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Chen, Xuemei; Wang, Suiping; Hartsuiker, Robert J. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2022
Structural priming studies in production have demonstrated stronger priming effects for unexpected sentence structures (inverse preference effect). This is consistent with error-based implicit learning accounts that assume learning depends on prediction error. Such prediction error can be verb-specific, leading to strong priming when a verb that…
Descriptors: Sentence Structure, Priming, Language Processing, Reading Comprehension
Sinclair, Alyssa H.; Barense, Morgan D. – Learning & Memory, 2018
Through the process of "reconsolidation," reminders can temporarily destabilize memories and render them vulnerable to change. Recent rodent research has proposed that prediction error, or the element of surprise, is a key component of this process; yet, this hypothesis has never before been extended to complex episodic memories in…
Descriptors: Memory, Prediction, Error Patterns, Cues
Waldron, Sam; Wood, Clare; Kemp, Nenagh – Journal of Research in Reading, 2017
An investigation into the impact of predictive text use upon the literacy skills of primary school, secondary school and university cohorts was conducted over the course of a year. No differences in use of text abbreviations ("textisms") were found between predictive text users and nonusers. However, secondary school children who used…
Descriptors: Grammar, Spelling, Reading Processes, Error Patterns
Foote, Rebecca – Second Language Research, 2015
In native speakers of gender-marking languages, mechanisms of gender production appear to be affected by the morphophonological cues to gender present in the noun phrase. This influence is manifested in higher levels of production accuracy when more transparent cues to gender are present in comparison to when they are not. The goal of the present…
Descriptors: Spanish, Grammar, Second Language Learning, Morphology (Languages)
Feng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating
Takashima, Hiroomi – Journal of Psycholinguistic Research, 2009
Ease of processing of 3,969 English words for native speakers and Japanese learners was investigated using lexical decision and naming latencies taken from the English Lexicon Project (Balota et al. The English Lexicon Project: A web-based repository of descriptive and behavioral measures for 40,481 English words and nonwords, 2002) and accuracy…
Descriptors: Translation, Dictionaries, English (Second Language), Comparative Analysis
Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis