The profound advancements in technology have rendered novel forms of data and data visualisation increasingly accessible to individuals within society, thereby influencing daily decision-making processes. To address this change, this study sets out to review recent research on data-driven inquiries at the K-12 level from two perspectives:…

The need for data-driven decision-making primarily motivates interest in analysing Big Data in higher education. Although there has been considerable research on the value of Big Data in higher education, its application to address critical issues within the sector is still limited. This systematic review, conducted in December 2021 and…

Design Thinking has been applied successfully in many fields; however, in Information Systems research most early studies focus on applying the specific toolsets to developing product and system designs to solve strategic, managerial, and operational problems. There is little research on how Design Thinking can be embedded in the learning…

The idea of data-based decision-making (DBDM) at the classroom level is that teachers use assessment data to adapt their instruction to students' individual needs and thus improve students' learning progress. In this study, we first investigate this theoretically assumed DBDM process, and second, we evaluate the effectiveness of teacher support on…

Learnersourcing is emerging as a viable approach for mobilizing the learner community and harnessing the intelligence of learners as creators of learning resources. Previous works have demonstrated that the quality of resources developed by students is quite diverse with some resources meeting rigorous judgmental criteria, whereas other resources…

The purpose of study was gain insight into pre-service teachers' experiences in using classroom data to make learning and teaching decisions. The qualitative study is based on the reflections and recommendations of three pre-service teachers' that participated in a data-driven decision-making intervention whilst on an immersive 10-week…

Decades of research suggest that faculty play a critical role in student learning and success, yet at many institutions, faculty are not integrated into the institutional research function. This chapter examines how institutional research and faculty can collaborate to encourage data-informed faculty decision-making to drive student success and…

This chapter describes an open learning analytics system focused on learning process measures and designed to engage instructors and students in an evidence-informed decision-making process to improve learning.

Response time variability and its changes over time have been interpreted as indicative of levels of knowledge automatization. Predominantly, only declines in variability have been examined over the course of practice and growing second language proficiency. We discuss possible scenarios that may involve increasing, rather than declining…

Contribution: An automated methodology that provides visualizations of students' free text comments from course satisfaction surveys. Focusing on sentiment, these visualizations reveal learning and teaching aspects of the course that either may require improvement or are performing well. They provide educators with a simple, systematic way to…

Large-scale, robust implementation of teacher data-driven decision making (DDDM) is a challenging endeavor, impeded by numerous organizational, and teacher, factors. One well-documented barrier to teacher DDDM is underdevelopment of teacher data literacy. This study examines common errors made by pre-service elementary teachers in the formulation…

Single-period inventory models with uncertain demand are very well known in the business analytics community. Typically, such models are rule-based functions, or sets of functions, of one decision variable (order quantity) and one random variable (demand). In academics, the models are taught selectively and usually not completely. Students are…

In this article, we propose the concept of "Autonomic Cycle Of Learning Analysis Tasks" (ACOLAT), which defines a set of tasks of learning analysis, whose objective is to improve the learning process. The data analysis has become a fundamental area for the knowledge discovery from data extracted from different sources. In the autonomic…

Personalized learning has become the most notable application of big data in primary and secondary schools in the United States. The combination of big data and adaptive technological platforms is heralded as a revolution that could transform education, overcoming the outdated classroom model, and realizing the progressive vision of…

This article analyses the rise of software systems in education governance, focusing on digital methods in the collection, calculation and circulation of educational data. It examines how software-mediated methods intervene in the ways educational institutions and actors are seen, known and acted upon through an analysis of the methodological…