase, data were collected from 384 experts, graduates, and postgraduate students using a structured questionnaire. The data were analyzed through confirmatory factor analysis and structural equation modeling using SPSS and SmartPLS. Qualitative findings identified five comprehensive themes: learning perspectives, the body of ecotourism knowledge, teaching–learning strategies, learning assessment and monitoring, and environmental competencies and skills. Confirmatory factor analysis validated 20 organizing themes and 76 basic themes. Model fit indices (NFI=0.968, GOF=0.557, SRMR=0.002) confirmed the structural soundness of the three-layer framework. Significant positive correlations were found among all themes and the environmental literacy–based ecotourism curriculum. The three-layer thematic framework provides a coherent model for ecotourism curriculum design in higher education. By integrating environmental literacy principles, it fosters deeper learning, responsible environmental attitudes, and enhanced ecological competencies among students. The model can be effectively applied in other interdisciplinary fields such as environmental management and sustainable tourism education.

Universities around the world are encouraging teachers to provide more constructive feedback to support student learning, but do teachers know how to distinguish constructive feedback? What pedagogical practice is considered as feedback and what is not? For example, is a rubric a type of feedback? To date, very limited research has answered these questions from university teachers’ perspectives and the current study aims to address this gap. In this study, ten teacher training workshops were conducted in a university in Hong Kong, with an intention to enhance teachers’ competence in assessment and feedback. During the workshops, we first adopted Poll Everywhere to survey whether teachers (N = 248) recognise six types of common pedagogical practices as feedback, and subsequently used this as a base to discuss with teachers the reasons behind their responses. Findings reveal teachers’ varied perceptions of these practices as feedback, which may be related to their varied understandings of feedback purposes. The paper calls for an explicit acknowledgement of the multiple purposes of feedback, and concludes with implications for teacher feedback literacy in higher education.

This paper introduces the 'SkillSense for Assessment Mastery (SSAM) Programme©’ designed to teach assessment literacy in higher education, outlining its theoretical rationale and research-informed insights for its implementation. The SSAM Programme aims to enhance understanding of the learning process, offer personalized support, and align assessments with academic skills. Prioritizing fairness and diversity, it fosters a sense of belonging in the academic Community of Practice (CoP). The programme includes workshops with presentations, peer, and self-assessment activities based on the purposefully designed Academic Skills Feedback and Marking Rubric (ASR). Emphasis is on the vital importance of cultivating students' self-efficacy and essential skills. The initiative focuses on scaffolding reflective learning, utilizing quantitative and qualitative data for its ongoing evaluation. Empirical insights from this continuous evaluation within a UK Higher Education Institution during 2022-24 will also be presented briefly in this paper to demonstrate its effectiveness in promoting student development.

As generative AI tools become increasingly integrated into higher education, understanding how students engage with AI-generated feedback is essential for rethinking and redesigning English writing practices. This study introduces AI feedback literacy (AIFL) to describe EFL learners’ ability to interpret, evaluate, and apply automated feedback effectively. Drawing on feedback literacy theory and motivational frameworks, such as self-determination and cost-value models, a psychometric scale was developed and validated with data from 486 university students. Analyses using confirmatory factor analysis, mediation modelling, and multiple regression revealed that AIFL significantly predicts students’ uptake of AI-generated feedback, both directly and indirectly through motivational appraisals. Behavioural engagement emerged as a stronger predictor than attitudinal disposition, emphasising the importance of situated practice. AIFL was shaped not by demographic background but by frequency of AI use, raising equity concerns about access and opportunity. Overall, the findings suggest that meaningful engagement with AI feedback depends less on technological access and more on learners’ readiness, confidence, and experience, offering implications for designing assessment environments that promote feedback literacy, and for equipping teachers to mediate AI tools effectively.

Enhancing students’ assessment literacy is essential in enabling all students to manage their learning successfully. Understanding of the assessment standards required and how to meet them impacts students’ learning outcomes within higher education (HE). However, there are many different conceptions of what assessment literacy comprises, making it difficult to provide guidance on the most effective approaches to enhancing student and academic understanding of this complex and multifaceted concept. With this concern in mind, we investigated the psychometric properties of an assessment tool and its suitability for use within the context of implementing and evaluating pedagogical interventions aimed at enhancing students’ and academics’ assessment literacy skills. The validity of the tool was confirmed using exploratory and confirmatory factor analyses. Furthermore, the identified relationship between assessment literacy and feedback elements of the tool confirms the importance of an integrated approach to assessment. Drawing on extensive piloting of the tool across disciplines we highlight the importance of pedagogical co-construction approaches that promote shared understandings of assessment literacy between students and academics. Suggestions for further enhancement of this measure are proposed with the aim of supporting academics’ and students’ shared understandings and development of assessment literacy.

Purpose Generative Artificial Intelligence (AI), gamification, and digital literacy have transformed higher education by enhancing student engagement, personalizing learning, and fostering digital competencies. This study investigated the impact of three dimensions of Generative AI—knowledge, willingness, and concerns—on students’ perceptions of learning and academic performance in Saudi Arabia. It also explores the roles of gamification and digital literacy. Both Gamification and digital literacy moderate the relationship between Generative AI and educational outcomes, whereas digital literacy affects the association between AI factors and students' perceptions of learning and performance. Design/methodology/approach A quantitative research design was adopted to collect data from 550 postgraduate students across various Saudi universities and disciplines. This cohort was chosen because of its heightened capacity to engage critically with advanced educational technologies. Employing two analytical approaches, the measurement model (validity and reliability) and structural equation modelling (hypothesis testing), statistical analysis was used to assess the relationships. Findings The results demonstrated that all the proposed relationships were significant. Knowledge, willingness, and concerns regarding generative AI were positively related to both PLE and PAP (H1: β = 0.328, p = 0.000), (H2: β = 0.192, p = 0.001), (H3: β = 0.294, p = 0.000), (H4: β = 0.149, p = 0.002). (H5: β = 0.138, p = 0.003) respectively. In addition, gamification and digital literacy exhibited significant moderating effects, as indicated in the results section, amplifying the positive impact of AI integration on students’ academic perceptions and outcomes. Originality/value This study provides empirical evidence of the interplay between Generative AI, gamification, and digital literacy in higher education, delivering practical insights for policymakers, educators, and technology developers. This underscores the importance of digital literacy training programs and policies promoting responsible, gamified AI integration, enhancing effective and inclusive learning environments in Saudi Arabia and beyond.

In today’s society, workplace, and scientific environment, data is increasingly regarded as a highly valuable often the most valuable resource. Decisions are progressively being made on the basis of data. Digitalisation and datafication are reshaping life and work in the 21st century: artificial intelligence, networked production, communicating machines, and autonomous vehicles all rely on data while simultaneously generating vast amounts of it. Data thus forms the foundation for knowledge creation, value generation, and better decision-making. Therefore, data literacy must be cultivated from the start of higher education and across all disciplines. The present study is aimed to find out the data literacy of the university students in Pakistan furthermore to compare the data literacy of applied and social science students at BS level. For the purpose, a total six academic departments three from the applied sciences (Biotechnology, Chemistry, and Zoology) and three from the social sciences (Education, Psychology, and Sociology). A sample size of 360 (180 students from each applied and social science) were selected. IDL was used as data collection tool. Results showed that overall data literacy levels are low across both groups, with social science students demonstrating relatively higher proficiency. From inferential data analysis no significant difference in data literacy between applied science and social science students at the BS level was found. It is recommended that universities should organize workshops and training sessions for teachers; facilitated Enhancing faculty proficiency in statistical tools will directly contribute to improving students’ understanding and use of data literacy software such as SPSS, STATA, and R. The Higher Education Commission of Pakistan (HEC) is encouraged to integrate a dedicated unit on data analysis software including SPSS, STATA, and R into relevant undergraduate programs.