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Julian M. Pine; Daniel Freudenthal; Fernand Gobet – Journal of Child Language, 2023
Verb-marking errors are a characteristic feature of the speech of typically-developing (TD) children and are particularly prevalent in the speech of children with Developmental Language Disorder (DLD). However, both the pattern of verb-marking error in TD children and the pattern of verb-marking deficit in DLD vary across languages and interact…
Descriptors: Developmental Disabilities, Language Impairments, Verbs, Error Patterns
Abu-Zhaya, Rana; Arnon, Inbal; Borovsky, Arielle – Cognitive Science, 2022
Meaning in language emerges from multiple words, and children are sensitive to multi-word frequency from infancy. While children successfully use cues from single words to generate linguistic predictions, it is less clear whether and how they use multi-word sequences to guide real-time language processing and whether they form predictions on the…
Descriptors: Sentences, Language Processing, Semantics, Prediction
Ait-Adda, Samia; Bousbia, Nabila; Balla, Amar – E-Learning and Digital Media, 2023
Our aim in this paper is to improve the efficiency of a learning process by using learners' traces to detect particular needs. The analysis of the semantic path of a learner or group of learners during the learning process can allow detecting those students who are in needs of help as well as identify the insufficiently mastered concepts. We…
Descriptors: Semantics, Learning Processes, Learning Analytics, Models
Cong Xie; Shuangfei Zhang; Xinuo Qiao; Ning Hao – npj Science of Learning, 2024
This study investigated whether transcranial direct current stimulation (tDCS) targeting the inferior frontal gyrus (IFG) can alter the thinking process and neural basis of creativity. Participants' performance on the compound remote associates (CRA) task was analyzed considering the semantic features of each trial after receiving different tDCS…
Descriptors: Stimulation, Brain Hemisphere Functions, Semantics, Comparative Analysis
Jing Chen; Bei Fang; Hao Zhang; Xia Xue – Interactive Learning Environments, 2024
High dropout rate exists universally in massive open online courses (MOOCs) due to the separation of teachers and learners in space and time. Dropout prediction using the machine learning method is an extremely important prerequisite to identify potential at-risk learners to improve learning. It has attracted much attention and there have emerged…
Descriptors: MOOCs, Potential Dropouts, Prediction, Artificial Intelligence
Sonia, Allison N.; O'Brien, Edward J. – Discourse Processes: A Multidisciplinary Journal, 2021
The coherence threshold marks the point at which a reader has gained a sufficient comprehension level to move on in a text. Previous research has demonstrated that the readers' coherence threshold can be manipulated by increasing or decreasing task demands. The present experiments examined a manipulation of the coherence threshold within the text…
Descriptors: Reading Comprehension, Difficulty Level, Comparative Analysis, Reading Rate
Jeglinski-Mende, Melinda A.; Fischer, Martin H.; Miklashevsky, Alex – Journal of Numerical Cognition, 2023
While some researchers place negative numbers on a so-called extended mental number line to the left of positive numbers, others claim that negative numbers do not have mental representations but are processed through positive numbers combined with transformation rules. We measured spatial associations of negative numbers with a modified implicit…
Descriptors: Number Concepts, Association Measures, Cognitive Processes, Mathematics Skills
Gafny, Ronit; Ben-Zvi, Dani – Teaching Statistics: An International Journal for Teachers, 2023
In recent years, big data has become ubiquitous in our day-to-day lives. Therefore, it is imperative for educators to integrate nontraditional (big) data into statistics education to ensure that students are prepared for a big data reality. This study examined graduate students' expressions of uncertainty while engaging with traditional and…
Descriptors: Student Attitudes, Data Science, Data Analysis, Models
López-Zambrano, Javier; Lara, Juan A.; Romero, Cristóbal – Journal of Computing in Higher Education, 2022
One of the main current challenges in Educational Data Mining and Learning Analytics is the portability or transferability of predictive models obtained for a particular course so that they can be applied to other different courses. To handle this challenge, one of the foremost problems is the models' excessive dependence on the low-level…
Descriptors: Learning Analytics, Prediction, Models, Semantics
Brainerd, Charles J.; Bialer, Daniel M.; Chang, Minyu – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2022
The conjoint-recognition model (CRM) implements fuzzy-trace theory's opponent process conception of false memory. Within the family of measurement models that separate the memory effects of recollection and familiarity, CRM is the only one that accomplishes this for false as well as true memory. We assembled a corpus of 537 sets of…
Descriptors: Memory, Accuracy, Recognition (Psychology), Familiarity
Dadi Ramesh; Suresh Kumar Sanampudi – European Journal of Education, 2024
Automatic essay scoring (AES) is an essential educational application in natural language processing. This automated process will alleviate the burden by increasing the reliability and consistency of the assessment. With the advances in text embedding libraries and neural network models, AES systems achieved good results in terms of accuracy.…
Descriptors: Scoring, Essays, Writing Evaluation, Memory
Oliveira Moraes, Laura; Pedreira, Carlos Eduardo – IEEE Transactions on Learning Technologies, 2021
Manually determining concepts present in a group of questions is a challenging and time-consuming process. However, the process is an essential step while modeling a virtual learning environment since a mapping between concepts and questions using mastery level assessment and recommendation engines is required. In this article, we investigated…
Descriptors: Computer Science Education, Semantics, Coding, Matrices
Tal Ness; Valerie J. Langlois; Albert E. Kim; Jared M. Novick – Perspectives on Psychological Science, 2025
Understanding language requires readers and listeners to cull meaning from fast-unfolding messages that often contain conflicting cues pointing to incompatible ways of interpreting the input (e.g., "The cat was chased by the mouse"). This article reviews mounting evidence from multiple methods demonstrating that cognitive control plays…
Descriptors: Cognitive Ability, Language Processing, Psycholinguistics, Cues
Wang, Jue; Engelhard, George; Combs, Trenton – Journal of Experimental Education, 2023
Unfolding models are frequently used to develop scales for measuring attitudes. Recently, unfolding models have been applied to examine rater severity and accuracy within the context of rater-mediated assessments. One of the problems in applying unfolding models to rater-mediated assessments is that the substantive interpretations of the latent…
Descriptors: Writing Evaluation, Scoring, Accuracy, Computational Linguistics
Gary, Lee P., Jr.; Richmond, Scott; Spiewak, Daryl – Online Submission, 2023
This presentation highlights the challenges of establishing a consistent application of the two terms, "threats" and "hazards," in academic courses and professional training, designed for emergency, disaster, and humanitarian management programs offered by public and private higher education, government agencies, and…
Descriptors: Professional Education, Emergency Programs, Natural Disasters, Administration

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