Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Toward sustained interaction: investigating the drivers of continued use of AI chatbots for language learning in Confucius Institutes
2
Zitationen
3
Autoren
2025
Jahr
Abstract
Introduction Sustaining learners' continued use of AI chatbots for Mandarin instruction is a key challenge for EdTech developers, educators, and Confucius Institutes. Building on technology-continuance perspectives, this study examines how cognitive appraisals (performance expectancy, effort expectancy, facilitating conditions, social influence) shape learning motivation, learning satisfaction, and continuance intention among Chinese language learners. Methods A cross-sectional survey using convenience sampling was administered to learners at 16 Confucius Institutes across eight Southeast Asian countries (N = 737), all with prior experience using AI chatbots for Mandarin learning. A hypothesized model was tested via structural equation modeling (SEM) to assess direct effects on motivation, satisfaction, and continuance intention, as well as indirect (mediated) effects via motivation and satisfaction. Results Performance expectancy, effort expectancy, social influence, and facilitating conditions each had significant positive effects on learning motivation and learning satisfaction. For continuance intention, performance expectancy, effort expectancy, and facilitating conditions showed significant direct effects, whereas the direct effect of social influence was non-significant. Learning motivation and learning satisfaction acted as critical mediators, transmitting the effects of social influence and technological perceptions to continuance intention, thereby strengthening sustained engagement. Discussion Findings support a unified cognitive-affective model of technology continuance in AI-mediated language learning. To enhance sustained chatbot use, stakeholders should: (1) raise perceived usefulness through curriculum-aligned tasks and feedback, (2) reduce effort via intuitive design and scaffolding, (3) improve facilitating conditions (training, access, support), and (4) cultivate motivation and satisfaction through adaptive, engaging learning experiences. Although social influence alone does not directly drive continuance, it indirectly promotes sustained use by elevating motivation and satisfaction.
Ähnliche Arbeiten
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller
1999 · 5.632 Zit.
An experiment in linguistic synthesis with a fuzzy logic controller
1975 · 5.562 Zit.
A FRAMEWORK FOR REPRESENTING KNOWLEDGE
1988 · 4.548 Zit.
Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy
2023 · 3.351 Zit.