This study explores the perceptions of pre-service English as a Foreign Language (EFL) teachers in Türkiye regarding the integration of generative artificial intelligence (GenAI) into English language teacher education. Employing a quantitative research design, data were collected from 150 pre-service teachers (PSTs) to examine their awareness of AI technologies, perceived impacts on language learning, and acceptance of AI as a pedagogical tool. The findings provide a nuanced understanding of how pre-service teachers engage with AI in educational contexts and emphasise the need for thoughtful pedagogical integration of GenAI tools in teacher education programs. The study highlights the importance of structured, reflective initial teacher education that addresses both the technological affordances and ethical implications of AI use in the classroom. The study also underlines the gender equity in AI adoption, reinforcing that both male and female PSTs share similar levels of engagement with AI technologies. Additionally, results indicate gender parity in AI engagement, suggesting equitable adoption across male and female participants. This research contributes to the growing body of literature advocating for inclusive and responsible technology integration in education.
Background: The COVID-19 pandemic led to unprecedented school closures, affecting over one billion students worldwide and raising concerns about long-term educational consequences. While national studies indicate substantial learning losses, evidence from international assessments provides a unique opportunity to capture global patterns and inequalities. Aims: This study examines the magnitude and distribution of pandemic-related learning losses in mathematics and science. We investigate whether achievement in 2023 deviated from pre-pandemic trends, how learning losses relate to the duration of school closures, and whether effects vary by gender, home language, and prior achievement. Sample: Data are drawn from all Trends in International Mathematics and Science Study (TIMSS) cycles between 1999 and 2023, covering more than 2 million students from 84 education systems at Grades 4 and 8. Methods: We estimate deviations from long-term national achievement trends using mixed-effects regressions with country fixed effects and student background controls. Interaction terms capture heterogeneity by school closure duration, gender, home language, and proficiency level. Quantile regressions assess impacts across the achievement distribution. Results: Average achievement in 2023 was 0.11 SD below expected trends, with larger losses in countries that experienced longer closures. Grade 8 students were more affected than Grade 4 students. Girls and students from language minority backgrounds experienced disproportionately greater losses. Low achievers suffered the most, losing up to 0.23 SD, while top performers were largely unaffected. Conclusions: The findings highlight a persistent global learning crisis with widening inequalities. Targeted interventions are urgently needed to support disadvantaged groups and mitigate long-term consequences of pandemic-related disruptions.
I examine the relationship between students' computer and information literacy (CIL) and their performance in ow- and high-stakes assessments in Chile. Information and communication technologies have become increasingly prevalent in the Chilean education system over the past few decades, suggesting that CIL may now be essential for educational success. My study examines how CIL in Grade 8 associates with student performance in teacher assessments and standardized tests in subsequent school years. I create a unique student-level database by linking data from various student assessments at different time points to the set of Grade 8 students who participated in the International Computer and Information Study in 2013. Using within-student variation in outcomes over time, I find a positive association between CIL and their performance in national reading and math standardized assessments. However, I find little to no evidence that CIL is associated with student performance in teacher-based assessments.
