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In Germany, principals’ working environments are data-rich for school improvement purposes in a rather low-stakes test-regime. An effective use of externally as well as internally generated data, also known as data wise leadership, is considered to be a key competence of successful principals. The purpose of this paper is to describe data use practices in German schools, especially focussing on schools facing challenging circumstances.

The paper draws on findings from two projects funded by the German Federal Ministry of Education and Research. A standardized questionnaire study was conducted to measure the usage of available data for school improvement quantitatively. The perceived usefulness, the reflection upon, and the use of information sources by principals were measured. Moreover, semi-structured interviews with school leaders from schools in deprived areas were conducted, transcribed and analyzed by means of qualitative content analysis.

The results showed that internal sources of information were used frequently while (international) student assessment, statewide comparative tests, and school inspections proved to be of relatively little use for the principals’ professional practice. Moreover, there was a discrepancy between the perceived usefulness of information sources and the actual use of the data.

In contrast to the USA, for example, research on educational leadership and principals’ data use – particularly at schools in challenging circumstances – is rather limited in Germany. This paper seeks to take up this desideratum.

An increasing number of schools and districts across the US are requiring teachers to collaborate for the purpose of data‐driven decision making. Research suggests that both data use and teacher collaboration are important ingredients in the school improvement process. Existing studies also reveal the complexities of teacher collaboration and the importance of context in shaping teachers’ collaborative work, especially with data. Yet, the intersection of teacher collaboration and data use has been understudied. The purpose of this paper is to examine the affordances and constraints that exist in the context of established teacher collaboration time for the purposes of data‐driven decision making.

The paper draws upon qualitative case study data gathered in six schools that structured teacher time for collaboration on data use.

An analysis of the data revealed that a variety of leadership activities and organizational conditions shaped teachers’ collaborative work with data. These included leadership focused on thoughtful use of data and the framing of data‐driven decision making in terms of collective responsibility; the establishment of norms for teacher collaboration; the implementation of data discussion protocols; and teacher groupings and subject matter subcultures.

Knowing how and when a leadership activity or organizational condition becomes either an affordance or a constraint to teacher collaboration around data use has important implications for leadership and educational change. The findings of this study also help to lay the groundwork for future research regarding teacher collaboration around data use.

School improvement planning and implementation is one organizational process by which principals may positively impact school and student outcomes. Limited research, however, has explored how principal preparation programs prepare aspiring leaders for this common school leadership activity. This study examined aspiring principals engaged in the school improvement process by evaluating what they included in their school improvement plans (SIPs) that were developed as part of their field experience.

The authors examined SIPs aspiring principals collaboratively developed as part of their field experience. Using an abductive analysis method, combining both deductive and inductive coding methods, authors examined 77 SIPs in which aspiring principals used school level data in planning.

Each aspiring principal's SIP was contextually specific. No two plans were identical relative to who was targeted for improvement and how the plan was to be implemented, indicating aspiring principals can apply course-based learning and implement important data-driven decision-making skills in field-based school improvement projects.

Findings are exploratory and limited to SIPs developed by aspiring principals in one university program in one large urban school district context. The findings that specific requirements and program structures affected the aspiring principal's school improvement planning process as did the overall school context adds to current understandings of how course-based learning is applied. However, further investigations are needed.

Findings provide evidence of how school leadership preparation programs may impact leadership development relative to skills associated with school improvement planning. The findings also suggest the importance of detailed analysis of aspiring principals school improvement planning as a program evaluation process.

This study was the first to document the content of aspiring principals' field-based SIPS and how skills in data-driven decision-making were applied in a SIP field-based activity.

Reflecting the Mauritian government's “quality” agenda and its focus on school leadership, this paper reports the findings of research exploring Mauritian principals’ views about the use of total quality management (TQM) for school improvement. While aspects of this research have been reported elsewhere, the purpose of this paper is to focus on school leaders’ use of data and evidence in making decisions for school improvement.

The paper reports on qualitative aspects within a mixed methods research with data collected by means of semi-structured interviews conducted with a purposive sample of six principals. The analysis of the data were an exercise in grounded theory building.

The paper expands the knowledge of principals as quantitative data users arguing that qualitative information based on professional discourses, human judgements and lived experiences should be equally valorised if TQM is used for making informed educational decisions.

The research relied on principals’ views as the unique source of data. The perspectives of the other stakeholders would offer a richer description of leadership reality in Mauritian schools.

The paper suggests a more participatory decision-making model for effective change that could rightfully engage all stakeholders through various complementary quantitative and qualitative processes. It further recommends that alongside the core systemic qualities of TQM, there are ethical, moral and cultural dimensions of leadership that could enhance the teaching and learning environment.

While confirming some extant research, the paper brings new thinking to understanding the critical role of principals within the TQM scenario of data-driven decision making.

A literature review of 28 data literacy, education articles from 2010 to 2018 was conducted to gain a better understanding of the current state of data literacy research.

A systematic literature review of ERIC, Education Source, and JSTOR was conducted. Articles were included in this literature review if they focused on “data literacy” for K-12 teachers or leaders.

Results demonstrated that the concept of data literacy has become more concrete, but there is still disagreement about the parameters of the construct. While data literacy was shown to be gaining in importance, training from schools of education were focused heavily on assessment literacy. Four recommendations are made as follows: (1) create skill-focused educator prep programs, (2) encourage opportunities for collaboration, (3) model data use from both quantitative and qualitative sources and (4) investigate the role of technology and big data on data literacy.

The scope of this literature review was very narrow and, as such, does not fully encapsulate data-driven decision-making in K-12 education overall.

Data literacy is important for both teachers and leaders, as educational environments strive to better understand individual learners and improve learning outcomes. This literature review looks to pull together the current status of data literacy research with hopes of inspiring more targeted research that influences training practices for both teachers and leaders.

Currently, in the education data use literature, there is a lack of research and examples that consider the early steps of filtering, organizing and visualizing data to inform decision-making. The purpose of this study is to describe how school leaders and researchers visualized and jointly made sense of data from a common learning management system (LMS) used by students across multiple schools and grades in a charter management organization operating in the USA. To make sense of LMS data, researchers and practitioners formed a partnership to organize complex data sets, create data visualizations and engage in joint sensemaking around data visualizations to begin to launch continuous improvement cycles.

The authors analyzed LMS data for n = 476 students in Algebra I using hierarchical cluster analysis heatmaps. The authors also engaged in a qualitative case study that examined the ways in which school leaders made sense of the data visualization to inform improvement efforts.

The outcome of this study is a framework for informing evidence-based improvement cycles using large, complex data sets. Central to moving through the various steps in the proposed framework are collaborations between researchers and practitioners who each bring expertise that is necessary for organizing, filtering and visualizing data from digital learning environments and administrative data systems.

The authors propose an integrated cycle of data use in schools that builds on collaborations between researchers and school leaders to inform evidence-based improvement cycles.

When school leaders advance strategic plans focused on improving educational equity through data-driven decision making, how do policies-as-practiced unfold in the daily work of science teachers? The paper aims to discuss this issue.

This ethnographic study examines how data-centric accountability and improvement efforts surface as practices for 36 science teachers in three secondary schools. For two years, researchers were embedded in schools alongside teachers moving through daily classroom practice, meetings with colleagues and leaders, data-centric meetings, and professional development days.

Bundled initiatives created consequences for science educators including missed opportunities to capitalize on student-generated ideas, to foster science sensemaking, and to pursue meaningful and equitable science learning. Problematic policy-practice intersections arose, in part, because of school leaders’ framing of district and school initiatives in ways that undermined equity in science education.

From the perspective of science education, this paper raises an alarming problem for equitable science teaching. Lessons learned from missteps seen in this study have practical implications for others attempting similar work. The paper suggests alternatives for supporting meaningful and equitable science education.

Seeing leaders’ framing of policy initiatives, their bundling of performance goals, equity and accountability efforts, and their instructional coaching activities from the point of view of teachers affords unique insight into how leadership activities mediate policies in schools.

The purpose of this article is to develop a conceptual framework that sets out the linkages that exist between digitalisation and active labour market policies (ALMPs).

Based on a narrative literature review, this article seeks to connect two research streams, namely that relating to ALMPs and that relating to digitalisation in the public sector. This exercise requires an understanding of both how the context of digitalisation in the public sector has evolved in relation to technological change and the identification of specific ALMPs that are more sensitive to digitalisation.

Starting from the identification of ideal-types of ALMPs, “employment assistance” can be considered the type of policies most sensitive to digitalisation, looking at main forms of interventions as career guidance, profiling and job-matching tools. The first tool is closer to a technological domain of “remotisation”, while the second is closer to that of “automatisation”.

Achieving an understanding of the different degrees of sensitivity to digitalisation for various types of ALMPs is relevant for policy-making purposes to identify potential priority areas of strategic investment to enhance this sector.

The authors present an understanding of the current state of the digitalisation of public employment services. The literature review itself allowed the authors to conclude that, despite the interests in the public and academic debate, the existing research relating to the digitalisation of public employment services remains scant. At the same time, the article points towards fertile areas for further analysis.

The research literature in this field demonstrates that instructional leadership provided by principals is essential for student learning, but the question of its impact on students with high and low socioeconomic status (SES) has remained largely unexplored. In the present study, the authors focus on the moderating role of instructional leadership in the relationship between SES and achievement at both the school and student levels.

Using cross-national Programme for International Student Assessment (PISA) 2015 data, the authors fitted multilevel models to investigate whether the effect of instructional leadership on student achievement in math, science and reading varies across groups of students with the different individual as well as school SES levels.

Instructional leadership significantly moderates the relationship between school-level SES and student achievement in math, while the moderation effect for individual SES and instructional leadership is not significant for any subject.

This study calls for more research on the moderation role of leadership in the relationship between SES and student achievement, with a specific focus on the integrated models that include the social justice aspect of school leadership.

The authors conclude that while instructional leadership might be beneficial in reducing the achievement gaps between schools, it may not make much difference in terms of reducing the disparity between different SES groups within schools.

The purpose of this paper is to analyze the inadequacies of current business education in the tackling of the educational challenges inherent to the advent of a data-driven business world. It presents an analysis of the implications of digitization and more specifically big data analytics (BDA) and data science (DS) on organizations with a special emphasis on decision-making processes and the function of managers. It argues that business schools and other educational institutions have well responded to the need to train future data scientists but have rather disregarded the question of effectively preparing future managers for the new data-driven business era.

The approach involves analysis and review of the literature.

The development of analytics skills shall not pertain to data scientists only, it must rather become an organizational cultural component shared among all employees and more specifically among decision makers: managers. In the data-driven business era, managers turn into manager-scientists who shall possess skills at the crossroad of data management, analytical/modeling techniques and tools, and business. However, the multidisciplinary nature of big data analytics and data science (BDADS) seems to collide with the dominant “functional silo design” that characterizes business schools. The scope and breadth of the radical digitally enabled change, the author are facing, may necessitate a global questioning about the nature and structure of business education.

For the sake of transparency and clarity, academia and the industry must join forces to standardize the meaning of the terms surrounding big data. BDA/DS training programs, courses, and curricula shall be organized in such a way that students shall interact with an array of specialists providing them a broad enough picture of the big data landscape. The multidisciplinary nature of analytics and DS necessitates to revisit pedagogical models by developing experiential learning and implementing a spiral-shaped pedagogical approach. The attention of scholars is needed as there exists an array of unexplored research territories. This investigation will help bridge the gap between education and the industry.

The findings will help practitioners understand the educational challenges triggered by the advent of the data-driven business era. The implications will also help develop effective trainings and pedagogical strategies that are better suited to prepare future professionals for the new data-driven business world.

By demonstrating how the advent of a data-driven business era is impacting the function and role of managers, the paper initiates a debate revolving around the question about how business schools and higher education shall evolve to better tackle the educational challenges associated with BDADS training. Elements of response and recommendations are then provided.