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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
Firoozi, Tahereh; Bulut, Okan; Epp, Carrie Demmans; Naeimabadi, Ali; Barbosa, Denilson – Journal of Applied Testing Technology, 2022
Automated Essay Scoring (AES) using neural networks has helped increase the accuracy and efficiency of scoring students' written tasks. Generally, the improved accuracy of neural network approaches has been attributed to the use of modern word embedding techniques. However, which word embedding techniques produce higher accuracy in AES systems…
Descriptors: Computer Assisted Testing, Scoring, Essays, Artificial Intelligence
Dragos Corlatescu; Micah Watanabe; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2023
Reading comprehension is essential for both knowledge acquisition and memory reinforcement. Automated modeling of the comprehension process provides insights into the efficacy of specific texts as learning tools. This paper introduces an improved version of the Automated Model of Comprehension, version 3.0 (AMoC v3.0). AMoC v3.0 is based on two…
Descriptors: Reading Comprehension, Models, Concept Mapping, Graphs
Mahowald, Kyle; Kachergis, George; Frank, Michael C. – First Language, 2020
Ambridge calls for exemplar-based accounts of language acquisition. Do modern neural networks such as transformers or word2vec -- which have been extremely successful in modern natural language processing (NLP) applications -- count? Although these models often have ample parametric complexity to store exemplars from their training data, they also…
Descriptors: Models, Language Processing, Computational Linguistics, Language Acquisition
Schuler, Kathryn D.; Kodner, Jordan; Caplan, Spencer – First Language, 2020
In 'Against Stored Abstractions,' Ambridge uses neural and computational evidence to make his case against abstract representations. He argues that storing only exemplars is more parsimonious -- why bother with abstraction when exemplar models with on-the-fly calculation can do everything abstracting models can and more -- and implies that his…
Descriptors: Language Processing, Language Acquisition, Computational Linguistics, Linguistic Theory
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, Reading Processes, Memory, Schemata (Cognition)
Dye, Melody – ProQuest LLC, 2017
While information theory is typically considered in the context of modern computing and engineering, its core mathematical principles provide a potentially useful lens through which to consider human language. Like the artificial communication systems such principles were invented to describe, natural languages involve a sender and receiver, a…
Descriptors: Computational Linguistics, Natural Language Processing, Artificial Languages, Computer Software
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
Jones, Michael N. – Grantee Submission, 2018
Abstraction is a core principle of Distributional Semantic Models (DSMs) that learn semantic representations for words by applying dimensional reduction to statistical redundancies in language. Although the posited learning mechanisms vary widely, virtually all DSMs are prototype models in that they create a single abstract representation of a…
Descriptors: Abstract Reasoning, Semantics, Memory, Learning Processes
Sano, Makoto; Baker, Doris Luft; Collazo, Marlen; Le, Nancy; Kamata, Akihito – Grantee Submission, 2020
Purpose: Explore how different automated scoring (AS) models score reliably the expressive language and vocabulary knowledge in depth of young second grade Latino English learners. Design/methodology/approach: Analyze a total of 13,471 English utterances from 217 Latino English learners with random forest, end-to-end memory networks, long…
Descriptors: English Language Learners, Hispanic American Students, Elementary School Students, Grade 2
Huang, Tao; Liang, Mengyi; Yang, Huali; Li, Zhi; Yu, Tao; Hu, Shengze – International Educational Data Mining Society, 2021
Influenced by COVID-19, online learning has become one of the most important forms of education in the world. In the era of intelligent education, knowledge tracing (KT) can provide excellent technical support for individualized teaching. For online learning, we come up with a new knowledge tracing method that integrates mathematical exercise…
Descriptors: Mathematics Instruction, Teaching Methods, Online Courses, Distance Education
Smith, Kevin A.; Huber, David E.; Vul, Edward – Cognition, 2013
Many important problems require consideration of multiple constraints, such as choosing a job based on salary, location, and responsibilities. We used the Remote Associates Test to study how people solve such multiply-constrained problems by asking participants to make guesses as they came to mind. We evaluated how people generated these guesses…
Descriptors: Problem Solving, Creativity Tests, Natural Language Processing, Cues
Cook, Anne E.; O'Brien, Edward J. – Discourse Processes: A Multidisciplinary Journal, 2014
Previous text comprehension studies using the contradiction paradigm primarily tested assumptions of the activation mechanism involved in reading. However, the nature of the contradiction in such studies relied on validation of information in readers' general world knowledge. We directly tested this validation process by varying the strength of…
Descriptors: Reading Comprehension, Validity, Reliability, Undergraduate Students
Luka, Barbara J.; Choi, Heidi – Journal of Memory and Language, 2012
Three experiments examine whether a naturalistic reading task can induce long-lasting changes of syntactic patterns in memory. Judgment of grammatical acceptability is used as an indirect test of memory for sentences that are identical or only syntactically similar to those read earlier. In previous research (Luka & Barsalou, 2005) both sorts of…
Descriptors: Priming, Comprehension, Sentences, Grammar
Lin, Phoebe M. S. – Applied Linguistics, 2012
With the ever increasing number of studies on formulaic language, we are beginning to learn more about the processing of formulaic language (e.g. Ellis et al. 2008; Siyanova et al. 2011), its use in speech (e.g. Aijmer 1996; Wood 2012) and writing (e.g. Hyland 2008a, 2008b) and its application in natural language processing (e.g. Tschichold 2000).…
Descriptors: Evidence, Language Research, Applied Linguistics, Memory
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