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The paper argues that learning analytics as a research field can benefit from a theory-informed shared language to describe sensemaking of learning and teaching data. To make the case for such shared language, first, I critically review prominent sensemaking theories to then demonstrate how studies in learning analytics do not use coherent descriptions of sensemaking, eclectically combining the paradigms that have underlying differences. I then propose a conceptualization of sensemaking that overcomes the differences between these theories and explains how the concepts of "activity system," the "definition of the situation" and "affordances" can be used to capture individual differences in sensemaking. The paper concludes with a preliminary framework and examples demonstrating its utility in raising new theoretical questions, informing design principles and providing shared language for researchers in learning analytics.

Education is seen as a resource at a global level but is currently considered to be in crisis in many parts of the world. This constitutes a significant drawback in terms of humanity's prosperity and well-being since education is the key not only to an educated workforce but also to humane, collaborative, and caring societies. Even within this dim landscape, there are certain educational systems that defy the odds and perform significantly higher than their otherwise comparable systems. This paper proposes using an unusual lens for educational policy comparative studies, that of positive deviance, to aid us in progressing towards a more stable educational state of affairs. Using a positive deviance methodology, which focuses on learning what is working well in systems that defy and overcome substantial challenges, this study investigates the patterns, attitudes, and actions of three selected cases: Massachusetts as a positive deviant in the US, Estonia as a positive deviant in Europe, and Castile-Leon as a positive deviant in Spain. The purpose is, by analysing educational policies, laws, and other related documents, to find commonalities that explain why these systems outperform others. The results of the comparative analysis pinpoint areas and strategies informative to those leading struggling educational systems, such as a strong commitment to equity and justice, placing teachers at the centre of reforms, using assessment as a tool for process monitoring and summative inquiry, and making preschool education accessible to all.

Chinese students studying abroad have been increasing rapidly in the past decades and become a significant financial contribution to receiving countries. Accordingly, understanding their enrollment choice is essential to facilitate college marketing and admission strategies. Though the decision process is believed to be different from domestic students, empirical analysis of Chinese students' enrollment choices is still lacking. This paper fills the void by examining the influential factors of Chinese students' enrollment choice with novel student-level data. We find that in addition to factors domestic students typically consider, such as financial aid and academic quality, Chinese students particularly emphasize college ranking, reputation, and location in their decision process. Furthermore, unlike domestic students who usually prefer colleges with proximity to home, Chinese students' location preference is linked to job prosperity. We also find that the impact of the factors varies for students from different regions of China, which can be attributable to uneven economic development within the country.

Many important questions in health professions education require datasets that are built from several sources, in some cases using data collected for a different purpose. In building and maintaining these datasets, project leaders will need to make decisions about the data. While such decisions are often construed as technical, there are several normative concerns, such as who should have access, how the data will be used, how products resulting from the data will be shared, and how to ensure privacy of the individuals the data is about is respected, etc. Establishing a framework for data governance can help project leaders in avoiding problems, related to such matters, that could limit what can be learned from the data or that might put the project (or future projects) at risk. In this paper, we highlight several normative challenges to be addressed when determining a data governance framework. Drawing from lessons in global health, we illustrate three kinds of normative challenges for projects that rely on data from multiple sources or involved partnerships across institutions or jurisdictions: (1) legal and regulatory requirements, (2) consent, and (3) equitable sharing and fair distribution.

One way to achieve equitable design is to directly include users who will be impacted the most in the planning and facilitation of a project. Common financial, logistical, and/or temporal constraints reveal that direct inclusion of the people most impacted is not always possible. If this barrier arises, one promising alternative is the creation and use of personas. Using a vignette and case study qualitative methodological approach, three researchers at a large urban university in the Pacific Northwest detail personas and journey mapping as an equitable design practice during a LMS migration on a rapid development timeline. This paper details how personas were created using empirical data, how journey mapping impacted various teams, and how centering equity better prepared staff to support instructors throughout the migration while addressing the student learning impact.

The COVID-19 pandemic has fast-tracked the development of digital applications and inspired everyone to adapt to the technologies to curb the spread of outbreak. As this crisis intensifies, the rapid usage of digital devices and apps has echoed the serious concerns about civil liberties, privacy, and data protection. Considering the situation, this research aimed to explore the internet using habits of the youths of West Bengal, a state in eastern India, during COVID-19. Besides, the paper explored their experiences of using various digital applications, the fundamental digital literacy and how safely they protect data from breaches. Thus, the paper presents the results by conducting an online survey among the youths in West Bengal. The result, from 215 participants, highlighted that the increased use of these digital applications has not matched the demand for digital privacy literacy among the young generation of the state. While this pandemic has raised their concerns over digital privacy and data protection, yet they do not undertake any strong protection mechanisms to safeguard them digitally. Besides, this paper suggests suitable plans to raise awareness among this generation and form a healthy digital citizenship with a proper regulatory framework as it is the need of the hour.

Dyslexia is the most prevalent disorder in the world that causes difficulties with reading, writing, and spelling. Pupils with dyslexia show trouble with their cognitive skills. Various interventions were already introduced for their treatment but dyslexia is still a trending disorder. The available interventions utilized for these pupils' learning open the research area for the current state-of-art of learning interventions for pupils with dyslexia. The results of this Systematic Literature Review show the trending interventions, sensory approaches utilized, and difficulties for pupils with dyslexia learning. Papers published over a period of 5 years were reviewed and their data was collected using a rigid systematic process. Based on the gathered data, several analyses were conducted. The search shows that nowadays, technological-based interventions are trending specifically apps and games, in parallel haptics technology is in its very initial stage. The most predominant sensory approaches were visual and auditory, followed by kinesthetic and tactile, mainly intervening with non-technological and technological interventions. There are still many open issues and research opportunities in the field of learning interventions for pupils with dyslexia, as most researchers utilized the visual and auditory approaches for the feedback and guidance of these pupils, while they lack to utilize the kinesthetic and tactile.

Employment and training services offered through Extension are part of and continue a long tradition of policy-focused employment and job training. This paper chronicles the successes of UT Extension's work as a third-party partner in the delivery of workforce development programming geared toward individuals receiving Supplemental Nutrition Assistance Program (SNAP) benefits. The paper begins with an overview of the federal program and a discussion of how Tennessee forged a state-level partnership for the delivery of workforce services. Data showing program success including number of participants served, supportive services offered, and economic impact are highlighted. Finally, lessons learned are outlined.

In today's data-sharing paradigm, personal data has become a valuable resource that intensifies the risk of unauthorized access and data breach. Increased data mining techniques used to analyze big data have posed significant risks to data security and privacy. Consequently, data breaches are a significant threat to individual privacy. Privacy is a multifaceted concept covering many areas, including the right to access, erasure, and rectify personal data. This paper explores the legal aspects of privacy harm and how they transform into legal action. Privacy harm is the negative impact to an individual as a result of the unauthorized release, gathering, distillation, or expropriation of personal information. Privacy Enhancing Technologies (PETs) emerged as a solution to address data privacy issues and minimize the risk of privacy harm. It is essential to implement privacy enhancement mechanisms to protect Personally Identifiable Information (PII) from unlawful use or access. FIPPs (Fair Information Practice Principles), based on the 1973 Code of Fair Information Practice (CFIP), and the Organization for Economic Cooperation and Development (OECD), are a collection of widely accepted, influential US codes that agencies use when evaluating information systems, processes, programs, and activities affecting individual privacy. Regulatory compliance places a responsibility on organizations to follow best practices to ensure the protection of individual data privacy rights. This paper will focus on FIPPs, relevance to US state privacy laws, their influence on OECD, and reference to the EU General Data Processing Regulation. (GDPR).

Longstanding inequities exist in community colleges across the United States. To address these inequities, California Community Colleges educators have engaged in a variety of practices including the writing of equity plans and participation in equity data inquiry. However, there is an urgent need for greater focus on racial equity and for more faculty involvement in equity work at the classroom level. This paper presents a teacher case study exploring Classroom Equity Data Inquiry (CEDI), a tool for faculty professional learning focused on equitable student outcomes. In CEDI, professors examine their disaggregated classroom data, reflect on their class equity gaps, and pursue relevant professional development. They implement targeted interventions and then assess those interventions. This paper describes the author's sustained CEDI utilizing six years of equity data in her English as a Second Language classes at a small northern California community college. First, it provides a definition and rationale for CEDI. Second, it details the author's CEDI process and challenges. Third, it shares the author's changes in thinking and practice including high impact interventions the author implemented to reduce equity gaps for men of color in her classes. Fourth, the article describes positive qualitative student data and increased success and retention rates for Hispanic and multi-race males following the interventions. The article concludes that CEDI requires training, support, and time, but that the approach merits further research. More research is needed on CEDI methods and their possible impact on racial equity in the classroom.

An increasingly complex and demanding research landscape has seen university libraries rapidly evolve their services. While research data management, bibliometrics, and research impact services have predominantly featured in the literature to date, the full scope of support libraries are currently providing to their institutions is unknown. This paper aims to present an up-to-date view of the scope and extent of research support services by university libraries across Australia and Aotearoa New Zealand. A coding process analyzed content data from university library websites. Eleven research support areas were identified. Service delivery is split between synchronous and asynchronous modes. This paper describes a lived experience of an evidence-based library and information practice approach to improving research support services at two Australian university libraries, and while it highlights continued maturation of research support services, more research is needed to better understand influences on service development.

This paper proposes an online learning platform learner DM method based on the improved fuzzy C clustering (FCM) algorithm, constructs a learner feature database, and combines clustering analysis and SPSS statistical methods to statistically summarize the big data of law, thus improving the deficiencies of static and absolute classification of students in the student model. In the experiment paper, the improved algorithm is implemented and the experimental data is analyzed. The results show that the learner behavior feature extraction model in this paper has fewer errors and higher recall rate. Compared with the traditional CF algorithm, the error rate is reduced by 19.64% and the recall rate is increased by 22.85%. This study provides better targeted teaching programs and case resources for legal case teaching and promotes the innovation of legal case teaching mode.

Purpose: In today's digital world, data-driven digital artefacts pose challenges for education, as many students lack an understanding of data and feel powerless when interacting with them. This paper aims to address these challenges and introduces the data awareness framework. It focuses on understanding data-driven technologies and reflecting on the role of data in everyday life. The paper also presents an empirical study on young school students' data awareness. Design/methodology/approach: The study involves a teaching unit on data awareness framed by a pre- and post-test design using a questionnaire on students' awareness and understanding of and reflection on data practices of data-driven digital artefacts. Findings: The study's findings indicate that the data awareness framework supports students in understanding data practices of data-driven digital artefacts. The findings also suggest that the framework encourages students to reflect on these data practices and think about their daily behaviour. Originality/value: Students learn a model about interactions with data-driven digital artefacts and use it to analyse data-driven applications. This approach appears to enable students to understand these artefacts from everyday life and reflect on these interactions. The work contributes to research on data and artificial intelligence literacies and suggests a way to support students in developing self-determination and agency during interactions with data-driven digital artefacts.

The field of learning analytics has advanced from infancy stages into a more practical domain, where tangible solutions are being implemented. Nevertheless, the field has encountered numerous privacy and data protection issues that have garnered significant and growing attention. In this systematic review, four databases were searched concerning privacy and data protection issues of learning analytics. A final corpus of 47 papers published in top educational technology journals was selected after running an eligibility check. An analysis of the final corpus was carried out to answer the following three research questions: (1) What are the privacy and data protection issues in learning analytics? (2) What are the similarities and differences between the views of stakeholders from different backgrounds on privacy and data protection issues in learning analytics? (3) How have previous approaches attempted to address privacy and data protection issues? The results of the systematic review show that there are eight distinct, intertwined privacy and data protection issues that cut across the learning analytics cycle. There are both cross-regional similarities and three sets of differences in stakeholder perceptions towards privacy and data protection in learning analytics. With regard to previous attempts to approach privacy and data protection issues in learning analytics, there is a notable dearth of applied evidence, which impedes the assessment of their effectiveness. The findings of our paper suggest that privacy and data protection issues should not be relaxed at any point in the implementation of learning analytics, as these issues persist throughout the learning analytics development cycle. One key implication of this review suggests that solutions to privacy and data protection issues in learning analytics should be more evidence-based, thereby increasing the trustworthiness of learning analytics and its usefulness.

The paper introduces a novel approach to university rankings that considers a university's contribution to sustainable development. It addresses the usual controversies surrounding the construction of rankings using composite indicators. The conventional approach typically involves normalizing sub-indicators and applying subjective weights for aggregation, which raises concerns about the reliability of the rankings. In response to this issue, we propose an alternative method based on Data Envelopment Analysis (DEA) that utilizes flexible weights. Our approach is applied to the data from the UI-GreenMetric World University Ranking. We initially employ a general Benefit of the Doubt DEA model and subsequently enhance its discrimination power by computing super-efficiency. In the third model, we impose weight restrictions on sub-indicators. The results of our analysis offer valuable insights for all stakeholders, as illustrated by the implications derived for Czech universities included in the sample. Furthermore, we compare the results of universities in various European countries, establishing a connection between rankings and the fulfillment of Sustainable Development Goals (SDG) within individual countries. This research contributes to a more comprehensive understanding of the relationship between university performance, sustainability, and the associated implications for policy and benchmarking.

In using software to write a scientific, technical, or other scholarly document, authors have essentially two options. They can either write it in a 'what you see is what you get' (WYSIWYG) editor such as a word processor, or write it in a text editor using a markup language such as HTML, LATEX, Markdown, or AsciiDoc. This paper gives an overview of the latter approach, focusing on both the non-visual accessibility of the writing process, and that of the documents produced. Currently popular markup languages and established tools associated with them are introduced. Support for mathematical notation is considered. In addition, domain-specific programming languages for constructing various types of diagrams can be well integrated into the document production process. These languages offer interesting potential to facilitate the non-visual creation of graphical content, while raising insufficiently explored research questions. The flexibility with which documents written in current markup languages can be converted to different output formats is emphasized. These formats include HTML, EPUB, and PDF, as well as file formats used by contemporary word processors. Such conversion facilities can serve as means of enhancing the accessibility of a document both for the author (during the editing and proofreading process) and for those among the document's recipients who use assistive technologies, such as screen readers and screen magnifiers. Current developments associated with markup languages and the accessibility of scientific or technical documents are described. The paper concludes with general commentary, together with a summary of opportunities for further research and software development.

OBE concept is a new teaching mode which emphasizes the improvement of students' subjective initiative and professional practice ability. The teaching of animation course is based on drawing and computer, which requires teachers to understand the OBE mode of animation course, carry out targeted teaching innovation of animation course, and adjust the traditional teaching methods, teaching contents and teaching assessment methods. Based on the MOOC platform from the perspective of big data, this paper analyzes the teaching status and innovation process of animation course, and puts forward a hybrid animation course teaching method. Through the research of 686 primary and secondary school teachers, the results show that the hybrid animation course teaching based on OBE and MOOC from the perspective of big data has a better effect than the traditional teaching method, which improves students' initiative in learning animation courses and greatly enhances students' acceptability in learning animation courses.

The level of information technology is increasing, and technology is developed. University English teaching has also changed under its influence. Different from the traditional teaching in the past, more and more students adopt the mode of "Internet + Smartphone" to learn English. This paper proposes a teaching mode evaluation method in the context of big data. Through the K-means algorithm based on it, the data clustering of business English teaching mode is completed. According to the data obtained from clustering, combined with the standardization of positive and negative indicators, the business English teaching mode system is constructed. Experiments show that when the clustering K value is 16, the clustering accuracy of this method is 99.2%, and it can effectively get the index weights, and the evaluation time is short, which is better than the other two comparison methods.

Recently, there has been increasing interest in comparing educational leadership measures, such as principal school leadership, using International Large-Scale Assessments (ILSAs) data. However, there are doubts about the uniformity of measurement across countries participating in the ILSAs. There are concerns that the robustness and psychometric characteristics of measures are adversely affected by socio-cultural, economic, political, and linguistic diversity across countries. The current study examines the uniformity of cross-cultural model data for the "principal instructional leadership scale" using the framework and data supplied by the Organization for Economic Cooperation and Development (OECD)'s Teaching and Learning International Survey is employed to estimate the conceptual measurement model and test measurement invariance across forty-eight countries. Countries are then divided countries into more homogenous groups, based on their socio-demographic characteristics, to test measurement invariance within these sub-groups. The results of this study reveal that, when testing for the forty-eight countries together, the scale measuring principals' school leadership is invariant across all countries only at an intermediate level (i.e. metric). This means the factor structures and the factor loadings are equivalent across countries, but the item intercepts are not. However, when testing within sub-groups, improvements in cross-cultural comparability are found. This paper concludes by making suggestions on scale improvement, discussing the implications of this study for policymaking and making recommendations for future research.

While the co-production of knowledge through community-engaged research is intended to be a reciprocally beneficial process, academic institutions have often devalued community expertise by treating community organizations as subjects rather than co-creators of knowledge. Drawing from Black Feminist Epistemology, this ethnographic study examines how one community-based organization, Los Angeles Community Action Network (LA CAN), partners with academic researchers, including their discourse around partnerships and how they challenged power dynamics between community and their university partners. This paper discusses key themes from their partnerships, including centering community members' expertise through their lived experience and forming long-term mutual relationships rooted in abolition and the Black Radical Tradition. Drawing on an analysis of LA CAN's organizing and research processes with academic partners, we discuss how the centering of community expertise and forming relationships with academics aligned on these values can help to challenge the traditional power dynamics in community-university partnerships, resulting in different ways of knowing or what LA CAN referred to as "the real data set."

This paper investigates changes in the promissory visions articulated in education reforms around the world. We use structural topic modeling to inductively analyze the content of 9,268 reforms from 215 countries and territories during the period 1970-2018 using the World Education Reform Database. Our findings reveal a decline in traditional management-focused reforms and a rise in reforms related to data and information. We also find an expanding commitment to educational access and inclusion, but reforms framed explicitly in 'rights' language diminish. We argue that the rise of data-centric reforms and the retreat from rights-based approaches may both reflect and contribute to a broader erosion of the liberal world order.

The pressure towards digital education is felt everywhere including in places with extreme digital divides. Resource-constrained educational environments are particularly threatened by datification manifest in the dominant business models of surveillance capitalism as there is less room in such contexts to refuse the 'free' offerings from big tech companies; it is these very contexts which are most vulnerable. Yet educators within such environments are not mere pawns of circumstance. While the realities of their structural constraints may be invisible or obfuscated, educators are driven by their own 'concerns', which in this case pertain to the needs of diverse students in very challenging circumstances as well as to their personal aversion to being monitored. This paper reports on findings from focus groups in a mixture of institutionsin South African education. Archer's theoretical framework provides a lens to show how, despite very little choice, educators critically reflect on their circumstances expressing discomfort and unease.

Text and data mining activities -- that is, the automated processing of digital materials to uncover new knowledge -- have become more frequent in all areas of scientific research. Because they require a massive use of copyrighted work, there are evident conflicts with copyright legislation. Countries at the forefront of research and development have begun to address this issue. This paper presents the basic aspects of legislation applicable to text and data mining activities. It offers a detailed comparative analysis of the norms of the main jurisdictions that have regulated them to date, highlighting in each case the positive and negative aspects. An adequate knowledge of these laws is not only important for researchers but also important for the academic librarians who provide advice and support in these matters.

School exclusion reduction in Scotland--and especially in the city of Glasgow--has received substantial media and policy attention in recent years. In London in particular, multiple governmental agencies have explicitly expressed a desire to replicate the exclusion reduction which recently occurred in Glasgow, often citing the connection between school exclusion and violence as a key motivating factor. In this paper, after presenting the statistical trends in school exclusions in Scotland, England, Glasgow and London, we mobilise original interview data to (1) explain how school exclusion reduction occurred so rapidly in Glasgow between 2007 and 2019, and (2) explore whether a similar reduction in exclusions could occur in contemporary London. We apply a theoretical framework to these issues which derives from Peters' work on policy coordination, allowing us to compare the conditions in Glasgow and London for well-coordinated pan-city exclusion reduction. Building on previous research which has contrasted national school exclusion policies in Scotland and England, we conclude that policy conditions surrounding school exclusion in the two cities differ substantially. There are substantial barriers to significant exclusion reduction in London, relating to both city- and national-level factors. There barriers include competition between different agencies working in relevant policy spaces; the fragmentation of the city's education system; the need for better incentivisation of inclusion by Ofsted and the Department for Education; and particular challenges to reframing the issue of school exclusion in London.

Purpose: In light of a need for more critical education about datafication, this paper aims to develop a framework for critical datafication literacy that is grounded in theoretical and empirical research. The framework draws upon existing critical data literacies, an in-depth analysis of three well-established educational approaches - media literacy, the German "(politische) Bildung" and Freirean "critical pedagogy" - and empirical analyses of online educational resources about datafication. Design/methodology/approach: The study interconnects theoretical analyses with an empirical mixed methods investigation that includes expert interviews with creators of online educational resources about datafication and a qualitative survey with educators interested in teaching about data technologies. Findings: The research identified novel findings on the goals of resource creators and educators, such as a focus on empowering and emancipatory approaches, fostering systemic understanding of datafication and encouraging collective action. Such perspectives are rare in existing critical data literacy conceptualisations but show resemblance to traditional education scholarship. This highlights how much can be learnt from practitioners and from these more established educational approaches. Based on these findings, a framework for critical datafication literacy is suggested that aims for systemic understanding of datafication, encouraging critical thinking and enabling learners to make enlightened choices and take different forms of action. Originality/value: The study is unique in its interconnection of theoretical and empirical research, and it advances previous research by suggesting a grounded framework for critical datafication literacy.

Internet users are becoming ignorant with their data and the transparency of information due to the nature of high-speed internet today. Regrettably, internet users are deceived by engineering tactics performed by highly trained people, namely cybercriminals. Thus, in order to combat phishing attacks, internet users should be educated on security concerns, the influence of social engineering and anti-phishing knowledge. This paper presents a literature review of phishing, a type of cyber fraud, covering the types of phishing, the implications and governance. This study benefits the public to mitigate phishing attacks and increase phishing awareness.

This paper reports on the perceptions of Spanish academic libraries regarding Open Science (OS). OS is irrupting into academia and academic librarians need to support researchers. On the other side, researchers need to be ready to change their scientific behaviour in relation to publications and research data. We conducted a focus group with 8 academic librarians. We also sent a survey to (N = 67) academic libraries, obtaining a response rate of 71.6%. In the survey, we asked for drivers and constraints for OS services as well as for any training taking place. Our results show that facilitators are the system relationships (SD = 4.74) and internal promotion of systems relationships (SD = 4.54). In relation to the level of knowledge of OS, both researchers (SD = 3.27) and librarians have a high level in terms of the OA area (SD = 4.15) but little development of the rest of the components of OS. On the other hand, in relation to training librarians, results indicated that OA (SD = 4.79), Open Data (SD = 4.79) and new evaluation models (SD = 4.79) should be part of the training for researchers. The results of the focus group reinforce some of the indicators mentioned. We conclude that academic libraries may train researchers in OS through the acquisition of new skills and trainers-training and with the strategic support of the university. We argue that academic incentives and a change in research accreditation are also needed to shift researchers' perceptions in relation to OS.

Purpose: Upon graduating from university, many engineers will work in new product development and/or technology adoption for continuous improvement and production optimization. These jobs require employees to be cognizant of ethical practices and implications for design. However, little engineering coursework, outside the traditional ABET (Accreditation Board for Engineering and Technology) required Engineering Ethics course, accounts for the role of ethics within this process. Because of this, engineering students have few learning opportunities to practice and reflect on ethical decision-making. Design/methodology/approach: This paper highlights one approach to integrating ethics into an engineering course (outside of engineering ethics). Specifically, the study is implemented within a five-week module with a focus on big data ethics, as part of a Supply Chain Management Technology course (required for Industrial Engineering Technology majors), using metacognition as the core assessment. Findings: Four main themes were identified through the qualitative data analysis of the metacognitive reflections: (1) overreliance on content knowledge, (2) time management skills, (3) career connections and (4) knowledge extensions. Originality/value: Three notable points emerged which contribute to the literature. First, this study showcased one example of how an ethics module can be integrated into an engineering course (other than Engineering Ethics). Second, this study demonstrated how metacognitive reflections can be used to reinforce student self-awareness of the learning process and connections to big data ethics in the workplace. Finally, this study exhibited how metacognitive reflection assignments can be deployed as a teaching and learning assessment tool, providing an opportunity for the instructor to make immediate changes as needed.