This study examined the use of Bayesian analysis methods for the estimation of item parameters in a two-parameter logistic item response theory model. Using simulated data under various design conditions with both informative and non-informative priors, the parameter recovery of Bayesian analysis methods were examined. Overall results showed that…

In this study, it was aimed to investigate the impact of different missing data handling methods on DINA model parameter estimation and classification accuracy. In the study, simulated data were used and the data were generated by manipulating the number of items and sample size. In the generated data, two different missing data mechanisms…

Describing, preserving, and providing access to data is now the purview of many science librarians, although the emphasis has been on data in electronic format. Data in paper or analog format might be found in many places around our campuses. At the University of Minnesota we conducted a preliminary investigation of analog data through discussions…

Brian Kotz is Professor of Mathematics and Statistics at Montgomery College. He is a former member of the American Statistical Association/American Mathematical Association of Two-Year Colleges (ASA)/(AMATYC) Joint Committee and the current chair of the AMATYC Data Science Subcommittee. This interview took place via email on November 23,…

This article addresses recent transformations of European education governance, in particular, the ways in which the parliamentary steering chain has been supplemented with an incentive-based mode of soft governance. The article argues that this new soft governance makes use of technologies that are designed to measure performance. In order to…

The importance of temporality in learning has been long established, but it is only recently that serious attention has begun to be paid to the precise identification, measurement, and analysis of the temporal features of learning. From 2009 to 2016, a series of temporality workshops explored temporal concepts and data types, analysis methods for…

Objective: Our objectives were to measure reporting differences between sexual behavior data from daily diary and retrospective estimates and to assess the utility of using smartphones to collect sexual behavior data from a college student population. Participants: Eighty-six participants (68 women, 18 men) completed the study. Methods: For…

Single-case data are frequently used in school psychology. In research, single-case designs allow experimenters to provide rigorous demonstrations of treatment effects on a smaller scale and with more precise measurement than traditional group experimental design. In practice, single-case data are used to evaluate the effects of school-based…

With this article, we propose using a Bayesian multilevel latent class (BMLC; or mixture) model for the multiple imputation of nested categorical data. Unlike recently developed methods that can only pick up associations between pairs of variables, the multilevel mixture model we propose is flexible enough to automatically deal with complex…

Two of the most important issues facing those in the field of academic advising are the use of technology and data analytics. There is no question that technology and data will shape the delivery and expectations for academic advising in higher education in the years to come. This chapter explores the intersections between advising, technology,…

The National Association for Developmental Education (NADE) Accreditation process is more relevant and important than ever to the discussion of students' success and completion of meaningful credentials. In the current politically-charged climate, NADE Accreditation helps programs demonstrate not only to themselves and their administrations, but…

All methodologies for detecting plagiarism to date have focused on the final digital "outcome", such as a document or source code. Our novel approach takes the creation process into account using logged events collected by special software or by the macro recorders found in most office applications. We look at an author's interaction…

Throughout the different phases of a drug development program, randomized trials are used to establish the tolerability, safety and efficacy of a candidate drug. At each stage one aims to optimize the design of future studies by extrapolation from the available evidence at the time. This includes collected trial data and relevant external data.…

Data science employment opportunities of varied complexity and environment are in growing demand across the globe. Data science as a discipline potentially offers a wealth of jobs to prospective employees, while traditional information science-based roles continue to decrease as budgets get cut across the U.S. Since data is related closely to…

The research urgency is caused by necessity to develop the informational support for management of development of higher education in conditions of high turbulence of external and internal environment. The purpose of the paper is the development of methodology for structuring and analyzing datasets of educational activities in order to reduce…