Predicting student performance has been a critical focus of educational research. With an effective predictive model, schools can identify potentially at-risk students and implement timely interventions to support student success. Recent developments in educational data mining (EDM) have introduced several machine learning techniques that can…

High dropout rate exists universally in massive open online courses (MOOCs) due to the separation of teachers and learners in space and time. Dropout prediction using the machine learning method is an extremely important prerequisite to identify potential at-risk learners to improve learning. It has attracted much attention and there have emerged…

The Data Quality Campaign (DQC) has been reviewing state report cards for the past seven years. They continue to examine the landscape of state report cards because they believe states must increase transparency and build trust by sharing information. But after many years, it was time to look at state report cards with fresh eyes. In addition to…

The novel coronavirus disease 2019 (COVID-19) pandemic has created an unprecedented set of obstacles for schools and exacerbated existing structural inequalities in public education. In spring 2020, as schools went to remote learning formats or closed completely, end-of-year assessment programs ground to a halt. As a result, schools began the…

The novel coronavirus disease 2019 (COVID-19) pandemic has created an unprecedented set of obstacles for schools and exacerbated existing structural inequalities in public education. In spring 2020, as schools went to remote learning formats or closed completely, end-of-year assessment programs ground to a halt. As a result, schools began the…

Considering the large volume of PISA data, it is expected that data mining will often be assisted in making PISA data more meaningful. Studies show that different dimensions of ICT may reveal different relationships for mathematics achievement. The purpose of this article is to evaluate the success of the decision tree classification algorithms in…

Purpose: The purpose of this study was to ascertain the relationship between EFL teachers' perception of the intended and unintended consequences of formative assessment (FA) decisions and their sense of self-efficacy and anxiety toward data-driven decision-making (DDDM). Design/methodology/approach: A correlational research design and…

Clients display considerable variations in functioning across the contexts that encompass their social environments (e.g., home, school/workplace, peer interactions). No single measurement method can fully capture these variations. Yet, assessors must balance the need to accurately capture clients' clinical presentations, and at the same time…

Accurate and efficient universal screening is a foundational component of multi-tiered systems of support for reading. By the time students reach middle school, educators often have extant data available to inform screening decisions. Therefore, the decision to collect additional data to inform screening should be considered carefully. The…

Fuzzy sets have experienced multiple expansions since their conception to enhance their capacity to convey complex information. Intuitionistic fuzzy sets, image fuzzy sets, q-rung orthopair fuzzy sets, and neutrosophic sets are a few of these extensions. Researchers and academics have acquired a lot of information about their theories and methods…

Large-scale summative assessment results are typically used for program-evaluation and resource-allocation purposes; however, stakeholders increasingly desire results from large-scale K-12 assessments that inform instruction. Because large-scale summative results are usually delivered after the end of the school year, teacher use of results is…

This volume brings together experts on various aspects of education to address many of the emerging issues and problems that affect how data are being used or misused in educational contexts. Readers will learn about the importance of using data effectively, responsibly, and ethically to fully understand how cognitive fallacies occur and how they…

Some universal behavioural screening processes require classroom teachers to complete a risk assessment measure on each student in their class, leading to a possible, but unexplored, problem: risk assessment scores may be influenced by the teacher completing the measure. The current study investigated whether teacher-reported risk assessment…

Data reproducibility is becoming increasingly important in the social sciences, but it has yet to be incorporated into many undergraduate sociology programs. This note describes a service-learning activity that can be added to an introductory statistics course. Students partner with a nonprofit and analyze quantitative data to answer questions…

Many of the numbers used to assess students are statistical in nature. The theoretical context underlying the production of a typical number or statistic used in student assessment is presented. The author urges readers to recognize objective data as subjective information and to carefully consider the numbers that often determine admission,…