Reshaping the Language Learning Landscape: Factors Influencing Learners' Use of Open‐Source Text‐to‐Video AI (Open‐Sora) in Second Language Acquisition.
Background: Following the disruptive impact of ChatGPT on language learning, the emergence of Sora has once again attracted considerable attention in the field. This novel generative AI product offers new learning modes and resources, bringing new possibilities for the transformation of language acq...
| Publicado en: | Journal of Computer Assisted Learning Vol. 42; no. 4; pp. 1 - 28 |
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| Autores principales: | , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Aug2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=195655205&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 195655205 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02664909 6M1 jtl: Journal of Computer Assisted Learning issn: 02664909 maglogo: Y pubinfo: dt: Aug2026 vid: 42 iid: 4 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 195655205 195655205 195655205 10.1002/jcal.70277 195655205 ppf: 1 ppct: 27 formats: tig: atl: Reshaping the Language Learning Landscape: Factors Influencing Learners' Use of Open‐Source Text‐to‐Video AI (Open‐Sora) in Second Language Acquisition. aug: au: Jiang, Yang Wang, Chengliang affil: School of Marxism (Basic Teaching Department), Xizang Agricultural and Animal Husbandry University, Nyingchi, China sug: subj: Students, College Psychosocial Factors Language Education Artificial Intelligence, Generative Utilization Audiovisual Production Language Development Self-Efficacy Intention Attitude to Computers Evaluation Human Funding Source China Male Female Young Adult Conceptual Framework Structural Equation Modeling Questionnaires Descriptive Statistics T-Tests One-Way Analysis of Variance Confidence Intervals Male Female ab: Background: Following the disruptive impact of ChatGPT on language learning, the emergence of Sora has once again attracted considerable attention in the field. This novel generative AI product offers new learning modes and resources, bringing new possibilities for the transformation of language acquisition. However, research systematically investigating learners' intention to use such text‐to‐video AI tools remains scarce. Objectives: This study utilises text‐to‐video AI‐generated teaching materials produced using Open‐Sora (an open‐source implementation inspired by Sora, not the unreleased official Sora model) as experimental content, aiming to explore college students' intention to use this system for second language (L2) learning and their perceptions of the technology. Methods: In response, this study, grounded in the stimulus–organism–response framework, employs the Information System Success Model, the Task‐Technology Fit model, and the Unified Theory of Acceptance and Use of Technology. Data were collected from 335 university students at universities in Western China and analysed using a structural equation model. Results and Conclusions: Performance expectancy, L2 enjoyment (LEE), and self‐efficacy (SE) significantly and positively predict Behavioural Intention (BI) to use Open‐Sora, whereas effort expectancy and facilitating conditions do not significantly predict BI. Furthermore, SE partially mediates the relationship between LEE and BI. This study enhances our understanding of college students' interactions with text‐to‐video AI in L2 learning contexts and provides implications for the educational use of such AI technologies. Lay Summary: What is currently known about this topic? ○The emergence of large language models has provided new technological tools and learning approaches for L2 learning.○AI technologies, especially text‐to‐video tools, are expected to bring new learning methods and teaching resources for L2 learning.○A systematic exploration of learners' intention to use AI text‐to‐video technology remains extremely limited at present.What does this paper add? ○Within the context of artificial intelligence, the study has introduced the S‐O‐R framework.○This study updates and expands upon ISSM, TTF, and UTAUT.○This study provides preliminary insights into some of the underlying psychological mechanisms of technology acceptance and usage.Implications for practice/or policy ○This study provides some reference for educators in attempting to design and apply generative AI tools in the classroom.○This study demonstrates the potential application of generative AI tools in second language classrooms.○The findings mainly provide implications for instructional design at both the classroom and curriculum levels. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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