Latent Profile Analysis of AI Literacy and Trust in Mathematics Teachers and Their Relations with AI Dependency and 21st-Century Skills DOI Creative Commons
Tommy Tanu Wijaya, Qingchun Yu, Yiming Cao

и другие.

Behavioral Sciences, Год журнала: 2024, Номер 14(11), С. 1008 - 1008

Опубликована: Окт. 30, 2024

Artificial Intelligence (AI) technology, particularly generative AI, has positively impacted education by enhancing mathematics instruction with personalized learning experiences and improved data analysis. Nonetheless, variations in AI literacy, trust dependency on these technologies among teachers can significantly influence their development of 21st-century skills such as self-confidence, problem-solving, critical thinking, creative collaboration. This study aims to identify distinct profiles trust, examines how correlate the aforementioned skills. Using a cross-sectional research design, collected from 489 China. A robust three-step latent profile analysis method was utilized analyze data. The revealed five literacy teachers: (1) Basic Engagement; (2) Developing Literacy, Skeptical AI; (3) Balanced Competence; (4) Advanced Integration; (5) Expertise Confidence. found that an increase directly correlates decrease findings underscore need for careful integration educational settings. Excessive reliance lead detrimental dependencies, which may hinder essential contributes existing literature providing empirical evidence impact professional teachers. It also offers practical implications policymakers institutions consider balanced approaches integration, ensuring enhances rather than replaces thinking problem-solving capacities educators.

Язык: Английский

Giving Away the Immersive L2 Learning Experiences in GenAI‐Mediated Contexts: The Contributions of Cognitive and Affective Factors DOI Open Access

Zhou Guan-qiong

European Journal of Education, Год журнала: 2025, Номер 60(2)

Опубликована: Март 23, 2025

ABSTRACT Immersive learning plays a crucial role in effective second language (L2) acquisition, but many learners face limited opportunities to interact with native speakers. While existing research highlights the importance of immersion L2 learning, there is still gap understanding how Generative AI (GenAI) can provide greater access such immersive environments. This study aims address this by exploring factors influencing GenAI‐mediated learning. Drawing upon cognitive‐affective model control‐value theory, and technology acceptance model, examined impact cognitive (e.g., perceived ease use usefulness) affective enjoyment boredom) on immersion, using sample 460 Chinese college learners. Structural equation modelling Amos 24 was applied analyse data, yielding several key findings. (i) Perceived positively predicted usefulness had no direct effect or boredom. (ii) influenced while negatively affecting (iii) Enjoyment positive predictor whereas boredom significant effect. (iv) Mediation analysis revealed that indirectly through not combination usefulness. The concludes implications for practice suggestions future research.

Язык: Английский

Процитировано

0

Latent Profile Analysis of AI Literacy and Trust in Mathematics Teachers and Their Relations with AI Dependency and 21st-Century Skills DOI Creative Commons
Tommy Tanu Wijaya, Qingchun Yu, Yiming Cao

и другие.

Behavioral Sciences, Год журнала: 2024, Номер 14(11), С. 1008 - 1008

Опубликована: Окт. 30, 2024

Artificial Intelligence (AI) technology, particularly generative AI, has positively impacted education by enhancing mathematics instruction with personalized learning experiences and improved data analysis. Nonetheless, variations in AI literacy, trust dependency on these technologies among teachers can significantly influence their development of 21st-century skills such as self-confidence, problem-solving, critical thinking, creative collaboration. This study aims to identify distinct profiles trust, examines how correlate the aforementioned skills. Using a cross-sectional research design, collected from 489 China. A robust three-step latent profile analysis method was utilized analyze data. The revealed five literacy teachers: (1) Basic Engagement; (2) Developing Literacy, Skeptical AI; (3) Balanced Competence; (4) Advanced Integration; (5) Expertise Confidence. found that an increase directly correlates decrease findings underscore need for careful integration educational settings. Excessive reliance lead detrimental dependencies, which may hinder essential contributes existing literature providing empirical evidence impact professional teachers. It also offers practical implications policymakers institutions consider balanced approaches integration, ensuring enhances rather than replaces thinking problem-solving capacities educators.

Язык: Английский

Процитировано

2