Understanding prenatal alcohol exposure (PAE) risk perception is important for the communication and prevention of alcohol use during pregnancy. A previous systematic review has explored the dimensions and influencing factors of women's PAE risk perceptions, leading to the construction of Pregnancy Alcohol Use Risk Perception (PARP) conceptual…

In this paper, we describe two empirical studies that demonstrate the application and modeling of keystroke logs in writing assessments. We illustrate two different approaches of modeling differences in writing processes: analysis of mean differences in handcrafted theory-driven features and use of large language models to identify stable personal…

In 2008, China's museums began to offer free admission, which led to an explosive growth in the number of visitors. As a result, more researchers are examining how to determine the learning experience of museum visitors, and improving it gradually will be the next direction for the development of Chinese museums. The Contextual Model of Learning…

When people encounter items that they believe will help them gain reward, they later remember them better than others. A recent model of emotional memory, the emotional context maintenance and retrieval model (eCMR), predicts that these effects would be stronger when stimuli that predict high and low reward can compete with each other during both…

The present study seeks to revisit the concept of intertextuality as integrated into a sociocognitive discourse-analytical perspective, whereby intertextual meanings can be explicated via semantic macropropositions, mental representations, event models, and pragmatic context models. The study's significance derives from its scholarly endeavour to…

Over 10 years of the new college entrance examination reform, the flexible subject selection model has posed challenges to Science, Technology, Engineering, and Math (STEM) majors education in Chinese universities. The relaxation of subject requirements has led to diverse knowledge backgrounds among students, resulting in some lacking a solid…

Predictive analytics are increasingly pervasive in higher education. However, algorithmic bias has the potential to reinforce racial inequities in postsecondary success. We provide a comprehensive and translational investigation of algorithmic bias in two separate prediction models--one predicting course completion, the second predicting degree…

Automating the classification of instructional strategies from a large-scale online tutorial dialogue corpus is indispensable to the design of dialogue-based intelligent tutoring systems. Despite many existing studies employing supervised machine learning (ML) models to automate the classification process, they concluded that building a…

This research integrates context-based learning and modelling. It presents a teaching-learning sequence (TLS) about the dissolution of gases in liquids using carbonated drinks as the context. The impact of the TLS is analysed in a longitudinal short-term study involving two groups of learners aged 13-14 years old (n=53). The results led us to…

Background: The learning assistant (LA) model supports student success in undergraduate science courses; however, variation in outcomes has led to a call for more work investigating how the LA model is implemented. In this research, we used cultural historical activity theory (CHAT) to characterize how three different instructors set up…

Purpose: To examine the contextual and personal factors that influence teachers' reported adoption of one or more instructional models (IMs). Methods: Participants (n = 25) were interviewed that reported adopting Sport Education; Teaching Games for Understanding; Teaching Personal and Social Responsibility; and/or Sports, Play, and Active…

Comprehenders generate expectations about upcoming lexical items in language processing using various types of contextual information. However, a number of studies have shown that argument roles do not impact neural and behavioral prediction measures. Despite these robust findings, some prior studies have suggested that lexical prediction might be…

The use and interpretation of educational and psychological test scores are paramount to individual outcomes and opportunities. Methods for detecting differential item functioning (DIF) are imperative for item analysis when developing and revising assessments, particularly as it pertains to fairness across populations, languages, and cultures. We…

Grade prediction can help students and their advisers select courses and design personalized degree programs based on predicted future course performance. One of the successful approaches for accurately predicting a student's grades in future courses is Cumulative Knowledge-based Regression Models (CKRM). CKRM learns shallow linear models that…

A key component of research on human sentence processing is to characterize the processing difficulty associated with the comprehension of words in context. Models that explain and predict this difficulty can be broadly divided into two kinds, expectation-based and memory-based. In this work, we present a new model of incremental sentence…