Purpose: Predictions are complex, multisensory, and dynamic processes involving real-time adjustments based on environmental inputs. Disruptions to prediction abilities have been proposed to underlie characteristics associated with autism. While there is substantial empirical literature related to prediction, the field lacks a self-assessment…

Long-running surveys need a systematic way to reflect social change and to keep items relevant to respondents, especially when they ask about controversial subjects, or they threaten the items' validity. We propose a protocol for updating measures that preserves content and construct validity. First, substantive experts articulate the current and…

Since 2018, institutions of higher education have been aware of the "enrollment cliff" which refers to expected declines in future enrollment. This paper attempts to describe how prepared institutions in Ohio are for this future by looking at trends leading up to the anticipated decline. Using IPEDS data from 2012-2022, we analyze trends…

Most existing solutions to the current replication crisis in science address only the factors stemming from specific poor research practices. We introduce a novel mechanism that leverages the experts' predictive abilities to analyze the root causes of replication failures. It is backed by the principle that the most accurate predictor is the most…

Recent investigations on how people derive meaning from language have focused on task-dependent shifts between two cognitive systems. The symbolic (amodal) system represents meaning as the statistical relationships between words. The embodied (modal) system represents meaning through neurocognitive simulation of perceptual or sensorimotor systems…

Background: The study focuses on the need to optimise assessment scales for support needs in individuals with intellectual and developmental disabilities. Current scales are often lengthy and redundant, leading to exhaustion and response burden. The goal is to use machine learning techniques, specifically item-reduction methods and selection…

Given the rapid adoption of machine learning methods by education researchers, and the growing acknowledgment of their inherent risks, there is an urgent need for tailored methodological guidance on how to improve and evaluate the validity of inferences drawn from these methods. Drawing on an integrative literature review and extending a…

Background: Professor-student rapport is associated with various important student success outcomes, highlighting the need for a good measure of this construct. Objective: The current study attempted to replicate the components of the Professor-Student Rapport Scale (PSRS) reported in Wilson and Ryan (2013). Method: 760 undergraduate students…

This study examines the predictive validity of high school grade point average and ACT® Composite score on first-year college grade point average prior to and after the onset of the COVID-19 pandemic in 2020. The findings reveal that the predictive power of high school grade point average changed significantly after 2020, suggesting that students…

Instructional leaders require timely and predictive data to guide post-pandemic systemic changes. We investigated the predictability of an observational instrument, the Rigor Appraisal, and its association with achievement and other school effectiveness measures in a sample of 53 schools in Illinois. We found that increases in the Rigor Appraisal…

This article aims to study the performance of machine learning models in forecasting gender based on the students' open education competency perception. Data were collected from a convenience sample of 326 students from 26 countries using the eOpen instrument. The analysis comprises 1) a study of the students' perceptions of knowledge, skills, and…

Classroom teaching is a demanding and arduous profession, requiring teachers to have a suitable personality to succeed and persevere. However, academic institutions usually determine acceptance based solely on cognitive test scores, despite research indicating the added value of personality measures. This study presents the MESILA personality…

The increased prevalence of suicide among autistic people highlights the need for validated clinical suicide screening and assessment instruments that are accessible and meet the unique language and communication needs of this population. We describe the preliminary preregistered psychometric validation of the Suicide Assessment Kit-Modified…

Modeling reading comprehension processes is a critical task for Learning Analytics, as accurate models of the reading process can be used to match students to texts, identify appropriate interventions, and predict learning outcomes. This paper introduces an improved version of the Automated Model of Comprehension, namely version 4.0. AMoC has its…

We have maintained the customer grade system that is being implemented to customers with excellent performance through customer segmentation for years. Currently, financial institutions that operate the customer grade system provide similar services based on the score calculation criteria, but the score calculation criteria vary from the financial…