Performance-based funding policies for postsecondary institutions have been enacted throughout the United States as an answer to reductions in public funding and increased accountability mandates. Institutional effectiveness, as demonstrated through metrics such as graduation and retention rates, dictates the level of funding received. Educational…

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…

Data showing what students earn after attending higher education institutions have become increasingly available, bolstering calls from policymakers and advocates that government financial aid programs should be tied to those outcomes. Often overlooked, however, is that these data and policies usually reflect the earnings of only students who…

Artificial intelligence (AI) is now affecting all aspects of our social lives. Without always knowing it, we interact daily with intelligent systems. They serve us invisibly. At least that is the goal we assign to them: to make our lives better, task by task. Artificial intelligence has the potential to make biology education more engaging,…

Drawing on the data collected via a European funded project with eleven higher education partners, the article proposes a five-stage working model which can be adopted in and adapted to different institutional contexts so as to shift perceptions, strengthen engagement and channel commitment with a view to developing the desired quality culture.…

Being able to understand, interpret, and critically evaluate data is necessary for all individuals in our society. Using the PreK-12 Guidelines for Assessment and Instruction in Statistics Education-II (GAISE-II; Bargagliotti et al., 2020) curriculum framework, the current paper outlines five evidence-based recommendations that teachers can use to…

Business analytics is a fast-growing field that requires a combination of technical, analytical, and communication skills. This article aims to identify the most sought after skills for business analytics jobs based on a content analysis of over 2600 online job postings. The results show that the top skills include analytics, communication,…

Data science education in Japan extends from elementary to high school students. However, some studies show that this has not enhanced interest or curiosity in data science. Therefore, gamification appears to be an efficient method for encouraging high school students' interest in data science, with research indicating that video games are…

Manipulation checks are an essential component of quality experimental design in motor learning. Guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework, this methodological systematic review examined the utilization of manipulation checks in focus of attention research. Seventy-eight protocols from four…

When using multiple imputation, users often want to know how many imputations they need. An old answer is that 2-10 imputations usually suffice, but this recommendation only addresses the efficiency of point estimates. You may need more imputations if, in addition to efficient point estimates, you also want standard error (SE) estimates that would…

Large-scale analyses are a powerful and increasingly common tool for investigating a range of public health and social concerns (Pienta, O'Rourke, & Franks, 2011). This series will provide a primer on large-scale secondary analysis in school psychology, with this article focusing on considerations for researchers interested in applying and…

The purpose of this study was to compare 12 commonly-used nonoverlap methods with each other and with the results of visual analysis. Data were obtained from 25 studies focused on embedded instruction and schema-based instruction and included a total of 101 graphs. Treatment effect estimates using 12 nonoverlap methods were calculated for each…

Missing data result in less precise and possibly biased effect estimates in single studies. Bias arising from studies with incomplete outcome data is naturally propagated in a meta-analysis. Conventional analysis using only individuals with available data is adequate when the meta-analyst can be confident that the data are missing at random (MAR)…

Spatial regression models provide the opportunity to analyze spatial data and spatial processes. Yet, several model specifications can be used, all assuming different types of spatial dependence. This study summarizes the most commonly used spatial regression models and offers a comparison of their performance by using Monte Carlo experiments. In…

Educational data mining has become an effective tool for exploring the hidden relationships in educational data and predicting students' academic achievements. This study proposes a new model based on machine learning algorithms to predict the final exam grades of undergraduate students, taking their midterm exam grades as the source data. The…