Educators seek to harness knowledge from educational corpora to improve student performance outcomes. Although prior studies have compared the efficacy of data mining methods (DMMs) in pipelines for forecasting student success, less work has focused on identifying a set of relevant features prior to model development and quantifying the stability…

Educational data mining involves the application of data mining techniques to student activity. However, in the context of computer programming, many data mining techniques can not be applied because they require vector-shaped input, whereas computer programs have the form of syntax trees. In this paper, we present ast2vec, a neural network that…

The authors of this paper applied a new approach combining text mining and principal component analysis (PCA) to objectively determine the actual state of regional COVID-19 strategy meetings and verified its utility. The authors used text mining to analyze meeting minutes and extracted words with high phase ubiquity by co-occurrence analysis.…

A digital learning-teaching environment is introduced in which undergraduate students are challenged to connect the basic physical concepts of oscillation, buoyancy and data analysis via an authentic experiment. The damped oscillation of a cylindrical body swimming upright in water is measured via the MEMS acceleration sensor of a wireless MCU…

Artificial Intelligence is at the heart of modern society with computers now capable of making process decisions in many spheres of human activity. In education, there has been intensive growth in systems that make formal and informal learning an anytime, anywhere activity for billions of people through online open educational resources and…

Although "free tuition" programs are politically popular, some worry that these programs will exacerbate inequity. Scholars note that program outcomes depend on implementation, but few have probed the contextual conditions that contribute to differences in implementation or the consequences of implementation for equity. To address this…

This case is designed to be used in business analytics courses; particularly those that emphasize predictive analytics. Students are given background information on money laundering and data from People's United Bank, a regional bank in the northeast United States. The students must develop their hypothesis, analyze the data, develop and optimize…

Choosing a major field of study is important, and so is the selection of a specialized concentration that is aligned with an individual's career aspirations. In this paper, we explore a relatively newer concentration in the area of business, namely business analytics. The field of analytics has seen a rapid growth in recent years and enrollment in…

Over the last 20 years, statistics preparation has become vital for a broad range of scientific fields, and statistics coursework has been readily incorporated into undergraduate and graduate programs. However, a gap remains between the computational skills taught in statistics service courses and those required for the use of statistics in…

An estimated 1,400 colleges and universities nationwide have invested in predictive analytics technology to identify which students are at risk of failing courses or dropping out, with spending estimated in the hundreds of millions of dollars. How accurate and stable are those predictions? The authors put six predictive models to the test to gain…

The academic calendar contains national data on how the academic year is structured (beginning of the academic year, term times, holidays and examination periods). Differences between university and non-university study programmes are also highlighted. The information is available for 37 countries. [For the 2020/21 report, see ED610818.]

Measuring similarity of educational items has several applications in the development of adaptive learning systems, and previous research has already proposed a wide range of similarity measures. In this work, we provide an experimental evaluation of selected similarity measures using a large dataset. The used items are alternate-choice questions…

Researchers have long traced achievement gaps in the elementary years back to readiness gaps at the start of kindergarten. Educators seeking to address these gaps, which are associated with race and ethnicity, home language, disability status, and indicators of economic disadvantage, need systematic ways to identify which children need what kinds…

The Faculty Survey of Student Engagement (FSSE) complements the National Survey of Student Engagement (NSSE). FSSE measures faculty members' expectations of student engagement in educational practices that are empirically linked with high levels of learning and development. The survey also collects information about how faculty members spend their…

There is strong evidence that children who attend high-quality pre-kindergarten (pre-K) programs learn skills that benefit them in school and life. The price tag of most private programs puts them out of reach for some families, however. In response, many states and school districts fund pre-K programs to expand opportunities for their youngest…