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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
Amal Alrayes; Tara Fryad Henari; Dalal Abdulkarim Ahmed – Electronic Journal of e-Learning, 2024
This paper provides a thorough examination of the role of Artificial Intelligence (AI), particularly ChatGPT and other AI language models, in the realm of education. Drawing insights from existing literature and a novel study on educator perspectives, the paper delves into the potential advantages, ethical dilemmas, and factors shaping educators'…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Intention
López-Beltrán, Priscila; Johns, Michael A.; Dussias, Paola E.; Lozano, Cristóbal; Palma, Alfonso – Second Language Research, 2022
Traditionally, it has been claimed that the non-canonical word order of passives makes them inherently more difficult to comprehend than their canonical active counterparts both in the first (L1) and second language (L2). However, growing evidence suggests that non-canonical word orders are not inherently more difficult to process than canonical…
Descriptors: Language Processing, Word Order, Form Classes (Languages), Native Language