Actions can enhance memory, exemplified by the enactment effect. In a typical experiment, participants hear a series of simple action phrases (e.g., "bounce the ball"), which they either carry out (subject-performed tasks, or SPTs), watch the experimenter carry out (experimenter-performed tasks, EPTs), or simply listen to (verbal tasks,…

We analyzed a Japanese lexical database to investigate the structure of the lexical environment based on the hypothesis that the lexical environment is optimized for the functioning of verbal working memory. Our prediction was that, as a consequence of the cultural transmission of language, low-imageable meanings tend to be represented by frequent…

The standard model of particle physics is the most successful theory describing the behavior of matter and energy in the subatomic realm. However, success doesn't mean it is perfect, and a recent measurement of the mass of a particle called the W boson is puzzling, as it disagrees with theoretical predictions and earlier precise measurements. If…

Random encouragement designs evaluate treatments that aim to increase participation in a program or activity. These randomized controlled trials (RCTs) can also assess the mediated effects of participation itself on longer term outcomes using a complier average causal effect (CACE) estimation framework. This article considers power analysis…

This study aimed to develop a prediction model to classify students based on their academic procrastination tendencies, which were measured and classified as low and high using a self-report tool developed based on the students' assignment submission behaviours logged in the learning management system's database. The students' temporal learning…

Wildfires pose significant environmental threats in Australia, impacting ecosystems, human lives, and property. This review article provides a comprehensive analysis of various empirical and dynamic wildfire simulators alongside machine learning (ML) techniques employed for wildfire prediction in Australia. The study examines the effectiveness of…

Understanding attrition risks specific to online student populations is crucial for the long-term success of online programs. Online programs allow place-based working professionals access to education needed for professional development and career advancement. This study was conducted to determine if educational preparation, student…

This study explored how caregiver-reported executive functioning domains, assessed by the BRIEF2 at baseline, predicted behavioral challenges reported by caregivers using the CBCL six months later. The sample included 94 youth with Down syndrome, aged 6 to 18 years. Results of hierarchical regression analyses revealed that, after controlling for…

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…

Existing toolkits for analyzing movement dynamics in animal ecology primarily focus on individual or group behavior in habitats without predefined boundaries, while methods for studying human activity often cater to bounded environments, such as team sports played on defined fields. This leaves a gap in tools for modeling and analyzing human group…

The study intended to describe profiles of three achievement emotions (enjoyment, boredom, anxiety), their associations with each other and with control-value appraisals within the framework of the control-value theory. A total of 2002 Chinese university EFL students from 11 universities in China participated in the questionnaire survey.…

Background: Perceptual evaluation of speech disorders produces scores that poorly predict the consequences of speech impairment on the communication abilities of patients treated for oral/oropharyngeal cancer. This may be mitigated by automatic speech analysis. Aim: To measure communication and speech impairment using automatic analyses of…

Feature engineering plays a critical role in the development of machine learning systems for educational contexts, yet its impact on student trust remains understudied. Traditional approaches have focused primarily on optimizing model performance through expert-crafted features, while the emergence of AutoML offers automated alternatives for…

Knowledge Tracing (KT) models predicting student performance in intelligent tutoring systems have been successfully deployed in several educational domains. However, their usage in open-ended programming problems poses multiple challenges due to the complexity of the programming code and a complex interplay between syntax and logic requirements…

Despite the spread of artificial intelligence (AI) tools and applications, the Apple Vision Pro (AVP) stands out for its innovative features compared to other types of wearable technology. Moreover, traditional glasses have been deficient in incorporating many AI innovations that could enhance user experiences and pose new challenges. In response…