This collection focuses on the role of higher education institutions concerning datafication as a complex phenomenon. It explores how the universities can develop data literac(ies) shaping tomorrow skills and "formae mentis" to face the most deleterious effects of datafication, but also to engage in creative and constructive ways with…

Background and Context: Computational thinking (CT) has been increasingly added to K-12 curricula, prompting teachers to grade more and more CT artifacts. This has led to a rise in automated CT assessment tools. Objective: This study examines the scope and characteristics of publications that use machine learning (ML) approaches to assess…

The rapid development of artificial intelligence has driven the transformation of educational evaluation into big data-driven. This study used a systematic literature review method to analyzed 44 empirical research articles on the evaluation of big data education. Firstly, it has shown an increasing trend year by year, and is mainly published in…

In educational data mining (EDM), preprocessing is an arduous and complex task and must promote an appropriate treatment of data to solve each specific educational problem. In the same way, the parameters used in the evaluation of postprocessing results are decisive in the interpretation of the results and decision-making in the future. These two…

Many articles have been published in gifted education in recent years. This study aims to provide a comprehensive review of the evolution of academic studies in gifted education. In this context, the structural topic modeling (STM) method was used to analyze the topics and trends in the field. STM is a machine learning technique that utilizes…

A small subset of education studies analyzes school data collected seasonally (separating the summer from the school year). At first, this work was primarily known for documenting learning loss in the summers, but scholars have since recognized that observing how inequality changes between summer and school periods provides leverage for…

We examined how Learning Analytics literature represents participants from diverse societies by comparing the studies published with samples from WEIRD (Western, Industrialized, Rich, Democratic) nations versus non-WEIRD nations. By analyzing the Learning Analytics studies published during 2015-2019 (N = 360), we found that most of the studies…

Evidence-based assessment (EBA) requires that investigators employ scientific theories and research findings to guide decisions about what domains to measure, how and when to measure them, and how to make decisions and interpret results. To implement EBA, investigators need high-quality assessment tools along with evidence-based processes. We…

A reproducible analysis is one in which an independent entity, using the same data and the same statistical code, would obtain the exact same result as the previous analyst. Reproducible analyses utilize script-based analyses and open data to aid in the reproduction of the analysis. A reproducible analysis does not ensure the same results are…

The application of natural language processing (NLP) technology in the field of education has attracted considerable attention. This study takes 716 articles from the Web of Science database from 1998 to 2023 as its research sample. Using bibliometrics as the theoretical foundation, and employing methods such as literature review and knowledge…

The field of computational thinking (CT) is developing rapidly, reflecting its importance in the global economy. However, most empirical studies have targeted CT in K-12, thus, little attention has been paid to CT in higher education. The present scoping review identifies and summarizes existing empirical studies on CT assessments in…

BASIE is a framework for interpreting impact estimates from evaluations. It is an alternative to null hypothesis significance testing. This guide walks researchers through the key steps of applying BASIE, including selecting prior evidence, reporting impact estimates, interpreting impact estimates, and conducting sensitivity analyses. The guide…

This publication provides a guide for STEM Education Centers (SECs) and Centers for Teaching and Learning (CTLs) to carry out a self-assessment process focusing on their role(s) in undergraduate science, technology, engineering, mathematics (STEM) education. These resources were developed to assist centers in framing their contributions to…

How can we close opportunity gaps for young children affected by poverty and systemic racism--and build hope and resilience for children and their families? Research points the way forward, and in this timely volume, 40+ leading researchers identify new approaches, insights, and technologies that can promote educational equity and improve outcomes…

In this technical report, the Center for Research Use in Education (CRUE) presents the methodological design of a large-scale quantitative investigation of research use by school-based practitioners through the "Survey of Evidence in Education for Schools (SEE-S)." It documents the major technical aspects of the development of SEE-S,…