4 countries - TEACHERS about Learning with AI - JULY 2024

Published: 10 June 2025| Version 1 | DOI: 10.17632/2n4ckjnv3c.1
Contributors:
Sneh Bansal, Yuanting Liao, Mursidi Murah, Carmen CIORANU

Description

The study employed an exploratory, cross-sectional survey design aimed at understanding how teachers from four countries—Romania, India, China, and Brunei—define, use, and evaluate the effectiveness of artificial intelligence (AI)-based tools in their teaching practice. The research focused on identifying patterns of AI integration across three key phases of instruction (before, during, and after class) and examined their correlation with contextual factors such as teaching experience, professional development, digital infrastructure, and subject area. Data were collected in July 2024 from 252 teachers (68 from Romania, 58 from India, 89 from China, and 37 from Brunei), recruited through academic networks and institutional partnerships using convenience and snowball sampling. Eligible participants were active teachers with regular access to the internet and digital devices; no restrictions were imposed regarding age, gender, or subject specialization. Participation was entirely voluntary and anonymous, with informed consent obtained prior to survey completion. No personal or sensitive data were collected, and given the non-interventional nature of the study and the absence of vulnerable populations, formal ethical approval was not required under national guidelines. Data were gathered via a structured online questionnaire (in English) distributed through Google Forms, comprising 23 items with both closed and open-ended questions organized into sections on demographics, digital infrastructure access, cognitive representations of AI, professional training, practical integration of AI in lessons (including frequency and concrete examples), types of tools used, perceived effectiveness (measured on Likert scales), and barriers reported by non-users. A key finding was that national context significantly shaped AI integration: a Chi² test revealed a statistically significant association between country of origin and the actual use of AI in teaching (χ² = 19.59, df = 6, p = 0.003), suggesting that policy, infrastructure, digital literacy, and professional culture are critical to how educators engage with AI in education.

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