Original Research

The effect of graphing calculator use on learners’ achievement and strategies in quadratic inequality problem solving

Levi Ndlovu, Mdutshekelwa Ndlovu
Pythagoras | Vol 41, No 1 | a552 | DOI: https://doi.org/10.4102/pythagoras.v41i1.552 | © 2020 Levi Ndlovu, Mdutshekelwa Ndlovu | This work is licensed under CC Attribution 4.0
Submitted: 30 April 2020 | Published: 18 November 2020

About the author(s)

Levi Ndlovu, Stellenbosch University Centre for Pedagogy, Department of Curriculum Studies, Faculty of Education, Stellenbosch University, Cape Town, South Africa
Mdutshekelwa Ndlovu, Department of Science and Technology Education, Faculty of Education, University of Johannesburg, Johannesburg, South Africa

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The purpose of this mixed methods study was to investigate the effect of a graphing calculator (GC) intervention on Grade 11 learners’ achievement in quadratic inequality problem solving. The quantitative aspects of the study involved an experimental and control group design in which the experimental group received instruction using the GC activities and the control group was taught without using the GC. The qualitative aspects of the study involved script analysis and task-based interviews. We used three data collection instruments: a quadratic inequality problem solving test used both as a pre- and a post-test administered to both the experimental and the control group learners, a written task analysis protocol and a task-based interview schedule. The results of the dependent samples t-test confirmed a statistically significant improvement in the quadratic inequality problem solving achievement of the experimental group with a Cohen’s d effect size of 1.3. The dependent t-test results for the control group were also a statistically significant improvement but with a smaller Cohen’s d of 1.2. The results of the independent t-test indicated that the experimental group achievement was significantly higher than that of the control group with a Cohen’s d effect size of 0.79. Script analysis of selected learners’ post-test solutions also showed that learners in the experimental group employed more problem-solving strategies (at least three – symbolic, numeric and graphical). Interview results of purposively selected learners also affirmed that experimental group participants perceived the GC intervention to have prepared them more effectively for multiple solution strategies of the quadratic inequality problem tasks. The researchers recommend the integration of GCs in the teaching and learning of mathematics in general and quadratic inequalities in particular. However, more research is needed in the integration of the GC in high-stakes assessment.


Quadratic inequality problems; problem-solving strategies; graphing calculator; realistic mathematics learning; learner achievement and strategies


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