Home⇛Psychology and Education: A Multidisciplinary Journal⇛vol. 36 no. 6 (2025)

Experiential Learning and Cognitive Competence of Grade 11 STEM in Statistics and Probability

Ronalyn Legaspi | Susie Daza

Discipline: others in psychology

 

Abstract:

Statistics and probability are essential tools for problem-solving, data analysis, and decision-making in many fields. Students must acquire strong conceptual knowledge and expert procedural skills to ensure mastery of these ideas. This study investigated the effect of experiential learning in enhancing cognitive competence in statistics and probability. It focused on random variables and probability distribution, normal distribution, and estimation of parameters. A quasi-experimental research design was employed. The findings revealed a significant improvement in cognitive competence for both groups. The experimental group, exposed to experiential learning, demonstrated better conceptual understanding and procedural skills than the control group. The experimental group exhibited outstanding comprehension and very satisfactory levels of analysis, outperforming the control group across various metrics. Analysis of covariance revealed that even after controlling for pretest effects, both teaching approaches significantly influenced conceptual understanding and procedural skills. However, the experiential learning approach exhibited a more pronounced effect. In conclusion, this study underscored the effectiveness of experiential learning in fostering cognitive competence in statistics and probability. The findings support the integration of experiential learning methodologies into pedagogical practices, highlighting its potential to enhance students' conceptual understanding and procedural skills in complex mathematical topics.



References:

  1. Barton, T. (2021). Experiential Learning in and out of classrooms - Serve Learn. Serve Learn. https://servelearn.co/blog/experiential-learning-in-and-out-of-classrooms/
  2. Bates, A. (2015). 3.6 Experiential learning: learning by doing (2). Pressbooks. https://opentextbc.ca/teachinginadigitalage/chapter/4-4-models-for-teaching-by-doing/
  3. Boatman, C. (2022, May 25). A simple strategy to encourage student reflection and improvement. Edutopia. https://www.edutopia.org/article/simple-strategy-encourage-student-reflection-and-improvement/
  4. Chimmalee, B., & Anupan, A. (2022, December 13). Enhancement of mathematical conceptual understanding in a cloud Learning environment for undergraduate students. International Journal of Engineering Pedadogy. https://doi.org/10.3991/ijep.v12i6.33775
  5. Choueiry, G. (2021). Pretest-Posttest Control Group Design: An Introduction. https://quantifyinghealth.com/pretest-posttest-control-group-design/
  6. Greenaway, T. P. a. R. (n.d.). Experiential learning articles + critiques of David Kolb’s theory. Tim Pickles, LearningWIRE, TrainingZone: http://www.trainingzone.co.uk and Roger Greenaway, Reviewing Skills Training https://reviewing.co.uk/research/experiential.learning.htm
  7. Hatcher, J. (n.d.). Bringing the gap between service and learning. DigitalCommons@UNO. https://digitalcommons.unomaha.edu
  8. Hurrell, D. P. (2021). Conceptual knowledge or procedural knowledge or conceptual knowledge and procedural knowledge:why the conjunction is important forteachers. Research Online. https://ro.ecu.edu.au/ajte/vol46/iss2/4/
  9. Lani, J. (2021, August 11). Analysis of covariance (ANCOVA). Statistics Solutions. https://www.statisticssolutions.com/analysis-of-covariance-ancova/
  10. Li, Y., & Schoenfeld, A. H. (2019). Problematizing teaching and learning mathematics as “given” in STEM education. International Journal of STEM Education. https://doi.org/10.1186/s40594-019-0197-9
  11. Manolis, C., Burns, D. J., Assudani, R., & Chinta, R. (2013) Assessing experiential learning styles: A methodological reconstruction and validation of the Kolb Learning Style Inventory. Learning and Individual Differences. https://doi.org/10.1016/j.lindif.2012.10.009
  12. Mcleod, S. (2023, June 15). Constructivism learning theory & philosophy of education. Simply Psychology.  https://www.simplypsychology.org/constructivism.html
  13. Koskinen, R., & Pitkäniemi, H. (2022). Meaningful learning in mathematics: A research synthesis of teaching approaches. International Electronic Journal of Mathematics Education. https://doi.org/10.29333/iejme/11715
  14. Oliveira Júnior, A. P. de; Zamora, P. R.; Azevedo de Oliveira, L.; & Costa de Souza, T. (2018). Student´s attitudes towards probability and statistics and academic achievement on higher education. Acta Didactica Napocensia, 11(2), 43-56, DOI: 10.24193/adn.11.2.4.
  15. Saunders, L. (2020). Active learning: engaging people in the learning process. pressbooks. https://iopn.library.illinois.edu/pressbooks/instructioninlibraries/chapter/active-learning-engaging-people-in-the-learning-process/
  16. Scager, K., Boonstra, J., Peeters, T., Vulperhorst, J. P., & Wiegant, F. A. C. (2016). Collaborative learning in higher education: evoking positive interdependence. CBE Life Sciences Education.      https://doi.org/10.1187/cbe.16-07-0219
  17. Taylor, S. (2023). Random sampling. corporate finance institute. https://corporatefinanceinstitute.com/resources/data-science/random-sampling/
  18. Uyen, B. P., Tong, D. H., & Lien, N. B. (2022). The effectiveness of experiential learning in teaching arithmetic and geometry in sixth grade. Frontiers in Education; Frontiers Media. https://doi.org/10.3389/feduc.2022.858631
  19. Yusop, S. R. M., Rasul, M. S., Yasin, R. M., & Hashim, H. U. (2023). Identifying and validating vocational skills domains and indicators in classroom assessment practices in TVET. Sustainability; Multidisciplinary Digital Publishing Institute. https://doi.org/10.3390/su15065195

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