Historically, organizational researchers have fully embraced frequentist statistics and null hypothesis significance testing (NHST). Bayesian statistics is an underused alternative paradigm offering numerous benefits for organizational researchers and practitioners: e.g., accumulating direct evidence for the null hypothesis (vs. 'fail to reject…

Technical difficulties occasionally lead to missing item scores and hence to incomplete data on computerized tests. It is not straightforward to report scores to the examinees whose data are incomplete due to technical difficulties. Such reporting essentially involves imputation of missing scores. In this paper, a simulation study based on data…

Computer-based assessment (CBA) is a top-rated tool for conducting assessments, mapping learning outcomes, and selecting new candidates. Research that examines the development and use of CBA is also increasing from year to year, so without bibliometric analysis, it would be quite challenging to keep up with all of these studies. This study aims to…

Many institutions use placement tests as a method to assess students' readiness for college-level coursework. With the increased use of technology in testing, many institutions have transitioned placement test administration to an online format in an unproctored setting. While unproctored placement tests may provide financial and logistical…

The COVID-19 pandemic outbreak has upended the educational system worldwide, possibly with severe long-term consequences as most training institutions were forced to move to an online environment. Given the sudden transition to remote education, the main objective of this contribution is to evaluate the impact of distance education on examination…

This study explored the validity of growth on two computer adaptive tests, Star Reading and Star Math, in explaining performance on an end-of-year achievement test for a sample of students in Grades 3 through 6. Results from quantile regression analyses indicate that growth on Star Reading explained a statistically significant amount of variance…

In the machine learning literature, it is commonly accepted as fact that as calibration sample sizes increase, Naïve Bayes classifiers initially outperform Logistic Regression classifiers in terms of classification accuracy. Applied to subtests from an on-line final examination and from a highly regarded certification examination, this study shows…

In this research report, we present an empirical argument for the use of a contributory scoring approach for the 2-essay writing assessment of the analytical writing section of the "GRE"® test in which human and machine scores are combined for score creation at the task and section levels. The approach was designed to replace a currently…

The current work uses memory errors to examine the mental representation of verb-particle constructions (VPCs; e.g., "make up" the story, "cut up the meat"). Some evidence suggests that VPCs are represented by a cline in which the relationship between the VPC and its component elements ranges from highly transparent ("cut…

Within multitiered systems of support, assessment practices that limit the amount of time students miss instruction should be prioritized. At the same time, decisions about student response to intervention need to be based upon technically adequate data. We evaluated the impact of data collection frequency and trend estimation method on the…

Two experiments explored the hypothesis that anaphors and demonstratives signal different procedural instructions: Whereas the anaphor "it" brings a concrete entity into a reader's focus, the demonstrative "this" directs the focus to a predicate proposition in a discourse representation. The findings from an online eye-tracking…

We examine the impact of remedial and developmental courses on college students with varying levels of academic preparedness, thus focusing on a wider range of students than previous studies. Using a regression discontinuity design, we provide causal estimates of the effects of placement in different levels of remedial courses on short-,…

A problem faced by many instructors is that of designing exams that accurately assess the abilities of the students. Typically, these exams are prepared several days in advance, and generic question scores are used based on rough approximation of the question difficulty and length. For example, for a recent class taught by the author, there were…

Item positions in educational assessments are often randomized across students to prevent cheating. However, if altering item positions results in any significant impact on students' performance, it may threaten the validity of test scores. Two widely used approaches for detecting position effects -- logistic regression and hierarchical…

Nearly two dozen states now administer online exams. These tests have real consequences: their results feed into accountability systems, which have been used for more than a decade to hold schools and districts accountable for their students' learning. We examine the rollout of computer-based testing in Massachusetts over 2 years to investigate…