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The Use of Artificial Intelligence to Promote Autonomous Pronunciation Learning: Segmental and Suprasegmental Features Perspective

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Title: The Use of Artificial Intelligence to Promote Autonomous Pronunciation Learning: Segmental and Suprasegmental Features Perspective
Authors: Senowarsito, Sukma Nur Ardini
Source: Indonesian Journal of English Language Teaching and Applied Linguistics. 2023 8(2):133-147.
Availability: Indonesian Journal of English Language Teaching and Applied Linguistics. English Department, Faculty of Education and Teacher Training, State Islamic Institute of Samarinda, Indonesia. e-mail: ijeltalj@gmail.com; Web site: https://ijeltal.org/index.php/ijeltal
Peer Reviewed: Y
Page Count: 15
Publication Date: 2023
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Artificial Intelligence, Suprasegmentals, Pronunciation Instruction, Language Proficiency, Intonation, Phonology, Language Rhythm, Web Sites, Phonemes, Correlation, Teaching Methods, Computer Software, Second Language Learning, Second Language Instruction, Undergraduate Students, English (Second Language), Independent Study, Foreign Countries
Geographic Terms: Indonesia
ISSN: 2527-6492
2527-8746
Abstract: The study aimed at investigating the effects of autonomous pronunciation learning using AI as well as the experiences of autonomous pronunciation learning using AI by higher level students. Explanatory sequential mixed-method research using both quantitative and qualitative methods was employed within thirty-two students from Universitas PGRI Semarang's first-year students serving as the sample. Assessments, interviews, and an evaluation of instructional materials were used as the instruments. Through pre- and post-testing, quantitative analysis was used to evaluate the students' pronunciation proficiency. Quantitative data analysis was done using SPSS. However, a qualitative analysis was used to review the interview. To bolster the findings of the tests, it was descriptively examined. After the treatments using an AI based application named ELSA, there was a significant correlation between the use of AI and autonomous pronunciation learning. However, ELSA has certain shortcomings. It appears to be primarily concerned with segmental than suprasegmental features. Only intonation is available from among all the features offered to practice suprasegmental features. While students found it difficult to emphasize words, there is no other practice for suprasegmental qualities. In reality, the ELSA website states that its curriculum covers core English skills such as word stress, intonation, rhythm, listening, and conversation. As a result, the ELSA creator may take this criticism into consideration as they continue to improve their product. It implies that the creator is responsive to the concerns or suggestions of their customers or users, which can contribute to the ongoing development and success of the product.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1409001
Database: ERIC
FullText Text:
  Availability: 0
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  Data: The Use of Artificial Intelligence to Promote Autonomous Pronunciation Learning: Segmental and Suprasegmental Features Perspective
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  Data: <searchLink fieldCode="AR" term="%22Senowarsito%22">Senowarsito</searchLink><br /><searchLink fieldCode="AR" term="%22Sukma+Nur+Ardini%22">Sukma Nur Ardini</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Indonesian+Journal+of+English+Language+Teaching+and+Applied+Linguistics%22"><i>Indonesian Journal of English Language Teaching and Applied Linguistics</i></searchLink>. 2023 8(2):133-147.
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  Data: Indonesian Journal of English Language Teaching and Applied Linguistics. English Department, Faculty of Education and Teacher Training, State Islamic Institute of Samarinda, Indonesia. e-mail: ijeltalj@gmail.com; Web site: https://ijeltal.org/index.php/ijeltal
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  Data: Y
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  Data: 15
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  Data: 2023
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  Data: Journal Articles<br />Reports - Research
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  Data: <searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Suprasegmentals%22">Suprasegmentals</searchLink><br /><searchLink fieldCode="DE" term="%22Pronunciation+Instruction%22">Pronunciation Instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Language+Proficiency%22">Language Proficiency</searchLink><br /><searchLink fieldCode="DE" term="%22Intonation%22">Intonation</searchLink><br /><searchLink fieldCode="DE" term="%22Phonology%22">Phonology</searchLink><br /><searchLink fieldCode="DE" term="%22Language+Rhythm%22">Language Rhythm</searchLink><br /><searchLink fieldCode="DE" term="%22Web+Sites%22">Web Sites</searchLink><br /><searchLink fieldCode="DE" term="%22Phonemes%22">Phonemes</searchLink><br /><searchLink fieldCode="DE" term="%22Correlation%22">Correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Teaching+Methods%22">Teaching Methods</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Software%22">Computer Software</searchLink><br /><searchLink fieldCode="DE" term="%22Second+Language+Learning%22">Second Language Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Second+Language+Instruction%22">Second Language Instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Undergraduate+Students%22">Undergraduate Students</searchLink><br /><searchLink fieldCode="DE" term="%22English+%28Second+Language%29%22">English (Second Language)</searchLink><br /><searchLink fieldCode="DE" term="%22Independent+Study%22">Independent Study</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Indonesia%22">Indonesia</searchLink>
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  Data: 2527-6492<br />2527-8746
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The study aimed at investigating the effects of autonomous pronunciation learning using AI as well as the experiences of autonomous pronunciation learning using AI by higher level students. Explanatory sequential mixed-method research using both quantitative and qualitative methods was employed within thirty-two students from Universitas PGRI Semarang's first-year students serving as the sample. Assessments, interviews, and an evaluation of instructional materials were used as the instruments. Through pre- and post-testing, quantitative analysis was used to evaluate the students' pronunciation proficiency. Quantitative data analysis was done using SPSS. However, a qualitative analysis was used to review the interview. To bolster the findings of the tests, it was descriptively examined. After the treatments using an AI based application named ELSA, there was a significant correlation between the use of AI and autonomous pronunciation learning. However, ELSA has certain shortcomings. It appears to be primarily concerned with segmental than suprasegmental features. Only intonation is available from among all the features offered to practice suprasegmental features. While students found it difficult to emphasize words, there is no other practice for suprasegmental qualities. In reality, the ELSA website states that its curriculum covers core English skills such as word stress, intonation, rhythm, listening, and conversation. As a result, the ELSA creator may take this criticism into consideration as they continue to improve their product. It implies that the creator is responsive to the concerns or suggestions of their customers or users, which can contribute to the ongoing development and success of the product.
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  Data: 2024
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  Data: EJ1409001
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RecordInfo BibRecord:
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    PhysicalDescription:
      Pagination:
        PageCount: 15
        StartPage: 133
    Subjects:
      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Suprasegmentals
        Type: general
      – SubjectFull: Pronunciation Instruction
        Type: general
      – SubjectFull: Language Proficiency
        Type: general
      – SubjectFull: Intonation
        Type: general
      – SubjectFull: Phonology
        Type: general
      – SubjectFull: Language Rhythm
        Type: general
      – SubjectFull: Web Sites
        Type: general
      – SubjectFull: Phonemes
        Type: general
      – SubjectFull: Correlation
        Type: general
      – SubjectFull: Teaching Methods
        Type: general
      – SubjectFull: Computer Software
        Type: general
      – SubjectFull: Second Language Learning
        Type: general
      – SubjectFull: Second Language Instruction
        Type: general
      – SubjectFull: Undergraduate Students
        Type: general
      – SubjectFull: English (Second Language)
        Type: general
      – SubjectFull: Independent Study
        Type: general
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: Indonesia
        Type: general
    Titles:
      – TitleFull: The Use of Artificial Intelligence to Promote Autonomous Pronunciation Learning: Segmental and Suprasegmental Features Perspective
        Type: main
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          Name:
            NameFull: Senowarsito
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            NameFull: Sukma Nur Ardini
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              Type: published
              Y: 2023
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              Value: 2527-6492
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              Value: 2527-8746
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              Value: 8
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            – TitleFull: Indonesian Journal of English Language Teaching and Applied Linguistics
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