AI-enhanced pedagogical practices and mathematical language proficiency in STEM education
DOI:
https://doi.org/10.32674/6h0e3376Keywords:
AI-enhanced pedagogical practices, digital literacy, learning engagement, mathematical language proficiency, STEM education, structural equation modeling, SEM, AEPPAbstract
This study investigates the effectiveness of AI-enhanced pedagogical practices on improving the mathematical language proficiency of senior high school students in Ghana. The current research adopted a quantitative cross-sectional design, where the structural equation modeling approach was used on a sample size of 360 participants, to investigate digital literacy and learning engagement as partial mediators. As expected, results from this study show that AEPP, DL, and LE are statistically significant positive predictors of students’ MLP. Additionally, digital literacy and learning engagement play a mediating role in the relationship between the AI-supported instruction and the proficiency outcomes. The findings highlighted the importance of integrating adaptive AI tools to enhance the digital literacy of the students as well as their learning engagement to improve the mathematical communication and reasoning of the senior high school students.
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