Exploring students’ acceptance of an artificial intelligence speech evaluation program for EFL speaking practice: an application of the Integrated Model of Technology Acceptance

Zou, Bin; Lyu, Qinglang; Han, Yining; Li, Zijing; Zhang, Weilei

doi:10.1080/09588221.2023.2278608

Cited by 9 publications

(3 citation statements)

References 53 publications

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“…This suggested that the platform had successfully integrated into the learners' regular practice routines, indicating a sustainable model for ongoing academic language development. The positive findings aligned with previous studies that have noted positive perceptions and attitudes towards AI tools for speaking practice (Loewen et al, 2019;Zou, Du, et al, 2023;Zou et al, 2021;Zou, Lyu, et al, 2023).…”

Section: Discussionsupporting

confidence: 89%

“…This social aspect of learning encouraged peer interactions and feedback, further enriching the learning experience and providing a more engaging and interactive environment for speaking skill development. Moreover, an investigation into the acceptance of AI speech evaluation systems by Zou, Lyu et al (2023), revealed positive student attitudes towards using these cuttingedge technologies for speaking practice. The integration of AI in speaking skill development not only offers personalized and immediate feedback but also fosters a more engaging, interactive, and efficient learning environment, addressing the challenges of individualized attention and extensive practice needs.…”

Section: Introductionmentioning

confidence: 99%

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Bridging the Gap: Linking AI Technology Acceptance to Actual Improvements in EAP Learners' Speaking Skills

He,

Zou,

2024

Preprint

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The integration of artificial intelligence (AI) technologies into educational platforms offered novel approaches to English for Academic Purposes (EAP) learning and teaching. This study evaluated the EAP Talk platform, an AI-driven tool designed to enhance speaking skills among EAP learners. Utilizing a mixed-methods approach, this research encompassed pre- and post-tests, questionnaires, and semi- structured interviews to measure the platform's impact on various speaking competencies, including fluency, grammar, vocabulary, pronunciation, and organization of ideas. Results demonstrated significant improvements across all evaluated speaking skills, with learners reporting enhanced performance and increased confidence. The study also explored user engagement with the platform, revealing that EAP Talk's personalized feedback and the ability to tailor exercises to individual needs were highly valued by participants. However, issues such as the accuracy of speech recognition and automated scoring were noted, highlighting areas for future enhancement. This study contributed to the field by providing empirical evidence on the effectiveness of AI-assisted platforms in improving language proficiency within an EAP context. It also identifies the potential for such technologies to complement traditional learning methods, thereby enriching the educational experience and offering learners more personalized and adaptive learning opportunities.

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Section: Discussionsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Bridging the Gap: Linking AI Technology Acceptance to Actual Improvements in EAP Learners' Speaking Skills

He,

Zou,

2024

Preprint

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“…Interviews with students and teachers suggested that speaking to ASR-based websites was less intimidating than speaking in front of peers or people, indicating potential benefits of ASR technology in alleviating FLSA and making language learning more accessible and less stressful. Given the benefits, many AI tools for speaking practice has been increasingly popular (Lehman et al, 2020), such as Duolingo (Rachels & Rockinson-Szapkiw, 2018), Liulishuo (Chang et al, 2022, EAP Talk (Zou, Lyu, et al, 2023), ChatGPT (Cat et al, 2023), Call Annie (Wan & Moorhouse, 2024), etc.…”

Section: Ai Tools For L2 Speaking Practicementioning

confidence: 99%

Personalizing AI Tools for Second Language Practice: The Role of Gender and Autistic Traits

Du,

Wang,

Zou

et al. 2024

Preprint

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This study examined the relationship among autistic traits, gender, and perceptions of artificial intelligence (AI) tools for second language (L2) speaking practice among neurotypical university students. The investigation included 111 participants and utilized the Broad Autism Phenotype Questionnaire to assess Autistic Traits (AU) and the sub-traits Aloof (AF), Rigid (RD), and Pragmatic Language (PL). It also employed various scales to measure perceptions, including Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Attitude (AT), Behavioral Intention (BI), and Usage Behavior (UB). The findings indicated no significant differences in AU, AF, RD, and PL between males and females. Similarly, there were no significant differences in PU, AT, BI, and UB between genders, although males demonstrated marginally higher scores in PEOU than females. Autistic traits showed specific correlations with perceptions of AI tools: AU was negatively correlated with PU, AT, and marginally with PEOU; AF was marginally negatively correlated with PU and AT; RD was negatively correlated with PEOU, AT, and BI, and marginally with PU. Furthermore, the study highlighted the moderating role of gender in the relationship between autistic traits and perceptions of AI tools. Specifically, the effects of autistic traits on perceptions were more pronounced in males than in females, particularly the relationships between PEOU and AF, UB and AU, and UB and PL. This research highlighted the importance of considering autistic traits in educational technology deployment, advocating for customizable AI solutions to better meet diverse learner needs. The outcomes contributed to a more inclusive understanding of educational technology, emphasizing the need to adapt AI tools to enhance learning experiences for all students, regardless of gender or neurodiversity.

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English speaking with artificial intelligence (AI): The roles of enjoyment, willingness to communicate with AI, and innovativeness

Huang,

Zou

2024

Computers in Human Behavior

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Exploring students’ acceptance of an artificial intelligence speech evaluation program for EFL speaking practice: an application of the Integrated Model of Technology Acceptance

Cited by 9 publications

References 53 publications

Bridging the Gap: Linking AI Technology Acceptance to Actual Improvements in EAP Learners' Speaking Skills

Bridging the Gap: Linking AI Technology Acceptance to Actual Improvements in EAP Learners' Speaking Skills

Personalizing AI Tools for Second Language Practice: The Role of Gender and Autistic Traits

English speaking with artificial intelligence (AI): The roles of enjoyment, willingness to communicate with AI, and innovativeness

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