Systematic Error Analysis in Technology-Enhanced Calculus: Comparing Maple and GeoGebra Approaches in Pre-Service Teacher Education in Ghana

Authors

  • Collins Fordjour Nkrumah Department of Mathematics and Information Technology, Wesley College of Education, Kumasi Author
  • Francis Kwadwo Awuah Department of Teacher Education, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana Author
  • Bright Emmanuel Owusu Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana Author
  • Prince Edem Dzakpasu Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana Author
  • Enyonam Mansah Attimu-Eshun Department of Mathematics and Information Technology, Wesley College of Education, Kumasi Author
  • William Obeng-Denteh Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana Author

Keywords:

GeoGebra, Maple, Pólya, Technology-Enhanced, Calculus

Abstract

The study focused on errors committed by 120 Ghanaian Pre-service teachers learning the volumes of solids of revolution (VOSR) through the lecture method or technology-enhanced instruction (TEI) using Maple and GeoGebra. A quasi-experimental pretest–posttest nonequivalent groups design was used. The errors were categorised according to Pólya's four problem-solving stages: understanding, planning, carrying out, and verification. The errors at pretest were dominated by those in verification (77.5%) and carrying out (70.0%), with no difference between the groups. Errors at pretest were dominated by those of verification (77.5%) and carrying out (70.0%), with no differences between groups. Technology group error reduction was significantly higher than that of the lecture instruction group after 8 weeks. Mean errors decreased by 78.3% for Maple (M pretest = 115, M posttest = 25) and 76.9% for GeoGebra (M pretest = 104, M posttest = 24), compared to 41.2% for lecture (M pretest = 114, M posttest = 67). Concept errors were reduced the most by Maple (88.0%), and procedural errors by GeoGebra (84.0%). For both, the number of calculation errors decreased (GeoGebra: 8.3%; Maple: 5.0%). The highest percentage of spatial reasoning errors was found in the group using GeoGebra (25.0%), and the verification errors were high across all groups, with significant differences between the lecture and the technology groups according to χ² analysis (χ²(3, N = 116) = 15.23, p = .002, V = .58) but not between Maple and GeoGebra.

References

Abroampa, W. K., Amadiok, D., Nyatsikor, M. K., & Dzakpasu, P. E. (2025). How are basic school teachers in Ghana improvising ICT integration? Implications for the implementation of the standard-based curriculum. Journal of Teacher Education and Educators, 14(2), 119–138.

Akyeampong, K., Lussier, K., Pryor, J., & Westbrook, J. (2013). Improving teaching and learning of basic mathematics and reading in Africa: A review of policy and practice. Department for International Development.

Anamuah-Mensah, J., Mereku, D. K., & Ghartey-Ampiah, J. (2008). Ghanaian junior secondary school students' achievement in mathematics and science. Ministry of Education.

Anthony, G., & Agyemang, S. (2020). Mathematics anxiety and error rates in Ghanaian preservice teacher education. African Journal of Teacher Education, 9(1), 45–63.

Artigue, M. (2002). Learning mathematics in a CAS environment: The genesis of a reflection about instrumentation and the dialectics between technical and conceptual work. International Journal of Computers for Mathematical Learning, 7(3), 245–274.

Armah, R. B., Cofie, P. O., & Assuah, C. K. (2018). Analysis of students' errors in solving linear equations: The case of Ghanaian senior high school students. African Journal of Educational Studies in Mathematics and Sciences, 14, 49–62.

Ball, D. L., Thames, M. H., & Phelps, G. (2008). Content knowledge for teaching: What makes it special? Journal of Teacher Education, 59(5), 389–407.

Benecke, S., & Kaiser, G. (2023). Error analysis in mathematics education: A systematic review. ZDM–Mathematics Education, 55(2), 311–327.

Burkhard, P., Katja, E., Andreas, F., Niels, P., Rösken-Winter, B., Rüdiger, T., & Belzen, U.Z.A.(2019). A framework to foster problem-solving in STEM and computing education. Research in Science & Technological Education, Volume 38, 2020 - Issue 1. https://doi.org/10.1080/02635143.2019.1600490.

Bray, W. S. (2011). A collective case study of the influence of teachers' beliefs and knowledge on error-handling practice during class discussion of mathematics. Journal for Research in Mathematics Education, 42(1), 2–8.

Caligaris, M. G., Schivo, M. E., & Romiti, M. R. (2015). Calculus & GeoGebra, an interesting partnership. Procedia Social and Behavioural Sciences, 174, 1183–1188. https://doi.org/10.1016/j.sbspro.2015.01.735

Carlson, M. P., & Bloom, I. (2005). The cyclic nature of problem solving: An emergent multidimensional problem solving framework. Educational Studies in Mathematics, 58(1), 45–75. https://doi.org/10.1007/s10649-005-0808-x

Drijvers, P., Doorman, M., Boon, P., Reed, H., & Gravemeijer, K. (2010). The teacher and the tool: Instrumental orchestrations in the technology-rich mathematics classroom. Educational Studies in Mathematics, 75(2), 213–234.

Etsey, Y. K., Amedahe, F. K., & Edjah, H. (2005). Do part-time and full-time students differ in their academic performance in undergraduate courses? Journal of Institutional Research, 76. Fikru G., Chernet, T. D., Adula, B. H. (2024). Effects of GeoGebra-assisted instructional methods on students’ conceptual understanding of geometry.DOI:10.1080/2331186X.2024.2379745.

Grundmeier, T. A., Hansen, J., & Sousa, E. (2006). An exploration of definition and procedural fluency in integral calculus. Problems, Resources, and Issues in Mathematics Undergraduate Studies, 16(2), 178–191.

Hanaysha, J.R., Bassam, S.F., & In'airat, M. (2023). Impact of classroom environment, teacher competency, information and communication technology resources, and university facilities on student engagement and academic performance. https://doi.org/10.1016/j.jjimei.2023.100188.

Heid, M. K., & Blume, G. W. (2008). Algebra and function development. In M. K. Heid & G. W. Blume (Eds.), Research on technology and the teaching and learning of mathematics: Vol. 1. Research syntheses pp. 55–108. Information Age Publishing.

Hohenwarter, M., & Fuchs, K. (2004). A combination of dynamic geometry, algebra, and calculus in the software system GeoGebra. In Proceedings of the Computer Algebra Systems and Dynamic Geometry Systems in Mathematics Teaching Conference. University of Pécs.

Hohenwarter, M., & Jones, K. (2007). Ways of linking geometry and algebra: The case of GeoGebra. Proceedings of the British Society for Research into Learning Mathematics, 27(3), 126–131.

Kendal, M., & Stacey, K. (2001). The impact of teacher privileging on learning differentiation with technology. International Journal of Computers for Mathematical Learning, 6(2), 143–165.

Kwarteng, E. F., Acheampong, E., & Asante, M. (2022). Pre-service teachers' preparedness for error analysis in mathematics classrooms: Evidence from Ghanaian colleges of education. Journal of Mathematics Teacher Education, 25(3), 289

Lagrange, J. B., Artigue, M., Laborde, C., & Trouche, L. (2011). Technology and mathematics education: A multidimensional study of the evolution of research and innovation. In Second international handbook of mathematics education, pp. 237-269. Dordrecht: Springer Netherlands. Springer. Lavicza, Z. (2021). Integrating technology into mathematics teaching at the university level. The International Journal of Mathematics Education 42(1):105-119. DOI:10.1007/s11858-009-0225-1

Lester, F. K. (2013). Thoughts about research on mathematical problem-solving instruction. The Mathematics Enthusiast, 10(1–2), 245–278.

Luneta, K. (2015). Understanding students' misconceptions: An analysis of the final Grade 12 examination questions in geometry. Pythagoras, 36(1)

Machisi, E. (2021). Grade 11 students' reflections on their Euclidean geometry learning experiences. EURASIA Journal of Mathematics, Science and Technology Education, 17(2)

Martin, T. (2000). Calculus students' ability to solve geometric related-rates problems. Mathematics Education Research Journal, 12(2), 74–91.

Mereku, D. K. (2010). Mathematics curriculum implementation in Ghana. Mathematics Connection, 11.

Mereku, D. K., & Aduofour, K. A. (2005). Students' errors and misconceptions in senior secondary school mathematics. Mathematics Connection, 5(1), 33–43.

Ngcobo, A.Z. (2026). In-service and pre-service teachers’ perspectives on error analysis as an instructional approach to enhance mathematics teaching. education science. https://doi.org/10.33390/edcsci16020349. Nguyen, T. (2015). The effectiveness of online learning: beyond no significant difference and future horizons. MERLOT Journal of Online Learning and Teaching, 11, 309-319.

Peng, A., & Luo, Z. (2009). A framework for examining mathematics teacher knowledge as used in error analysis. For the Learning of Mathematics, 29(1), 22–25.

Rasmussen, C., Marrongelle, K., & Borba, M. C. (2014). Research on calculus: What do we know and where do we need to go? ZDM, 46(4), 507–515.

Riccomini, P. J. (2005). Identification and remediation of systematic error patterns in subtraction. Learning Disability Quarterly, 28(3), 233–242.

Ryan, J., & Williams, J. (2007). Children's mathematics 4–15: Learning from errors and misconceptions. Open University Press.

Sealey, V. (2014). A framework for characterizing student understanding of Riemann sums and definite integrals. The Journal of Mathematical Behavior, 33, 230–245.

Schoenfeld, A. H. (2006). Learning to think mathematically: Problem solving, metacognition, and sense making in mathematics.

Shadaan, P., & Leong, K. E. (2013). Effectiveness of using GeoGebra on students' understanding in learning circles. Malaysian Online Journal of Educational Technology, 1(4), 1–11.

Shimizu, Y., & Kang, S. (2025). International perspectives on student errors in mathematics education. Journal for Research in Mathematics Education, 56(1), 1–18.

Stewart, J. (2016). Calculus: Early transcendentals (8th ed.). Cengage Learning.

Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive load theory. Springer.

Tall, D. (2013). How humans learn to think mathematically: Exploring the three worlds of mathematics. Cambridge University Press.

Thompson, P. W. (2013). In the absence of meaning. In K. Leatham (Ed.), Vital directions for mathematics education research, pp. 57–93. Springer.

Villavicencio, F. T. (2023). Errors and misconceptions in calculus among senior high school students. International Journal of Research in Education and Science, 9(1), 123–140.

Wilmot, E. M., Ash Xiun, M., & Abiam, P. (2011). Errors in solving word problems in mathematics among senior high school students. African Journal of Education and Technology, 1(1), 11–19.

Ghana Tertiary Education Commission (2019). National teachers' standards for Ghana. Ghana Tertiary Education Commission.

Von Korff, J., & Rebello, N. S. (2012). Teaching integration with layers and representations: A case study. Physical Review Special Topics–Physics Education Research, 8(1), 010125.

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Published

2026-06-30