Secondary School Teachers’ Perceptions and Use of Generative AI in Bangladesh

Abstract

Currently, the use of generative artificial intelligence (GenAI) by Bangladeshi secondary school teachers remains undocumented, informal, and uneven. This study researched the secondary school teacher’s perceptions and use of GenAI in Bangladesh, which adopted an explanatory sequential mixed-method design. Quantitatively, it surveyed 207 secondary school teachers, which informed semi-structured interviews with 20 purposively sampled educators. Quantitative data were analyzed using descriptive statistics, Spearman correlation, ordinal logistic regression, and mediation analysis, and thematic analysis was utilized for the qualitative data. The study was guided by two theoretical frameworks: the Technology Acceptance Model (TAM) and the Technological Pedagogical Content Knowledge (TPACK) framework. The quantitative findings revealed that teachers viewed GenAI as useful and easy to use, but these perceptions did not significantly predict their actual use of GenAI. Instead, teacher’s attitude towards using GenAI were the strongest predictor, influencing whether they use it. School type significantly predicted GenAI usage, with teachers in non-government, private, and semi-government schools using GenAI more than those in public schools. The qualitative findings also disclosed six main themes: balancing efficiency and dependency, changes in student’s learning, lack of institutional and policy support, teacher’s resilience, the importance of teacher’s roles, and ethical concerns due to the absence of clear policies. The study contributes to refining the Technology Acceptance Model and provides practical recommendations for policymakers and educational leaders to support equitable, ethical, and effective use of GenAI in Bangladeshi secondary education.