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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
Haerim Hwang; Hyunwoo Kim – Language Testing, 2024
Given the lack of computational tools available for assessing second language (L2) production in Korean, this study introduces a novel automated tool called the Korean Syntactic Complexity Analyzer (KOSCA) for measuring syntactic complexity in L2 Korean production. As an open-source graphic user interface (GUI) developed in Python, KOSCA provides…
Descriptors: Korean, Natural Language Processing, Syntax, Computer Graphics
Jia, Qinjin; Young, Mitchell; Xiao, Yunkai; Cui, Jialin; Liu, Chengyuan; Rashid, Parvez; Gehringer, Edward – Journal of Educational Data Mining, 2022
Instant feedback plays a vital role in promoting academic achievement and student success. In practice, however, delivering timely feedback to students can be challenging for instructors for a variety of reasons (e.g., limited teaching resources). In many cases, feedback arrives too late for learners to act on the advice and reinforce their…
Descriptors: Student Projects, Learning Analytics, Intelligent Tutoring Systems, Feedback (Response)
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
Kunioshi, Nílson; Noguchi, Judy; Tojo, Kazuko; Hayashi, Hiroko – European Journal of Engineering Education, 2016
As English-medium instruction (EMI) spreads around the world, university teachers and students who are non-native speakers of English (NNS) need to put much effort into the delivery or reception of content. Construction of scientific meaning in the process of learning is already complex when instruction is delivered in the first language of the…
Descriptors: Computational Linguistics, Academic Discourse, Lecture Method, Internet
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