In recent years, there has been an increasing trend of utilizing artificial intelligence (AI) methodologies over traditional statistical methods for predicting student performance in e-learning contexts. Notably, many researchers have adopted AI techniques without conducting a comprehensive investigation into the most appropriate and accurate…

Children's responses to new, unfamiliar social interactions should be influenced by their cognitive appraisals and physiology, though little is known about how these constructs interrelate. To investigate these links, we examined whether children's appraisals of recalled events and resting parasympathetic physiology predicted social…

In a number of settings risk prediction models are being used to predict distal future outcomes for individuals, including high school risk prediction. We propose a new method, non-overlapping-leave-future-out (NOLFO) validation, to be used in settings with long delays between feature and outcome observation and where there are overlapping…

This study examines the potential to use keystroke logs to examine differences between authentic writing and transcribed essay writing. Transcribed writing produced within writing platforms where copy and paste functions are disabled indicates that students are likely copying texts from the internet or from generative artificial intelligence (AI)…

The integration of technology into education, though beneficial, has also raised concerns about academic dishonesty. Digital tools and platforms provide new opportunities for students to engage in behaviors that could undermine academic integrity. Understanding why students commit these acts is crucial for designing effective policies to mitigate…

Student feedback is crucial for evaluating the performance of teachers and the quality of teaching. Free-form text comments obtained from open-ended questions are seldom analyzed comprehensively since it is difficult to interpret and score compared to standardized rating scales. To solve this problem, the present study employed aspect-level…

The number of clinical prediction models sharing the same prediction task has increased in the medical literature. However, evidence synthesis methodologies that use the results of these prediction models have not been sufficiently studied, particularly in the context of meta-analysis settings where only summary statistics are available. In…

Are there some differences so small that we cannot detect them? Are some quantities so similar (e.g., the number of spots on two speckled hens) that they simply look the same to us? Although modern psychophysical theories such as Signal Detection Theory would predict that, with enough trials, even minute differences would be perceptible at an…

Symptoms of autism influence families' participation in daily activities, but few studies have broadly explored the types of accommodations caregivers make to their "family's" routines after their child is diagnosed with autism. The current study used a mixed-methods approach to characterize the rate and types of accommodations made by…

Social media is becoming more popular, and its resourcefulness has given students new opportunities to learn as well as broaden their academic horizons in various ways assumed if social media is handled appropriately. The main purpose of this study was positioned to estimate the predictive mediating effects of social media on the relationship…

As a prominent aspect of modeling learners in the education domain, knowledge tracing attempts to model learner's cognitive process, and it has been studied for nearly 30 years. Driven by the rapid advancements in deep learning techniques, deep neural networks have been recently adopted for knowledge tracing and have exhibited unique advantages…

Although research suggests that school psychologists are generally satisfied with their experiences in the field, scholars have yet to examine how exposure to racial microaggressions, or subtle race-based insults, may impact satisfaction. The purpose of the current study was to examine the relation between exposure to microaggressions and…

Automatic short answer grading (ASAG) is a challenging task that aims to predict a score for a given student response. Previous works on ASAG mainly use nonneural or neural methods. However, the former depends on handcrafted features and is limited by its inflexibility and high cost, and the latter ignores global word cooccurrence in a corpus and…

Researchers have become increasingly interested in response times to survey items as a measure of cognitive effort. We used machine learning to develop a prediction model of response times based on 41 attributes of survey items (e.g., question length, response format, linguistic features) collected in a large, general population sample. The…

The way we measure values is foundational to their study. This paper explores the empirical findings and theoretical discussions in the literature concerning an essential quality for any measure of values, its validity. We discuss an important debate on validity within the literature concerning the ability of value measures to predict…