While teachers' core responsibility is to provide high-quality instruction, they are also expected to engage in data-based decision-making (DBDM), e.g., to analyse and use data to improve instruction. We developed a relevance intervention to promote student teachers' self-determined motivation and application intentions for DBDM and implemented it…

Classification and Regression Tree (CART) analysis is a statistical modeling approach that uses quantitative data to predict future outcomes by generating decision trees. CART analysis can be useful for educators to inform their decision-making. For example, educators can use a decision tree from a CART analysis to identify students who are most…

For the last decade or more, circulation numbers of physical materials have declined in academic libraries across the United States. In the spring of 2020, the COVID-19 pandemic drastically altered society and daily life, not to mention library functions. In particular, fears of contagion via physical surfaces and transmission by contact led many…

The purpose of this small case-study is to gain an in depth understanding of how secondary school teachers perceive that data walls impact their teaching practices and subsequently, students' learning and growth. By drawing on a conceptual model of evidence-informed practice (EIP), this case study examined responses from secondary school teachers…

Data-informed decision-making in teachers' practice, now recommended by different teacher inquiry models and policy documents, implies deep practice change for many teachers. However, not much is known about how teachers perceive the different steps that analytics-informed teacher inquiry entails. This paper presents the results of a study into…

Protection of student privacy is critical for scaling up the use of learning analytics (LA) in education. Poorly implemented frameworks for privacy protection may negatively impact LA outcomes and undermine trust in the discipline. To design and implement models and tools for privacy protection, we need to understand privacy itself. To develop…

Higher education instructors constantly rely on educational data to assess and evaluate the behavior of their students and to make informed decisions such as which content to focus on and how to best engage the students with it. Massive open online course (MOOC) platforms may assist in the data-driven instructional process, as they enable access…

Why do I work? Despite instructors' best efforts, students struggle to understand how different people answer this question differently. This exercise enables students to explore what motivates them in comparison to their peers and previous generations while reinforcing the distinction between intrinsic and extrinsic motivation. Students…

Through time-series graphs, teachers often evaluate progress monitoring data to make both low- and high-stakes decisions for students. The construction of these graphs--specifically, the presence of an aimline and the data points per x- to y-axis ratio (DPPXYR)--may impact decisions teachers make. The purpose of this study was to evaluate the…

Powered by educational policy recommendations around the world, studies on different aspects of data-driven decision making have soared both in number and scope in different educational contexts. However, despite the availability of diverse data, second or foreign language research has been quite tardy in the study of language teachers'…

Decision-making, a key factor of organizational performance, is based on information retrieved from processing raw data. As businesses and consumers are shifting toward digital channels, more and more data is being generated through digital services and electronic devices. Big Data is argued to have significant benefits to businesses, and yet data…

Background: Emotions are inherently intertwined with learning and disciplinary identity, and this relationship demands that teachers attend and respond to students' emotions. In this study, we forward a theory that the development of "pedagogical empathy," or the capacity to understand the implications of student emotions and use…

Purpose: Research shows data-informed leadership matters for school improvement and student achievement, but less is known about what motivates leaders' data use toward such outcomes, particularly in the Catholic school context. Design/methodology/approach: This qualitative interview study uses interview (n = 23) data from a sample of Catholic…

The Data Culture Framework is a high-level guide designed for institutional leaders who want to create and sustain an effective data culture on campus. The Framework offers a set of practices designed to help institutions of higher education create and maintain an effective data-informed community among institutional leaders, faculty, and staff.

This paper deeply discusses the transformation potential of integrating Internet big data into the pre-school education model in colleges and universities. Through in-depth analysis, we studied the challenges and opportunities faced by preschool education in colleges and universities, and discussed the innovative influence of big data technology…