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Statistical Analysis of the Degree of Arabic Language Teachers’ AI Integration of Artificial Intelligence Application in Teaching Language Skills |
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PP: 1459-1479 |
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doi:10.18576/jsap/150601
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Author(s) |
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Shaman Saleh Marie Maabreh,
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Abstract |
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| This study investigated the extent to which Arabic language teachers employ artificial intelligence (AI) applications to teach Arabic language skills to their students in Jordan. Employing a descriptive-analytical research design, the study sampled 135 male and female Arabic language teachers (N = 135), recruited through a convenience sampling procedure from public and private schools affiliated with the Third Irbid Directorate of Education. Self-reported data were collected using a 26-item questionnaire structured across four primary skill domains: Listening, Speaking, Reading, and Writing. Statistical analyses included descriptive metrics (means, standard deviations, and 95% confidence intervals) and inferential tests, specifically a main-effects four-factor analysis of variance (ANOVA) with effect sizes, post hoc comparisons, and a sensitivity power analysis. The results indicated an overall moderate level of self-reported AI integration across all language domains (mean [M] = 3.25, standard deviation [SD] = 0.64). Among the individual domains, Reading ranked highest, followed by Writing, Speaking, and Listening, with each domain yielding a moderate evaluation. Inferential results revealed no statistically significant differences in AI integration attributable to gender or years of experience. However, statistically significant differences were observed for school type, favoring private schools over public schools, and for educational qualification, favoring postgraduate degree holders over Bachelor’s degree holders; these effects were small to medium (partial η2 = .058 and .066, respectively) and, given the unbalanced subgroups (22 private vs. 113 public school teachers) and the convenience sample, should be interpreted cautiously. The findings reflect teachers’ self-reported practices rather than observed classroom behavior. Based on these findings, it is recommended that educational policymakers establish systematic, institutionally supported professional development programs—particularly targeting public school educators and prioritizing oral language skills—to transition AI integration from ad hoc teacher usage toward structured, scalable pedagogical practices, supported by audio infrastructure and vetted Arabic-compatible tools. |
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