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Anna Rechtácková; Radek Pelánek; Tomáš Effenberger – ACM Transactions on Computing Education, 2025
Code quality is a critical aspect of programming, as high-quality code is easier to maintain, and code maintenance constitutes the majority of software costs. Consequently, code quality should be emphasized in programming education. While previous research has identified numerous code quality defects commonly made by students, the current state…
Descriptors: Programming, Computer Science Education, Error Patterns, Automation
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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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Xiao, Wenqi; Park, Moonyoung – International Journal of Computer-Assisted Language Learning and Teaching, 2021
With the advancement of automatic speech recognition (ASR) technology, ASR-based pronunciation assessment can diagnose learners' pronunciation problems. Meanwhile, ASR-based pronunciation training allows more opportunities for pronunciation practice. This study aims to investigate the effectiveness of ASR technology in diagnosing English…
Descriptors: Automation, Computer Software, Handheld Devices, Diagnostic Tests
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Mirzaei, Maryam Sadat; Meshgi, Kourosh; Kawahara, Tatsuya – Research-publishing.net, 2016
This study investigates the use of Automatic Speech Recognition (ASR) systems to epitomize second language (L2) listeners' problems in perception of TED talks. ASR-generated transcripts of videos often involve recognition errors, which may indicate difficult segments for L2 listeners. This paper aims to discover the root-causes of the ASR errors…
Descriptors: Automation, Computer Software, Listening Skills, Error Patterns
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Smith, Chad; Allman, Tamby; Crocker, Samantha – Online Learning, 2017
This study and discussion center upon the use of "YouTube's" automatic captioning feature with college-age adult readers. The study required 75 participants with college experience to view brief middle school science videos with automatic captioning on "YouTube" and answer comprehension questions based on material presented…
Descriptors: Educational Technology, Technology Uses in Education, Video Technology, Middle Schools
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Parton, Becky Sue – Journal of Open, Flexible and Distance Learning, 2016
Providing captions for videos used in online courses is an area of interest for institutions of higher education. There are legal and ethical ramifications as well as time constraints to consider. Captioning tools are available, but some universities rely on the auto-generated YouTube captions. This study looked at a particular type of video--the…
Descriptors: Video Technology, Layout (Publications), Visual Aids, Electronic Publishing
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Feng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating
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Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis