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This is a Quasi-Experimental study.

October 2, 2025

Effectiveness of Technology-Enhanced Simulations in Teaching Mathematical Concepts in Ecology and Human Physiology

MYMuhammad YusufAhmadu Bello University ZAZaharaddeen AliyuAhmadu Bello University ADA. DedeYobe State University

Key Points

Students using virtual simulations outperformed traditional methods, enhancing their grasp of mathematical models in biology.
With Cohen’s d effect sizes of 1.35 and 1.49, the experimental group showed considerable improvement in ecology and physiology.
The instructional method included AI-supported simulations, focusing on cognitive engagement and lowering cognitive load.
This study underscores the need for teacher training and infrastructural support to effectively implement simulation-based learning.

Abstract

This study examined how well technology-enhanced simulations taught mathematical models in secondary school biology classes that focused on ecology and human physiology. The study examined how virtual simulations can help close the pedagogical gap between abstract mathematical concepts and intricate biological systems. It was based on the Technological Pedagogical Content Knowledge (TPACK) framework, Constructivist Learning Theory, and Cognitive Load Theory. 300 Senior Secondary School Two (SS2) students from six purposefully chosen public schools participated in a quasi-experimental design with a pretest-posttest control group. While the control group was instructed using traditional teacher-led techniques, the experimental group was instructed using AI-supported virtual simulations. Data gathered using the Student Engagement and Comprehension Questionnaire and the Biology-Mathematical Modeling Achievement Test (BMMAT) and the Student Engagement and Comprehension Questionnaire (SECQ) were examined using descriptive and inferential statistics, such as ANCOVA and effect size calculations. The results showed that students in the experimental group performed significantly better than those in the control group in terms of understanding and applying mathematical models in biology, with large effect sizes (Cohen’s d = 1.35 for ecology; 1.49 for physiology) and strong explained variances (Partial Eta² = 0.172 and 0.195). The study also confirmed that simulation-based instruction improves cognitive engagement, lowers unnecessary cognitive load, and supports experiential and collaborative learning. These results are consistent with current research that supports the use of virtual simulations in STEM education to promote interdisciplinary competencies and scientific reasoning, and the study concluded that virtual simulations are transformative pedagogical tools that can increase student engagement and conceptual understanding in biology through dynamic and interactive modeling experiences. It recommends curriculum reforms, teacher professional development, infrastructural investment, AI-driven personalization, and interdisciplinary collaboration to optimize the use of virtual simulations in science education.

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