The broader aim of this study is the corpus-based investigation of the written language production process. To this end, temporal markers have been keylog recorded alongside the writing processes to exploit pauses to segment the speech product into linear units of performance. However, identifying these pauses requires selecting the relevant…

Spreading out study opportunities over time improves the retention of verbal material compared to consecutive study, yet little is known about the influence of temporal spacing on orthographic learning specifically. The current study addressed four questions: (1) do readers' eye movements during orthographic learning differ under spaced and massed…

When scores are used to make decisions about respondents, it is of interest to estimate classification accuracy (CA), the probability of making a correct decision, and classification consistency (CC), the probability of making the same decision across two parallel administrations of the measure. Model-based estimates of CA and CC computed from the…

A significant body of research has focused on the impact of immersive virtual reality (IVR) on vocabulary retention, but little is known about how to integrate language learning theories in IVR-mediated vocabulary learning. This study aims to examine the effect of IVR that integrate input processing model on vocabulary retention for elementary…

To reduce the chance of Heywood cases or nonconvergence in estimating the 2PL or the 3PL model in the marginal maximum likelihood with the expectation-maximization (MML-EM) estimation method, priors for the item slope parameter in the 2PL model or for the pseudo-guessing parameter in the 3PL model can be used and the marginal maximum a posteriori…

Testing item fit is central in item response theory (IRT) modeling, since a good fit is necessary to draw valid inferences from estimated model parameters. "Infit" and "outfit" fit statistics, widespread indices for detecting deviations from the Rasch model, are affected by data factors, such as sample size. Consequently, the…

Missing data are exceedingly common across a variety of disciplines, such as educational, social, and behavioral science areas. Missing not at random (MNAR) mechanism where missingness is related to unobserved data is widespread in real data and has detrimental consequence. However, the existing MNAR-based methods have potential problems such as…

Diagnostic accuracy studies often evaluate diagnostic tests at several threshold values, aiming to make recommendations on optimal thresholds for use in practice. Methods for meta-analysis of full receiver operating characteristic (ROC) curves have been proposed but still have deficiencies. We recently proposed a parametric approach that is based…

Diagnostic test accuracy studies frequently report on sensitivities and specificities for more than one threshold of the diagnostic test under study. Although it is obvious that the information from all thresholds should be used for a meta-analysis, in practice, frequently, only a single pair of sensitivity and specificity is selected. To overcome…

Systematic reviews and meta-analyses are the cornerstones of evidence-based medicine and inform treatment, diagnosis, or prevention of individual patients as well as policy decisions in health care. Statistical methods for the meta-analysis of intervention studies are well established today. Meta-analysis for diagnostic accuracy trials has also…

Aim/Purpose: This research aims to present a brand-new approach for student performance prediction using the Learning Fuzzy Cognitive Map (LFCM) approach. Background: Predicting student academic performance has long been an important research topic in many academic disciplines. Different mathematical models have been employed to predict student…

With the increasing adoption of Learning Management Systems (LMS) in colleges and universities, research in exploring the interaction data captured by these systems is promising in developing a better learning environment and improving teaching practice. Most of these research efforts focused on course-level variables to predict student…

Spaced repetition is among the most studied learning strategies in the cognitive science literature. It consists in temporally distributing exposure to an information so as to improve long-term memorization. Providing students with an adaptive and personalized distributed practice schedule would benefit more than just a generic scheduler. However,…

Age-period-cohort (APC) models are designed to estimate the independent effects of age, time periods, and cohort membership. However, APC models suffer from an identification problem: There are no unique estimates of the independent effects that fit the data best because of the exact linear dependency among age, period, and cohort. Among methods…

Are associative memories forgotten more quickly than item memories, and does the level of original learning differentially influence forgetting rates? In this study, we addressed these questions by having participants learn single words and word pairs once (Experiment 1), three times (Experiment 2), and six times (Experiment 3) in a massed…