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Jimmy Tobin; Phillip Nelson; Bob MacDonald; Rus Heywood; Richard Cave; Katie Seaver; Antoine Desjardins; Pan-Pan Jiang; Jordan R. Green – Journal of Speech, Language, and Hearing Research, 2024
Purpose: This study examines the effectiveness of automatic speech recognition (ASR) for individuals with speech disorders, addressing the gap in performance between read and conversational ASR. We analyze the factors influencing this disparity and the effect of speech mode--specific training on ASR accuracy. Method: Recordings of read and…
Descriptors: Foreign Countries, Speech Impairments, Computational Linguistics, Artificial Intelligence
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Xiaoqin Shi; Xiaoqing Wang; Wei Zhang – Language Testing in Asia, 2024
Automatic Speech Scoring (ASS) has increasingly become a useful tool in oral proficiency testing for Second Language (L2) learners. However, limited studies investigate the alignment of ASS indices with the Complexity, Accuracy, and Fluency (CAF)--the three dimensions in evaluating L2 speakers' oral proficiency, and the subsequent impact indices…
Descriptors: Speech Communication, Oral Language, Language Proficiency, Scoring
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Shahzad, Areeba; Wali, Aamir – Education and Information Technologies, 2022
Checking essays written by students is a very time consuming task. Besides spellings and grammar, they also need to be evaluated on their semantic content such as cohesion, coherence, etc. In this study we focus on one such aspect of semantic content which is the topic of the essay. Putting it formally, given a prompt or essay-statement and an…
Descriptors: Computer Uses in Education, Essays, Writing Evaluation, Semantics
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Barrot, Jessie S. – Computer Assisted Language Learning, 2023
Despite the building up of research on the adoption of automated writing evaluation (AWE) systems, the differential effects of automated written corrective feedback (AWCF) on errors with different severity levels and gains across writing tasks remain unclear. Thus, this study fills in the vacuum by examining how AWCF through Grammarly affects…
Descriptors: Automation, Written Language, Error Correction, Feedback (Response)
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Shinta Estri Wahyuningrum; Gilles van Luijtelaar; Augustina Sulastri; Marc P. H. Hendriks; Ridwan Sanjaya; Tom Heskes – SAGE Open, 2024
Visual Reproduction is a condition to measure Visual Spatial Memory as one of the cognitive domains commonly used to measure visuo-spatial memory. Geometric figures serve as stimulus material, and probands have to reproduce the figures from memory through a hand drawing. The scoring of the drawing has subjective elements. This study aims to…
Descriptors: Automation, Scores, Geometry, Visual Aids
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Conijn, Rianne; Kahr, Patricia; Snijders, Chris – Journal of Learning Analytics, 2023
Ethical considerations, including transparency, play an important role when using artificial intelligence (AI) in education. Explainable AI has been coined as a solution to provide more insight into the inner workings of AI algorithms. However, carefully designed user studies on how to design explanations for AI in education are still limited. The…
Descriptors: Ethics, Writing Evaluation, Artificial Intelligence, Essays
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Dillon, Thomas; Wells, Donald – English Teaching, 2023
This study examined effects of pronunciation training using automatic speech recognition technology on common pronunciation errors of Korean English learners. Participants were divided into two groups. One group was given instruction and training about the use of automatic speech recognition for pronunciation practice. The other group was not…
Descriptors: Pronunciation, English (Second Language), Second Language Instruction, English Language Learners
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Wang, Cong; Liu, Xiufeng; Wang, Lei; Sun, Ying; Zhang, Hongyan – Journal of Science Education and Technology, 2021
Assessing scientific argumentation is one of main challenges in science education. Constructed-response (CR) items can be used to measure the coherence of student ideas and inform science instruction on argumentation. Published research on automated scoring of CR items has been conducted mostly in English writing, rarely in other languages. The…
Descriptors: Automation, Scoring, Accuracy, Responses
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Neto, Valter; Rolim, Vitor; Pinheiro, Anderson; Lins, Rafael Dueire; Gasevic, Dragan; Mello, Rafael Ferreira – IEEE Transactions on Learning Technologies, 2021
This article investigates the impact of educational contexts on automatic classification of online discussion messages according to cognitive presence, an essential construct of the community of inquiry model. In particular, the work reported in the article analyzed online discussion messages written in Brazilian Portuguese from two different…
Descriptors: Foreign Countries, Computer Mediated Communication, Discussion, Content Analysis
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Mu, Tong; Jetten, Andrea; Brunskill, Emma – International Educational Data Mining Society, 2020
In some computerized educational systems, there is evidence of students "wheel-spinning," where a student tries and repeatedly fails at an educational task for learning a skill. This may be particularly concerning in low resource settings. Prior research has focused on predicting and modeling wheel-spinning, but there has been little…
Descriptors: Computer Uses in Education, Artificial Intelligence, Academic Failure, Automation
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Jones, Daniel Marc; Cheng, Liying; Tweedie, M. Gregory – Canadian Journal of Learning and Technology, 2022
This article reviews recent literature (2011-present) on the automated scoring (AS) of writing and speaking. Its purpose is to first survey the current research on automated scoring of language, then highlight how automated scoring impacts the present and future of assessment, teaching, and learning. The article begins by outlining the general…
Descriptors: Automation, Computer Assisted Testing, Scoring, Writing (Composition)
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Lämsä, Joni; Uribe, Pablo; Jiménez, Abelino; Caballero, Daniela; Hämäläinen, Raija; Araya, Roberto – Journal of Learning Analytics, 2021
Scholars have applied automatic content analysis to study computer-mediated communication in computer-supported collaborative learning (CSCL). Since CSCL also takes place in face-to-face interactions, we studied the automatic coding accuracy of manually transcribed face-to-face communication. We conducted our study in an authentic higher-education…
Descriptors: Cooperative Learning, Computer Assisted Instruction, Synchronous Communication, Learning Analytics
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Chen, Huai-Yi; Wu, Chien-Ming; Lai, Chiung-Hui – IEEE Transactions on Education, 2019
Contribution: Prior studies indicate that students experimenting with characterization of optical planar waveguides use expensive ready-made prism couplers without clear understanding about construction of the entire optical measurement system. This paper presents a cost-effective modified bright-mode prism coupler that helps students learn…
Descriptors: Optics, Physics, Scientific Concepts, Science Equipment
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Stuart McLean; Paul Raine; Geoffrey Pinchbeck; Laura Huston; Young Ae Kim; Suzuka Nishiyama; Shotaro Ueno – Vocabulary Learning and Instruction, 2021
Vocableveltest.org is a testing platform on which users can create on- line self-marking meaning-recall (reading or listening) and form-recall (typing) tests that address a number of limitations of the existing vocabulary level tests and vocabulary size tests. A major limitation of many existing vocabulary tests is the written receptive…
Descriptors: Accuracy, Automation, Scoring, Writing (Composition)
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Liyanagunawardena, Tharindu R. – European Journal of Open, Distance and E-Learning, 2020
Transcripts and captions make videos more accessible to everyone. However, the time and resources required for manual transcription are a known barrier in creating accessible videos. This paper presents a small study where students (283) and tutors (27) reported their views on automatic transcriptions for recorded webinar videos. Despite not…
Descriptors: Transcripts (Written Records), Video Technology, Assistive Technology, Students with Disabilities
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