most citedConfirmation Bias in Generative AI Chatbots: Mechanisms, Risks, Mitigation Strategies, and Future Research Directions

1 citations · 1 across the 12 of their papers we have counts for

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12 papers

cs.HC2026

Can AI Reduce Acculturative Stress? Exploring the Role of AI-Mediated Speaking Practice in Chinese International Students' Perceived Language Insufficiency, Social Isolation, and Academic Pressure

Bin Zou, Yijia Yuan, Chenghao Wang +1

This study examined whether AI-mediated speaking practice can reduce acculturative stress among Chinese international students in UK universities. Using a sequential explanatory mi…

cs.HC2026

Psychological Mechanisms of Generative AI Discontinuance Intention among Chinese K-12 Teachers

Yiran Du, Qian Chen, Huimin He

This study examines the psychological mechanisms underlying Chinese K-12 teachers' discontinuance intention toward generative AI. Drawing on the Cognition-Affect-Conation framework…

cs.HC2026

Examining University Students' Artificial Intelligence-Generated Content (AIGC) Verification Intention from a Protection Motivation Perspective

Yiran Du

Artificial Intelligence-Generated Content (AIGC) is increasingly used by students to support learning tasks, yet its outputs may contain inaccuracies, fabricated references, bias,…

cs.HC2026

The impact of coercive, normative, and mimetic Stress on Chinese teachers' continuance intention to use generative AI: An integrated perspective of the Expectation-Confirmation Model and Institutional Theory

Kunjie Jia, Kai Cui, Huimin He +1

This study investigates Chinese teachers' continuance intention to use generative artificial intelligence (AI) by integrating the Expectation-Confirmation Model with Institutional…

cs.HC2026

Examining discontinuance of AI-mediated informal digital learning of English (AI-IDLE) among university students: Evidence from SEM and fsQCA

Yiran Du, Huimin He

This study examined university students' discontinuance intention towards AI-mediated informal digital learning of English (AI-IDLE). Drawing on the cognition-affect-conation frame…

cs.HC2026

Why Learners Drift In and Out: Examining Intermittent Discontinuance in AI-Mediated Informal Digital English Learning (AI-IDLE) Using SEM and fsQCA

Yiran Du, Huimin He

This study examined intermittent discontinuance in AI-mediated informal digital learning of English (AI-IDLE) through the cognition-affect-conation framework. Survey data were coll…

cs.AI2026

Enabling and Inhibitory Pathways of University Students' Willingness to Disclose AI Use: A Cognition-Affect-Conation Perspective

Yiran Du, Huimin He

The increasing integration of artificial intelligence (AI) in higher education has raised important questions regarding students' transparency in reporting AI-assisted work. This s…

cs.HC2026

A sequential explanatory mixed-methods study on the acceptance of a social robot for EFL speaking practice among Chinese primary school students: Insights from the Computers Are Social Actors (CASA) paradigm

Yiran Du, Jinlong Li, Huimin He +2

This study investigates Chinese primary school students' acceptance of a social robot for English-as-a-foreign-language (EFL) speaking practice through a sequential explanatory mix…

cs.HC2026

Examining EAP Students' AI Disclosure Intention: A Cognition-Affect-Conation Perspective

Yiran Du, Huimin He

The growing use of generative artificial intelligence (AI) in academic writing has raised increasing concerns regarding transparency and academic integrity in higher education. Thi…

cs.HC2026

Enabling and Inhibitory Pathways of Students' AI Use Concealment Intention in Higher Education: Evidence from SEM and fsQCA

Yiran Du, Huimin He

This study investigates students' AI use concealment intention in higher education by integrating the cognition-affect-conation (CAC) framework with a dual-method approach combinin…

cs.AI2026

Examining Users' Behavioural Intention to Use OpenClaw Through the Cognition--Affect--Conation Framework

Yiran Du

This study examines users' behavioural intention to use OpenClaw through the Cognition--Affect--Conation (CAC) framework. The research investigates how cognitive perceptions of the…

cs.HC2025★ 1 cited

Confirmation Bias in Generative AI Chatbots: Mechanisms, Risks, Mitigation Strategies, and Future Research Directions

Yiran Du

This article explores the phenomenon of confirmation bias in generative AI chatbots, a relatively underexamined aspect of AI-human interaction. Drawing on cognitive psychology and…