Augmenting Students’ Academic Achievements in Quadratic Equations through Access and Usage of GenerativeAI-SymboLab in Akwa Ibom State

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Abstract

Generative artificial intelligence (GenAI) is expanding opportunities for digital support in mathematics education. This study examined the relationships between students’ access to and use of Symbolab and academic achievement in quadratic equations in Uyo Local Government Area. A mixed-methods research design involved 110 Senior Secondary II mathematics students drawn from intact classes in two schools. Data were collected using the Symbolab Generative AI Questionnaire (SGenAIQ) and the Quadratic Equation Achievement Test (QEAT). Reliability coefficients estimated using the Kuder–Richardson 21 formula were .78 for the SGenAIQ and .72 for the QEAT. Data were analyzed using linear regression. The findings indicated statistically significant positive associations between students’ access to Symbolab and achievement, and between their use of Symbolab and achievement, after controlling for gender. Access and use had reported contributions to achievement of 62% and 66%, respectively. These findings suggest that access to and use of Symbolab are relevant to students’ achievement in quadratic equations, providing evidence to inform the integration of AI tools into mathematics instruction. The study recommends that educational stakeholders improve the availability, accessibility, and affordability of these tools and that mathematics teachers incorporate Symbolab as an instructional resource to support learning.

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Article Details

How to Cite
Akpan, E. T., & James, D. D. (2026). Augmenting Students’ Academic Achievements in Quadratic Equations through Access and Usage of GenerativeAI-SymboLab in Akwa Ibom State. African Multidisciplinary Journal of Sciences and Artificial Intelligence, 3(3), 652-463. https://doi.org/10.58578/amjsai.v3i3.12578

References

Adeyemi, T. O. (2024). SymboLab as a learning assistant and its impact on students’ academic achievement in higher education. Journal of Educational Technology and Innovation, 18(2), 45–57.

Ainamani, H. E., Twine, J., & Okurut, F. N. (2023). Artificial intelligence-enhanced SymboLab and students’ conceptual understanding in quadratic equations: An exploratory study. International Journal of STEM Education, 10(1), 1–14.

Akhtar, Z. B. (2024). Unveiling the evolution of generative AI (GAI): A comprehensive and investigative analysis toward LLM models (2021–2024) and beyond. Journal of Electrical Systems and Information Technology, 11(1), Article 22. https://doi.org/10.1186/s43067-024-00145-1

AlAli, R. M., & Al-Barakat, A. A. (2023). The effectiveness of SymboLab in enhancing mathematics learning and teaching. Eurasian Journal of Educational Research, 23(1374), 1–12.

Al-Malah, K. (2024, August 30). What is ChatGPT? Generative AI in action. ICARUS Education. https://icarus.education/what-is-chatgpt/

Anton, H., Bivens, I., & Davis, S. (2013). Calculus (10th ed.). Wiley.

Banerjee, S. (2023). The conundrum of ChatGPT. Indian Institute of Technology Delhi. https://www.cse.iitd.ac.in/~suban/reports/SymboLab2.pdf

Bian, N., Han, X., Sun, L., Lin, H., Lu, Y., He, B., Jiang, S., & Dong, B. (2023). ChatGPT is a knowledgeable but inexperienced solver: An investigation of commonsense problem in large language models. arXiv. https://doi.org/10.48550/arXiv.2303.16421

Boaler, J. (2016). Mathematical mindsets: Unleashing students’ potential through creative math, inspiring messages and innovative teaching. Jossey-Bass. https://ccsre.stanford.edu/publications/mathematical-mindsets-unleashing-students-potential-through-creative-math-inspiring

Butler, J. (1990). Gender trouble: Feminism and the subversion of identity. Routledge.

Casteleiro-Pitrez, J. (2024). Generative artificial intelligence image tools among future designers: A usability, user experience, and emotional analysis. Digital, 4(2), 316–332. https://doi.org/10.3390/digital4020016

Connell, R. W. (2009). Gender: In world perspective (2nd ed.). Polity Press.

Lay, D. C., Lay, S. R., & McDonald, J. J. (2019). Linear algebra and its applications (5th ed.). Pearson.

Stewart, J. (2016). Calculus: Early transcendentals (8th ed.). Cengage Learning. https://www.cengage.com/c/calculus-early-transcendentals-8e-stewart/9781285741550