This article presents an exploration of college student perspectives of their zeitgeist over five semesters during and after the COVID-19 pandemic. At the start of each semester, from Spring 2021 through Spring 2023, between 100 and 150 individuals offered words and/or phrases which they believed characterized the spirit of the time. While this…

The effect of instructor clarity on student learning has been explained using cognitive load theory, which stipulates that students have limited mental resources to devote to activities pertaining to learning. To date, the effect of teacher clarity on students' cognitive burden has been studied in reference to students' extraneous cognitive load…

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,…

This study aimed to investigate the predictive role of critical thinking dispositions and new media literacies on the ability to detect fake news on social media. The sample group of the study consisted of 157 university students. Sosu Critical Thinking Dispositions Scale, New Media Literacy Scale, and fake news detection task were employed to…

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.…

Choosing a field of study (study major) is challenging for prospective students. However, little research has examined factors measured prior to enrollment to predict motivation and well-being in a specific study major. Based on literature on affective forecasting and person-environment fit, prospective students' well-being forecast could be such…

This study investigated college students' career maturity as a mediator of the effect of professional identity on academic achievement. The researchers developed a structural equation model and a research hypothesis using the Chinese college students' professional identity scale, career maturity scale, and academic achievement scale. After…

This study helps improve the early prediction of student performance by RNN-FitNets, which applies knowledge distillation (KD) to the time series direction of the recurrent neural network (RNN) model. The RNN-FitNets replaces the teacher model in KD with "an RNN model with a long-term time-series in which the features during the entire course…

The close relationship between working memory and maths problem solving is generally accepted, but the specifics of how working memory and its subcomponents contribute to maths problem solving remain poorly understood. Tests of working memory, maths problem problem solving, calculation, and intelligence were administered to 246 university…

Data from a moderately-selective state university in the Midwest is used to cross-examine the most appropriate data analytical techniques for predicting versus explaining college student persistence decisions. The current research provides an overview of the relative benefits of models specializing in prediction versus explanation with particular…

The relationship between peer support and academic engagement has been widely explored. However, scarce research examined this relationship for college students, and little was known about the underlying mechanism under this relationship. This study aimed to examine the effect of peer support on academic via the mediation of academic motivation…

Learning style recognition is an indispensable part of achieving personalized learning in online learning systems. The traditional inventory method for learning style identification faces the limitations such as subject and static characteristics. Therefore, an automatic and reliable learning style recognition mechanism is designed in this…

Teaching Institutions could benefit from Early Warning Systems to identify at-risk students before learning difficulties affect the quality of their acquired knowledge. An Early Warning System can help preemptively identify learners at risk of dropping out by monitoring them and analyzing their traces to promptly react to them so they can continue…

Whether machine learning algorithms effectively predict college students' course outcomes using learning management system data is unknown. Identifying students who will have a poor outcome can help institutions plan future budgets and allocate resources to create interventions for underachieving students. Therefore, knowing the effectiveness of…

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…