AI as a Debate Coach: A Mixed-Methods Analysis of Student Self-Efficacy and Perceptions in an AI-Assisted Debate
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| Title: | AI as a Debate Coach: A Mixed-Methods Analysis of Student Self-Efficacy and Perceptions in an AI-Assisted Debate |
|---|---|
| Language: | English |
| Authors: | Joan Wan-Ting Huang |
| Source: | Language Learning & Technology. 2026 30(1). |
| Availability: | National Foreign Language Resource Center at University of Hawaii. 1859 East-West Road #106, Honolulu, HI 96822. e-mail: llt@hawaii.edu; Web site: https://www.lltjournal.org/ |
| Peer Reviewed: | Y |
| Page Count: | 23 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Reports - Research Tests/Questionnaires |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Foreign Countries, English for Academic Purposes, College Students, Debate, Self Efficacy, Student Attitudes, Scaffolding (Teaching Technique), Technology Uses in Education, Artificial Intelligence, Educational Benefits, Intervention, Computer Attitudes, Second Language Learning |
| Geographic Terms: | Taiwan |
| DOI: | 10.64152/10125/73668 |
| ISSN: | 1094-3501 |
| Abstract: | Debate is an effective pedagogical approach, yet it presents significant challenges for EFL learners. While Artificial Intelligence (AI) chatbots are increasingly integrated into education, their application in multi-skilled tasks like debate preparation remains underexplored. This study investigated the impact of a two-phase AI-assisted intervention on 48 EFL learners' debating self-efficacy and perceptions. Phase 1 involved traditional debate preparation without AI assistance, focusing on foundational skill development through instructor-led instruction. Phase 2 introduced AI chatbots for refinement of arguments, rebuttals, and delivery practice, allowing students to enhance their debates through AI-powered scaffolding. Data were collected via self-efficacy questionnaires at three time points (pre-intervention, post-Phase 1, and post-Phase 2), a post-intervention perceptions questionnaire, written reflections, and focus group interviews. Repeated-measures ANOVAs revealed significant stepwise increases in students' debating self-efficacy across the three time points, with the most substantial gains observed in debate skills and language use. The perceptions questionnaire corroborated these findings, demonstrating that students rated AI as most effective for refining speeches, locating evidence, and developing arguments, while perceiving it as least helpful for oral delivery practice. Furthermore, qualitative analysis yielded nuanced and contextualized insights regarding both the benefits and limitations of AI-assisted debate preparation. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1502161 |
| Database: | ERIC |
| FullText | Text: Availability: 0 |
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| Header | DbId: eric DbLabel: ERIC An: EJ1502161 AccessLevel: 3 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1502161 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.64152/10125/73668 Languages: – Text: English PhysicalDescription: Pagination: PageCount: 23 Subjects: – SubjectFull: Foreign Countries Type: general – SubjectFull: English for Academic Purposes Type: general – SubjectFull: College Students Type: general – SubjectFull: Debate Type: general – SubjectFull: Self Efficacy Type: general – SubjectFull: Student Attitudes Type: general – SubjectFull: Scaffolding (Teaching Technique) Type: general – SubjectFull: Technology Uses in Education Type: general – SubjectFull: Artificial Intelligence Type: general – SubjectFull: Educational Benefits Type: general – SubjectFull: Intervention Type: general – SubjectFull: Computer Attitudes Type: general – SubjectFull: Second Language Learning Type: general – SubjectFull: Taiwan Type: general Titles: – TitleFull: AI as a Debate Coach: A Mixed-Methods Analysis of Student Self-Efficacy and Perceptions in an AI-Assisted Debate Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Joan Wan-Ting Huang IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2026 Identifiers: – Type: issn-electronic Value: 1094-3501 Numbering: – Type: volume Value: 30 – Type: issue Value: 1 Titles: – TitleFull: Language Learning & Technology Type: main |
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