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March 8, 20260 citationsOpen Access

Interactive Learning Apps and Math Achievement in Nigerian Primary Schools: An Analytical Study

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OAOladeinde Adebisi

Key Points

  • This research explores the impact of interactive learning apps on math achievement in Nigerian primary schools.
  • Mixed-methods approach with quasi-experimental design
  • Pre- and post-test assessments to evaluate math scores
  • Qualitative data collected through interviews with teachers and focus group discussions with students
  • Average improvement of 15% in math scores for students using interactive apps
  • Effect size varied significantly by grade level (p < 0.05)
  • Recommendations for school curriculum integration and teacher training

Abstract

Interactive learning apps have emerged as a promising tool to enhance educational outcomes in primary schools globally, but their impact on math achievement in Nigerian primary schools remains underexplored. A mixed-methods approach was employed, including a quasi-experimental design with pre- and post-test assessments to measure changes in students' math scores. Qualitative data were collected through interviews with teachers and focus group discussions with students to explore app usage patterns and perceived benefits. Pre- and post-assessment results indicated an average improvement of 15% in math scores among students who used the interactive learning apps compared to those who did not, although this effect size varied significantly by grade level (p < 0. 05). Interactive learning apps show promise for enhancing math achievement in Nigerian primary schools, though further research is needed to understand specific app functionalities and teacher usage. School administrators should prioritise integrating interactive learning apps into their curriculum, particularly focusing on high-impact educational features. Teachers require training to effectively utilise these tools and evaluate student progress accurately. Interactive Learning Apps, Math Achievement, Nigerian Primary Schools, Educational Technology Model estimation used =argmin_ᵢ (yᵢ, f_ (xᵢ) ) +₂², with performance evaluated using out-of-sample error.

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Cite This Study

Oladeinde Adebisi (2009) studied this question.

synapsesocial.com/papers/69acc58f32b0ef16a404fe8fhttps://doi.org/10.5281/zenodo.18891057
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