Evaluating the Comparative Effectiveness of CAPT-Based vs. Native Speaker-Led Pronunciation Training
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| Title: | Evaluating the Comparative Effectiveness of CAPT-Based vs. Native Speaker-Led Pronunciation Training |
|---|---|
| Language: | English |
| Authors: | Dana Ondrušková (ORCID |
| Source: | Contemporary Educational Technology. 2025 17(4):608. |
| Availability: | Contemporary Educational Technology. Faculty of Communication Sciences, Anadolu University, Yunus Emre Campus, Eskisehir 26470, Turkey. e-mail: editor@cedtech.net; Web site: http://www.cedtech.net |
| Peer Reviewed: | Y |
| Page Count: | 15 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Computer Assisted Instruction, Artificial Intelligence, Second Language Instruction, Second Language Learning, Instructional Effectiveness, Pronunciation Instruction, French, Listening Comprehension, Accuracy, Mutual Intelligibility, Intonation, Information Technology, Foreign Countries |
| Geographic Terms: | Czech Republic |
| Abstract: | This study examines the effectiveness of pronunciation training by comparing two instructional methods: native speaker-led instruction and artificial intelligence (AI)-driven pronunciation tools. The research aims to determine whether AI-assisted pronunciation training can serve as an effective alternative or complement to traditional instruction. This is particularly relevant for language programs where access to native speakers is limited. The study employs a quantitative research design, analyzing pronunciation accuracy, intelligibility, and listening comprehension among A1-level French learners. A statistical comparison of learners' performance in both groups was conducted, including Chi-square tests and standard deviation analysis. The findings suggest that AI-based pronunciation training is at least as effective as native speaker-led instruction, with students in the CAPT group performing even better, particularly in intelligibility and intonation. The reduced performance variability among AI-trained learners suggests that these tools provide a structured and uniform learning experience. These insights contribute to optimizing pronunciation teaching methods, highlighting the potential of AI as a scalable and accessible pronunciation training solution in foreign language education. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1494795 |
| Database: | ERIC |
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| Header | DbId: eric DbLabel: ERIC An: EJ1494795 AccessLevel: 3 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Evaluating the Comparative Effectiveness of CAPT-Based vs. Native Speaker-Led Pronunciation Training – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Dana+Ondrušková%22">Dana Ondrušková</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-9591-5673">0000-0001-9591-5673</externalLink>) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="SO" term="%22Contemporary+Educational+Technology%22"><i>Contemporary Educational Technology</i></searchLink>. 2025 17(4):608. – Name: Avail Label: Availability Group: Avail Data: Contemporary Educational Technology. Faculty of Communication Sciences, Anadolu University, Yunus Emre Campus, Eskisehir 26470, Turkey. e-mail: editor@cedtech.net; Web site: http://www.cedtech.net – Name: PeerReviewed Label: Peer Reviewed Group: SrcInfo Data: Y – Name: Pages Label: Page Count Group: Src Data: 15 – Name: DatePubCY Label: Publication Date Group: Date Data: 2025 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Journal Articles<br />Reports - Research – Name: Subject Label: Descriptors Group: Su Data: <searchLink fieldCode="DE" term="%22Computer+Assisted+Instruction%22">Computer Assisted Instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Second+Language+Instruction%22">Second Language Instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Second+Language+Learning%22">Second Language Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Instructional+Effectiveness%22">Instructional Effectiveness</searchLink><br /><searchLink fieldCode="DE" term="%22Pronunciation+Instruction%22">Pronunciation Instruction</searchLink><br /><searchLink fieldCode="DE" term="%22French%22">French</searchLink><br /><searchLink fieldCode="DE" term="%22Listening+Comprehension%22">Listening Comprehension</searchLink><br /><searchLink fieldCode="DE" term="%22Accuracy%22">Accuracy</searchLink><br /><searchLink fieldCode="DE" term="%22Mutual+Intelligibility%22">Mutual Intelligibility</searchLink><br /><searchLink fieldCode="DE" term="%22Intonation%22">Intonation</searchLink><br /><searchLink fieldCode="DE" term="%22Information+Technology%22">Information Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink> – Name: Subject Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Czech+Republic%22">Czech Republic</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This study examines the effectiveness of pronunciation training by comparing two instructional methods: native speaker-led instruction and artificial intelligence (AI)-driven pronunciation tools. The research aims to determine whether AI-assisted pronunciation training can serve as an effective alternative or complement to traditional instruction. This is particularly relevant for language programs where access to native speakers is limited. The study employs a quantitative research design, analyzing pronunciation accuracy, intelligibility, and listening comprehension among A1-level French learners. A statistical comparison of learners' performance in both groups was conducted, including Chi-square tests and standard deviation analysis. The findings suggest that AI-based pronunciation training is at least as effective as native speaker-led instruction, with students in the CAPT group performing even better, particularly in intelligibility and intonation. The reduced performance variability among AI-trained learners suggests that these tools provide a structured and uniform learning experience. These insights contribute to optimizing pronunciation teaching methods, highlighting the potential of AI as a scalable and accessible pronunciation training solution in foreign language education. – Name: AbstractInfo Label: Abstractor Group: Ab Data: As Provided – Name: DateEntry Label: Entry Date Group: Date Data: 2026 – Name: AN Label: Accession Number Group: ID Data: EJ1494795 |
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| RecordInfo | BibRecord: BibEntity: Languages: – Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 608 Subjects: – SubjectFull: Computer Assisted Instruction Type: general – SubjectFull: Artificial Intelligence Type: general – SubjectFull: Second Language Instruction Type: general – SubjectFull: Second Language Learning Type: general – SubjectFull: Instructional Effectiveness Type: general – SubjectFull: Pronunciation Instruction Type: general – SubjectFull: French Type: general – SubjectFull: Listening Comprehension Type: general – SubjectFull: Accuracy Type: general – SubjectFull: Mutual Intelligibility Type: general – SubjectFull: Intonation Type: general – SubjectFull: Information Technology Type: general – SubjectFull: Foreign Countries Type: general – SubjectFull: Czech Republic Type: general Titles: – TitleFull: Evaluating the Comparative Effectiveness of CAPT-Based vs. Native Speaker-Led Pronunciation Training Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Dana Ondrušková IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2025 Numbering: – Type: volume Value: 17 – Type: issue Value: 4 Titles: – TitleFull: Contemporary Educational Technology Type: main |
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