Purpose: The challenges of language assessment in bilinguals include a lack of assessment tools and bilingual speech-language pathology services. Additionally, the weighting of subtests in standardized tests has not been empirically explored to maximize sensitivity and specificity. Language exposure might also inform the decision to diagnose…

Purpose: Predictive coding theories posit that autism is characterized by an over-adjustment to prediction errors, resulting in frequent updates of prior beliefs. Atypical weighting of prediction errors is generally considered to negatively impact the construction of stable models of the world, but may also yield beneficial effects. In a novel…

Use of artificial intelligence (AI) to score responses is growing in popularity and likely to increase. Evidence of the validity of scores relies on quadratic weighted kappa (QWK) to demonstrate agreement between AI scores and human ratings. QWK is a measure of agreement that accounts for chance agreement and the ordinality of the data by giving…

Successful action anticipation in dynamic social environments, such as sports, requires the integration of prior expectations with observed kinematic cues. However, little is known about how temporal constraints modulate this integration process. In this EEG study, thirty-five expert basketball players completed a sport-specific prediction task in…

The nodules on the roots of soybeans provide N that the plant uses for growth and development. The goal of this study is to observe if the number of nodules on the taproot, volume of nodules on the taproot, the total number of nodules, or the number of nodules on the secondary roots in the early growth stages of soybeans have a significant…

This paper looks at the tension between the desire to claim predictive ability for Agent-Based Models (ABMs) and its extreme difficulty for social and ecological systems, suggesting that this is the main cause for the continuance of a rhetoric of prediction that is at odds with what is achievable. Following others, it recommends that it is better…

Background: Deep learning methods, where models do not use explicit features and instead rely on implicit features estimated during model training, suffer from an explainability problem. In text classification, saliency maps that reflect the importance of words in prediction are one approach toward explainability. However, little is known about…

Massive Open Online Courses (MOOCs) are revolutionizing online education and have become a popular teaching platform. However, traditional MOOCs often overlook learners' individual needs and preferences when designing learning materials and activities, resulting in suboptimal learning experiences. To address this issue, this paper proposes an…

The study examined the impact of child protective services (CPS) contact on out-of-school suspensions for 49,918 Wisconsin students (followed from ages 5-6 to 14-15; [school years 2010-2019; 74% White; 7% Black; 11% Hispanic; 8% other; 49% female]). A quasi-experimental design comparing recent CPS contact to upcoming (future) CPS contact shows…

Higher education institutions have consistently strived to provide students with top-notch education. To achieve better outcomes, machine learning (ML) algorithms greatly simplify the prediction process. ML can be utilized by academicians to obtain insight into student data and mine data for forecasting the performance. In this paper, the authors…

Futures of education are increasingly defined through predictive technologies and methods. We conceptualize 'algorithmic futuring' as the use of data-driven digital methods and predictive infrastructures to anticipate educational futures and animate actions in the present towards their materialization. Specifically, we focus on algorithmic…

Student academic performance prediction is a significant area of study in the realm of education that has drawn the interest and investigation of numerous scholars. The current approaches for student academic performance prediction mainly rely on the educational information provided by educational system, ignoring the information on students'…

Recently, researchers have focused on various factors influencing work engagement, particularly in the EFL context. In this vein, this study was carried out to investigate the relationship among proactive personality, flow, and work engagement in China. In so doing, three instruments including Proactive Personality Scale, Work-Related Flow…

One challenging issue in improving the teaching and learning methods in MOOCs is to construct potential knowledge graphs from massive learning resources. Therefore, this study proposes knowledge graphs driving online learning behaviour prediction and multi-learning task recommendation in MOOCs. Based on the knowledge graphs supported by…

Research on study habits among college students demonstrates a difference between what students should do and what they actually do. We sought to understand students' break-taking habits and perceptions within the context of study behaviors. One hundred and sixteen undergraduate students responded to a survey of their study break-taking behaviors,…