Dynamic structural equation models (DSEM) are designed for time series analysis of latent structures. Inherent to the application of DSEM is model parameter estimation, which has to be addressed in many applications by a single time series. In this context, however, the methods currently available either lack estimation quality or are…

The nature of teaching and learning has evolved over the years, especially as technology has evolved. Innovative application of educational analytics has gained momentum. Indeed, predictive analytics have become increasingly salient in education. Considering the prevalence of learner-system interaction data and the potential value of such data, it…

The American Family Health Study (AFHS) collected family health and fertility data from a national probability sample of persons aged 18-49 between September 2021 and May 2022, using web and mail exclusively. In July 2022, we surveyed AFHS respondents and gauged their willingness to become part of a national web panel that would create novel…

This study evaluated the forecasting accuracy of trend estimation methods applied to time-series data from computer adaptive tests (CATs). Data were collected roughly once a month over the course of a school year. We evaluated the forecasting accuracy of two regression-based growth estimation methods (ordinary least squares and Theil-Sen). The…

This article uses an anonymous 2014-15 school year dataset from the Directorate-General for Statistics of Education and Science (DGEEC) of the Portuguese Ministry of Education as a means to carry out a predictive power comparison between the classic multilinear regression model and a chosen set of machine learning algorithms. A multilinear…

This paper combines a theoretical-based model with a data-driven approach to develop an Early Warning System that detects students who are more likely to dropout. The model uses innovative multilevel statistical and machine learning methods. The paper demonstrates the validity of the approach by applying it to administrative data from a leading…

Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…

Institutions are applying methods and practices from data analytics under the umbrella term of "learning analytics" to inform instruction, library practices, and institutional research, among other things. This study reports findings from interviews with professional advisors at a public higher education institution. It reports their…

Educational institutions and governing practices are increasingly augmented with digital database technologies that function as new kinds of policy instruments. This article surveys and maps the landscape of digital policy instrumentation in education and provides two detailed case studies of new digital data systems. The Learning Curve is a…

Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…

Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…

New high-frequency, automated data collection and analysis algorithms could offer new insights into complex learning processes, especially for tasks in which students have opportunities to generate unique open-ended artifacts such as computer programs. These approaches should be particularly useful because the need for scalable project-based and…

National background of users may influence the process of technology acceptance. The present study explored this issue with the new, integrated technology use model proposed by Sun and Zhang (2006). Data were collected from samples of college students in India, Mauritius, Reunion Island, and United States. Questionnaire methodology and…

Two studies were conducted to examine the efficacy of direct measurement, standardized achievement tests, and aptitude-achievement discrepancy scores in distinguishing learning disabled (LD) and nonlearning disabled (NLD) students in grades 3 to 6. For both reading (Study I) and written expression (Study II), students' scores on direct and…

The working paper concentrates on the general objective, "How do the agency (Federal) and its policy makers utilize the information conveyed by scientific manpower forecasts?" Section 1 examines reasons for the growth in demand for these forecasts: (1) benefit cost analysis of public projects with long payout periods must rely on forecasts; (2)…