The Impact of Culturally Adaptive Feedback in Information-Interaction Systems on Language-Learning Motivation and Outcomes
DOI:
https://doi.org/10.70393/6a6574.333036ARK:
https://n2t.net/ark:/40704/JET.v2n1a01Disciplines:
Educational PsychologySubjects:
Learning MotivationReferences:
5Keywords:
Information-interaction System, Culturally Adaptive Feedback, Language-learning Motivation, Learning Outcomes, Cross-cultural EducationAbstract
Grounded in social-cognitive learning theory and the cross-cultural adaptation framework, this mixed-methods study tests how culturally adaptive feedback (CAF) delivered through an information-interaction system affects university EFL learners’ language-learning motivation and learning outcomes. One hundred and twenty second-year students were randomly allocated to a CAF group and a control group for eight weeks. The quantitative phase employed a 2 (group) × 2 (time) mixed-design ANOVA; the qualitative phase conducted semi-structured interviews with 18 learners, followed by thematic analysis. The findings are as follows: (1) post-test motivation in the CAF group was significantly higher than in the control group, group × time interaction F(1, 118)=15.27, p = .0002, partial η² = .115; (2) the growth rate of learning outcomes in the CAF group significantly surpassed that of the control group, interaction F(1, 118)=12.45, p = .0007, partial η² = .095, end-point Cohen’s d = 2.04; and (3) three high-frequency themes—“enhanced self-efficacy,” “high cultural relevance,” and “increased engagement”—were distilled from the interviews, corroborating the motivation-to-outcome pathway. The study extends the explanatory power of CAF in cross-cultural language learning, demonstrates the motivational amplification generated by culturally contextualised feedback in tandem with self-efficacy, and provides empirical evidence for feedback design in online platforms and classroom practice.
References
[1] Fan, X. Y. (2023). Design and implementation of an online language-interaction learning system based on speech-recognition technology. Automation and Instrumentation, (7), 187–190, 195.
[2] Zhao, J. (2022). The impact of emotional interaction on learning motivation in online collaborative learning [Doctoral dissertation, Northeast Normal University].
[3] Li, M., & Yan, D. (2023). Effects of bilingual interactional context on language control and cognitive control. Neijiang Science and Technology, 44(10), 93–95.
[4] Ai, Y., & Tang, Y. (2021). Waiting interval and system responsiveness effects on waiting experience and learning outcomes in voice interaction. Human Ergonomics, 27(1), 1–6.
[5] Jiang, Y., Zhang, T., & Liu, H. (2025). Research and Design of Blockchain-based Propagation Algorithm for IP Tags Using Local Random Walk in Big Data Marketing. Authorea Preprints.

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