This study investigated whether prompting children to generate predictions about an outcome facilitates activation of prior knowledge and improves belief revision. 51 children aged 9-12 were tested on two experimental tasks in which generating a prediction was compared to closely matched control conditions, as well as on a test of executive…

Purpose: The purpose of this study was to compare the utility of two automated indices of lexical diversity, the Moving-Average Type-Token Ratio (MATTR) and the Word Information Measure (WIM), in predicting aphasia diagnosis and responding to differences in severity and aphasia subtype. Method: Transcripts of a single discourse task were analyzed…

Open-ended "constructed responses" promote deeper processing of course materials. Further, evaluation of these explanations can yield important information about students' cognition. This study examined how students' constructed responses, generated at different points during learning, relate to their later comprehension outcomes.…

Data mining of course enrollment and course description records has soared as institutions of higher education begin tapping into the value of these data for academic and internal research purposes. This has led to a more than doubling of papers on course prediction tasks every year. The papers often center around a single prediction task and…

National failure rates seen in undergraduate introductory CS courses are quite high. In this paper, we develop a predictive model for student in-class performance in an introductory CS course. The model can serve as an early warning system, flagging struggling students who might benefit from additional support. We use a variety of features from…

In higher education, predictive analytics can provide actionable insights to diverse stakeholders such as administrators, instructors, and students. Separate feature sets are typically used for different prediction tasks, e.g., student activity logs for predicting in-course performance and registrar data for predicting long-term college success.…

The "2nd Annual WPI-UMASS-UPENN EDM Data Mining Challenge" required contestants to predict efficient testtaking based on log data. In this paper, we describe our theory-driven and psychometric modeling approach. For feature engineering, we employed the Log-Normal Response Time Model for estimating latent person speed, and the Generalized…

In this study, neural representation of adult second language (L2) speakers' implicit grammatical knowledge was investigated. Advanced L2 speakers of Japanese living in Japan, as well as L1 Japanese speakers, performed a word-monitoring task (proposed as an implicit knowledge test) in the MRI scanner. Behavioral measures were obtained from…

We use a novel paradigm to examine the effect of language exposure and variable input on the acquisition of words in primary school--aged children. Children growing up with different languages and foreign or regional accents in their input might benefit from their experience with variability when learning new words from peers with unfamiliar…

Objective: The purpose of this study is to examine the roles of risk perceptions and efficacy beliefs play in predicting emerging adults' health insurance information seeking behavior based on the risk perception attitude (RPA) framework. In addition, the current study tests a role of worry to elucidate an underlying mechanism of their health…

Background: Computer-based scaffolding has been intensively used to facilitate students' self-regulated learning (SRL). However, most previous studies investigated how computer-based scaffoldings affected the cognitive aspect of SRL, such as knowledge gains and understanding levels. In contrast, more evidence is needed to examine the effects of…

Concentrated pockets of under-resourced neighbourhoods and schools exist in urban areas in which there are overwhelming numbers of children labelled 'at-risk.' Structural equation modelling was used to predict the associations between family social capital in kindergarten and third-grade learning and development outcomes for low-socioeconomic…

Despite the plethora of m-learning acceptance studies, few have tackled the importance of examining the actual use of m-learning systems from the lenses of social influence, expectation-confirmation, and satisfaction. Additionally, most of the prior technology adoption literature tends to use the structural equation modeling (SEM) technique in…

This study compared the effects of extracurricular synchronous computer-mediated communication (SCMC) and asynchronous computer-mediated communication (ASCMC) between students and teachers on students' digital reading performance at different frequencies. 392,269 samples from 53 countries/regions that participated in the Programme for…

School dropout is a structural problem which permanently penalizes students and society in areas such as low qualification jobs, higher poverty levels and lower life expectancy, lower pensions, and higher economic burden for governments. Given these high consequences and the surge of the problem due to COVID-19 pandemic, in this paper we propose a…