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<p>A mixed-methods approach was used to investigate teachers’ perceived opportunities and concerns in Lebanon (n = 264) regarding the integration of Artificial Intelligence (AI) into teaching and learning. The questionnaire was grounded in insights from Focus Group Discussions (FGDs) with teachers (n = 16). Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were employed to develop an AI Teacher Competency Framework. Harman’s single-factor test was used to check for Common Method Bias (CMB). Multiple linear regression indicated no multicollinearity. Teachers highlighted both the benefits and challenges of integrating AI into the classroom. Student learning was central to shaping teachers’ intention to adopt AI, their engagement in training, and AI ethics. Further, the frequency of AI use and prior training significantly influenced teachers’ evaluations of AI’s role in education. Teachers identified teaching methods, assessment, and classroom activities as areas for training using AI via proper prompting, rather than AI training as a separate technological tool. Public school teachers expressed limited confidence in their institutions’ readiness to support AI integration, citing systemic barriers within the K–12 sector. Furthermore, interviews with principals in both resourced and under-resourced schools (n = 4) revealed inequalities in access to technology, with schoolchildren relying on borrowed devices and WhatsApp to follow up on delivered content. This study intersects with 12 AI competencies derived from technology models and adds novel cognitive and non-cognitive competencies that surpass the boundaries of technological and pedagogical frameworks. Findings indicate that teacher AI training needs should be assessed a priori to implement context-tailored AI strategies. Fourteen contextual modifiers, including AI risks, teacher resilience, and adaptive training, emerged as safeguards against systemic barriers hindering the integration of AI into education in conflict zones. Insights for theory, practice, and research are explored.</p>

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AI for educational innovation: opportunities and challenges amidst protracted crises

  • 期刊论文

  • 发表日期：

    2025年12月27日

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  • Maria Bou Zeid,
  • Kamal Abouchedid

摘要

A mixed-methods approach was used to investigate teachers’ perceived opportunities and concerns in Lebanon (n = 264) regarding the integration of Artificial Intelligence (AI) into teaching and learning. The questionnaire was grounded in insights from Focus Group Discussions (FGDs) with teachers (n = 16). Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were employed to develop an AI Teacher Competency Framework. Harman’s single-factor test was used to check for Common Method Bias (CMB). Multiple linear regression indicated no multicollinearity. Teachers highlighted both the benefits and challenges of integrating AI into the classroom. Student learning was central to shaping teachers’ intention to adopt AI, their engagement in training, and AI ethics. Further, the frequency of AI use and prior training significantly influenced teachers’ evaluations of AI’s role in education. Teachers identified teaching methods, assessment, and classroom activities as areas for training using AI via proper prompting, rather than AI training as a separate technological tool. Public school teachers expressed limited confidence in their institutions’ readiness to support AI integration, citing systemic barriers within the K–12 sector. Furthermore, interviews with principals in both resourced and under-resourced schools (n = 4) revealed inequalities in access to technology, with schoolchildren relying on borrowed devices and WhatsApp to follow up on delivered content. This study intersects with 12 AI competencies derived from technology models and adds novel cognitive and non-cognitive competencies that surpass the boundaries of technological and pedagogical frameworks. Findings indicate that teacher AI training needs should be assessed a priori to implement context-tailored AI strategies. Fourteen contextual modifiers, including AI risks, teacher resilience, and adaptive training, emerged as safeguards against systemic barriers hindering the integration of AI into education in conflict zones. Insights for theory, practice, and research are explored.