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Conrad Borchers; Tianze Shou – Grantee Submission, 2025
Large Language Models (LLMs) hold promise as dynamic instructional aids. Yet, it remains unclear whether LLMs can replicate the adaptivity of intelligent tutoring systems (ITS)--where student knowledge and pedagogical strategies are explicitly modeled. We propose a prompt variation framework to assess LLM-generated instructional moves' adaptivity…
Descriptors: Benchmarking, Computational Linguistics, Artificial Intelligence, Computer Software
Peer reviewedDevika Venugopalan; Ziwen Yan; Conrad Borchers; Jionghao Lin; Vincent Aleven – Grantee Submission, 2025
Caregivers (i.e., parents and members of a child's caring community) are underappreciated stakeholders in learning analytics. Although caregiver involvement can enhance student academic outcomes, many obstacles hinder involvement, most notably knowledge gaps with respect to modern school curricula. An emerging topic of interest in learning…
Descriptors: Homework, Computational Linguistics, Teaching Methods, Learning Analytics
Bogdan Nicula; Mihai Dascalu; Tracy Arner; Renu Balyan; Danielle S. McNamara – Grantee Submission, 2023
Text comprehension is an essential skill in today's information-rich world, and self-explanation practice helps students improve their understanding of complex texts. This study was centered on leveraging open-source Large Language Models (LLMs), specifically FLAN-T5, to automatically assess the comprehension strategies employed by readers while…
Descriptors: Reading Comprehension, Language Processing, Models, STEM Education
Yishen Song; Qianta Zhu; Huaibo Wang; Qinhua Zheng – IEEE Transactions on Learning Technologies, 2024
Manually scoring and revising student essays has long been a time-consuming task for educators. With the rise of natural language processing techniques, automated essay scoring (AES) and automated essay revising (AER) have emerged to alleviate this burden. However, current AES and AER models require large amounts of training data and lack…
Descriptors: Scoring, Essays, Writing Evaluation, Computer Software
Judy Lambert; Mark Stevens – Computers in the Schools, 2024
ChatGPT has garnered unprecedented popularity since its release in November 2022. This artificial intelligence (AI) large language model (LLM) is designed to generate human-like text based on patterns found in massive amounts of data scraped from the internet. ChatGPT is significantly different from previous versions of GPT by its quality of…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Writing Instruction
Zorislav Šojat; Gordana Gredicak Šojat – International Society for Technology, Education, and Science, 2023
The sudden, unexpected breakthrough in the intelligence shown by machines, as a wished for, but very disruptive element, will shape the future of our civilisation and Humans as individuals and collectives. The extreme drive towards commercialisation of newest developments already led to an extremely wide spread of Machine Intelligence Assistants…
Descriptors: Ethics, Artificial Intelligence, Technology Uses in Education, Morale
Bédi, Branislav; Chua, Cathy; Habibi, Hanieh; Martinez-Lopez, Ruth; Rayner, Manny – Research-publishing.net, 2019
This paper presents a brief overview of LARA (Learning And Reading Assistant), an open source online tool that has been under development since summer 2018. LARA currently contains a corpus of about 25 texts in ten languages and a crowdsourcing model used to expand the corpus. The central goal is to provide support for improving second language…
Descriptors: Computer Assisted Instruction, Indo European Languages, Computational Linguistics, Reading Comprehension
Todirascu, Amalia; Cargill, Marion – Research-publishing.net, 2019
We present SimpleApprenant, a platform aiming to improve French L2 learners' knowledge of Multi Word Expressions (MWEs). SimpleApprenant integrates an MWE database annotated with the Common European Framework of Reference for languages (CEFR) level and several Natural Language Processing (NLP) tools: a spelling checker, a parser, and a set of…
Descriptors: French, Phrase Structure, Second Language Learning, Second Language Instruction
Palka, Sean – ProQuest LLC, 2015
This research details a methodology designed for creating content in support of various phishing prevention tasks including live exercises and detection algorithm research. Our system uses probabilistic context-free grammars (PCFG) and variable interpolation as part of a multi-pass method to create diverse and consistent phishing email content on…
Descriptors: Prevention, Information Security, Grammar, Electronic Mail
Bird, Steven; Lee, Haejoong – Language Documentation & Conservation, 2014
Investigating a tone language involves careful transcription of tone on words and phrases. This is challenging when the phonological categories--the tones or melodies--have not been identified. Effects such as coarticulation, sandhi, and phrase-level prosody appear as obstacles to early elicitation and classification of tone. This article presents…
Descriptors: Classification, Computational Linguistics, Tone Languages, Intonation
Charlton, Patricia; Magoulas, George; Laurillard, Diana – Technology, Pedagogy and Education, 2012
The paper advocates an approach to learning design that considers it as creating digital artefacts that can be extended, modified and used for different purposes. This is realised through an "act becoming artefact" cycle, where users' actions in the authors' software environment, named Learning Designer, are automatically interpreted on…
Descriptors: Foreign Countries, Educational Technology, Instructional Design, Computer Software
Gasevic, D.; Zouaq, Amal; Torniai, Carlo; Jovanovic, J.; Hatala, Marek – IEEE Transactions on Learning Technologies, 2011
Recent research in learning technologies has demonstrated many promising contributions from the use of ontologies and semantic web technologies for the development of advanced learning environments. In spite of those benefits, ontology development and maintenance remain the key research challenges to be solved before ontology-enhanced learning…
Descriptors: Foreign Countries, Natural Language Processing, Computer Interfaces, Web 2.0 Technologies

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