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Haffenden, Chris; Fano, Elena; Malmsten, Martin; Börjeson, Love – College & Research Libraries, 2023
How can novel AI techniques be made and put to use in the library? Combining methods from data and library science, this article focuses on Natural Language Processing technologies, especially in national libraries. It explains how the National Library of Sweden's collections enabled the development of a new BERT language model for Swedish. It…
Descriptors: Foreign Countries, Artificial Intelligence, Models, Languages
Morrison, Ryan – Online Submission, 2022
Large Language Models (LLM) -- powerful algorithms that can generate and transform text -- are set to disrupt language learning education and text-based assessments as they allow for automation of text that can meet certain outcomes of many traditional assessments such as essays. While there is no way to definitively identify text created by this…
Descriptors: Models, Mathematics, Automation, Natural Language Processing
Botarleanu, Robert-Mihai; Dascalu, Mihai; Watanabe, Micah; McNamara, Danielle S.; Crossley, Scott Andrew – Grantee Submission, 2021
The ability to objectively quantify the complexity of a text can be a useful indicator of how likely learners of a given level will comprehend it. Before creating more complex models of assessing text difficulty, the basic building block of a text consists of words and, inherently, its overall difficulty is greatly influenced by the complexity of…
Descriptors: Multilingualism, Language Acquisition, Age, Models
Finley, Sara – First Language, 2020
In this commentary, I discuss why, despite the existence of gradience in phonetics and phonology, there is still a need for abstract representations. Most proponents of exemplar models assume multiple levels of abstraction, allowing for an integration of the gradient and the categorical. Ben Ambridge's dismissal of generative models such as…
Descriptors: Phonology, Phonetics, Abstract Reasoning, Linguistic Theory
Jacob Whitehill; Jennifer LoCasale-Crouch – Journal of Educational Data Mining, 2024
With the aim to provide teachers with more specific, frequent, and actionable feedback about their teaching, we explore how Large Language Models (LLMs) can be used to estimate "Instructional Support" domain scores of the CLassroom Assessment Scoring System (CLASS), a widely used observation protocol. We design a machine learning…
Descriptors: Artificial Intelligence, Teacher Evaluation, Models, Transcripts (Written Records)
Geden, Michael; Emerson, Andrew; Carpenter, Dan; Rowe, Jonathan; Azevedo, Roger; Lester, James – International Journal of Artificial Intelligence in Education, 2021
Game-based learning environments are designed to provide effective and engaging learning experiences for students. Predictive student models use trace data extracted from students' in-game learning behaviors to unobtrusively generate early assessments of student knowledge and skills, equipping game-based learning environments with the capacity to…
Descriptors: Game Based Learning, Middle School Students, Microbiology, Secondary School Science
Corlatescu, Dragos-Georgian; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2021
Reading comprehension is key to knowledge acquisition and to reinforcing memory for previous information. While reading, a mental representation is constructed in the reader's mind. The mental model comprises the words in the text, the relations between the words, and inferences linking to concepts in prior knowledge. The automated model of…
Descriptors: Reading Comprehension, Memory, Inferences, Syntax
Fernando Prieto Ramos – Interpreter and Translator Trainer, 2024
Multi-componential models of translation competence are widely used in translator training as a yardstick for curricular and syllabus design. These models must be adapted to reflect professional trends, such as the impact of artificial intelligence, and machine translation in particular, on working methods. This paper describes the process of…
Descriptors: Translation, Second Language Learning, Second Language Instruction, Language Processing
McKnight, Lucinda – Changing English: Studies in Culture and Education, 2021
With artificial intelligence (AI) now producing human-quality text in seconds via natural language generation, urgent questions arise about the nature and purpose of the teaching of writing in English. Humans have already been co-composing with digital tools for decades, in the form of spelling and grammar checkers built into word processing…
Descriptors: Robotics, Artificial Intelligence, Writing (Composition), Writing Instruction
Smith, Garrett; Franck, Julie; Tabor, Whitney – Cognitive Science, 2018
We present a self-organizing approach to sentence processing that sheds new light on notional plurality effects in agreement attraction, using pseudopartitive subject noun phrases (e.g., "a bottle of pills"). We first show that notional plurality ratings (numerosity judgments for subject noun phrases) predict verb agreement choices in…
Descriptors: Sentence Structure, Sentences, Grammar, Form Classes (Languages)
Hou, Lynn; Morford, Jill P. – First Language, 2020
The visual-manual modality of sign languages renders them a unique test case for language acquisition and processing theories. In this commentary the authors describe evidence from signed languages, and ask whether it is consistent with Ambridge's proposal. The evidence includes recent research on collocations in American Sign Language that reveal…
Descriptors: Sign Language, Phrase Structure, American Sign Language, Syntax
Brouwer, Harm; Crocker, Matthew W.; Venhuizen, Noortje J.; Hoeks, John C. J. – Cognitive Science, 2017
Ten years ago, researchers using event-related brain potentials (ERPs) to study language comprehension were puzzled by what looked like a "Semantic Illusion": Semantically anomalous, but structurally well-formed sentences did not affect the N400 component--traditionally taken to reflect semantic integration--but instead produced a P600…
Descriptors: Diagnostic Tests, Brain Hemisphere Functions, Language Processing, Semantics
Rastelli, Stefano – Language Acquisition: A Journal of Developmental Linguistics, 2019
The Discontinuity Model (DM) described in this article proposes that adults can learn part of L2 morphosyntax twice, in two different ways. The same item can be learned as the product of generation by a rule or as a modification of a template already stored in memory. These learning modalities, which are often seen as opposed in language theory,…
Descriptors: Adults, Second Language Learning, Language Acquisition, Linguistic Theory
Ambridge, Ben – First Language, 2020
The goal of this article is to make the case for a radical exemplar account of child language acquisition, under which unwitnessed forms are produced and comprehended by on-the-fly analogy across multiple stored exemplars, weighted by their degree of similarity to the target with regard to the task at hand. Across the domains of (1) word meanings,…
Descriptors: Language Acquisition, Morphology (Languages), Phonetics, Phonology
Sengupta, Souvik; Dasgupta, Ranjan – Education and Information Technologies, 2017
This paper proposes a new methodology for checking conformance of the software architectural design of Learning Management System (LMS) to Learning Technology System Architecture (LTSA). In our approach, the architectural designing of LMS follows the formal modeling style of Acme. An ontology is built to represent the LTSA rules and the software…
Descriptors: Integrated Learning Systems, Educational Technology, Computer Software, Architecture