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Emily A. Hellmich; Kimberly Vinall – Language Learning & Technology, 2023
The use of machine translation (MT) tools remains controversial among language instructors, with limited integration into classroom practices. While much of the existing research into MT and language education has explored instructor perceptions, less is known about how students actually use MT or how student use compares to instructor beliefs and…
Descriptors: Translation, Second Language Learning, Second Language Instruction, Computational Linguistics
Misnawati Misnawati; Yusriadi Yusriadi; Saidna Zulfiqar Bin Tahir – MEXTESOL Journal, 2023
It is commonly accepted that educators who prepare to teach materials to meet student needs should cover all skills in English, such as speaking, listening, reading, and writing with additional grammar and vocabulary according to the level of students. Because technology has developed rapidly, educators can design technologically friendly teaching…
Descriptors: Linguistic Input, English (Second Language), Second Language Learning, Second Language Instruction
Himel Mondal; Juhu Kiran Krushna Karri; Swaminathan Ramasubramanian; Shaikat Mondal; Ayesha Juhi; Pratima Gupta – Advances in Physiology Education, 2025
Large language models (LLMs)-based chatbots use natural language processing and are a type of generative artificial intelligence (AI) that is capable of comprehending user input and generating output in various formats. They offer potential benefits in medical education. This study explored the student's feedback on the utilization of LLMs in…
Descriptors: Computational Linguistics, Physiology, Teaching Methods, Artificial Intelligence
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
Nicula, Bogdan; Dascalu, Mihai; Newton, Natalie N.; Orcutt, Ellen; McNamara, Danielle S. – Grantee Submission, 2021
Learning to paraphrase supports both writing ability and reading comprehension, particularly for less skilled learners. As such, educational tools that integrate automated evaluations of paraphrases can be used to provide timely feedback to enhance learner paraphrasing skills more efficiently and effectively. Paraphrase identification is a popular…
Descriptors: Computational Linguistics, Feedback (Response), Classification, Learning Processes
Jennifer Hu – ProQuest LLC, 2023
Language is one of the hallmarks of intelligence, demanding explanation in a theory of human cognition. However, language presents unique practical challenges for quantitative empirical research, making many linguistic theories difficult to test at naturalistic scales. Artificial neural network language models (LMs) provide a new tool for studying…
Descriptors: Linguistic Theory, Computational Linguistics, Models, Language Research
Botarleanu, Robert-Mihai; Dascalu, Mihai; Watanabe, Micah; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2022
Age of acquisition (AoA) is a measure of word complexity which refers to the age at which a word is typically learned. AoA measures have shown strong correlations with reading comprehension, lexical decision times, and writing quality. AoA scores based on both adult and child data have limitations that allow for error in measurement, and increase…
Descriptors: Age Differences, Vocabulary Development, Correlation, Reading Comprehension
Bonner, Euan; Lege, Ryan; Frazier, Erin – Teaching English with Technology, 2023
Large Language Models (LLMs) are a powerful type of Artificial Intelligence (AI) that simulates how humans organize language and are able to interpret, predict, and generate text. This allows for contextual understanding of natural human language which enables the LLM to understand conversational human input and respond in a natural manner. Recent…
Descriptors: Teaching Methods, Artificial Intelligence, Second Language Learning, Second Language Instruction
Kim, Sung-Yeon; Kim, Kyung-Sook – TESL-EJ, 2022
Reading-integrated writing is known as an effective approach to teaching and learning vocabulary as it allows students to transfer vocabulary from a source text to writing. This study examines whether vocabulary transfer from an input text to writing varies according to the two types of tasks: essay writing and synchronous text chat. One hundred…
Descriptors: Vocabulary Development, Learning Processes, Word Lists, Transfer of Training
Franken, Margaret – Language Learning Journal, 2014
The use of online language corpora in L2 teaching and learning is gaining momentum largely because corpora are an easily accessed source of language input that potentially provide rich and authentic lexico-grammatical data. This can be of particular use for students' writing as its incorporation can enhance the appearance of native-like fluency.…
Descriptors: Second Language Learning, Computational Linguistics, Computer Software, Second Language Instruction
Amaral, Luiz A.; Meurers, W. Detmar – CALICO Journal, 2009
Error diagnosis in ICALL typically analyzes learner input in an attempt to abstract and identify indicators of the learner's (mis)conceptions of linguistic properties. For written input, this process usually starts with the identification of tokens that will serve as the atomic building blocks of the analysis. In this paper, we discuss the…
Descriptors: Grammar, Computer Assisted Instruction, Identification, Error Analysis (Language)
Rilling, Sarah; Dahlman, Anne; Dodson, Sarah; Boyles, Claire; Pazvant, Ozlem – CALICO Journal, 2005
This paper integrates the theory and practice of computer pedagogies in a variety of language courses, all stemming from participation in a graduate level course on computers in language teaching. First, the graduate level preservice CALL course is described, focusing on how connections between theory and practice were developed. Descriptions of…
Descriptors: Preservice Teacher Education, Preservice Teachers, Distance Education, Computer Simulation