Hindrances to undergraduate student’s meaningful learning of bivariate normal distribution at Kenya university
DOI:
https://doi.org/10.30862/jhm.v6i1.353Keywords:
Bivariate Normal Distribution, Difficulties, Hindrances, Kenyan University, Statistics, Undergraduate StudentsAbstract
The problem of the study was to investigate hindrances to undergraduate students’ meaningful learning of bivariate normal distribution (BND) in a Kenyan university. The study was informed by students’ poor performances in BND. This study adopted a case study design and a qualitative research methodology. Data was collected using a questionnaire from second- and third-year undergraduate statistics students (n=175). The data was thematically tabulated and analyzed using descriptive statistics of frequencies and percentages. The study revealed various hindrances to undergraduate students’ learning of BND, which included;- inadequate background knowledge on BND, negative attitude towards BND, lack of interest on BND, inadequate learning resources on BND, inefficiency in learning long and complex statistical equations, inability to comprehend BND function, inability to derive the conditional mean and variance equations of a joint distribution, lack of an in-depth teaching of BND, few worked examples and assignments on BND etc. It is recommended that an in-depth teaching and learning of BND coupled with adequate worked examples and assignments should be embraced by utilizing university’s freely provided internet resources to bridge students’ statistical content knowledge and pedagogical knowledge gaps.ÂReferences
Ben-Zvi, D., & Garfield, J. B. (2004). The challenge of developing statistical literacy, reasoning and thinking (pp. 3-16). Dordrecht, The Netherlands: Kluwer academic publishers. https://doi.org/10.1007/1-4020-2278-6
Bertsekas, D. P., & Tsitsiklis, J. N. (2002). The bivariate normal distribution. Introduction to probability, 1st edition, Athena Scientific, 247-253.
Creswell, J. W. (2003). Research design Qualitative quantitative and mixed methods approach. Research Design Qualitative Quantitative and Mixed Methods Approaches, 3–26. https://doi.org/10.3109/08941939.2012.723954
Delmas, R., & Liu, Y. (2005). Exploring Students’ Conceptions of The Standard Deviation. Statistics Education Research Journal, 4(1), 55–82. https://doi.org/10.52041/serj.v4i1.525
Garfield, J. (1995). How Students Learn Statistics. International Statistical Review / Revue Internationale de Statistique, 63(1), 25. https://doi.org/10.2307/1403775
Glancy, A. W., Moore, T. J., Guzey, S., & Smith, K. A. (2017). Students’ successes and challenges applying data analysis and measurement skills in a fifth-grade integrated STEM unit. Journal of Pre-College Engineering Education Research, 7(1), 68–75. https://doi.org/10.7771/2157-9288.1159
Gordon, S. (2006). The Normal Distribution. Sydney: Mathematics Learning Centre, University of Sydney.
Koparan, T. (2015). Difficulties in learning and teaching statistics: teacher views. International Journal of Mathematical Education in Science and Technology, 46(1), 94–104. https://doi.org/10.1080/0020739X.2014.941425
Lugo-Armenta, J. G., & Pino-Fan, L. R. (2021). Inferential statistical reasoning of math teachers: Experiences in virtual contexts generated by the COVID-19 pandemic. Education Sciences, 11(7). https://doi.org/10.3390/educsci11070363
Mbugua, Z., Kibet, K., Muthaa, G., & Nkonke, G. (2012). Factors Contributing To Students’ Poor Performance in Mathematics at Kenya Certificate of Secondary Education in Kenya: A Case of Baringo County, Kenya. Aijcrnet.Com, 2(6), 87–91. Retrieved from http://aijcrnet.com/journals/Vol_2_No_6_June_2012/11.pdf
McGrath, A. L. (2014). Content, Affective, and Behavioral Challenges to Learning: Students’ Experiences Learning Statistics. International Journal for the Scholarship of Teaching and Learning, 8(2). https://doi.org/10.20429/ijsotl.2014.080206
Nardi, E. (2008). Amongst mathematicians: Teaching and learning mathematics at the university level. (A. P. Koop & P. Wilson, Eds.), Journal of Chemical Information and Modeling (Vol. 3, pp. 1–349). Springer.
Onyancha, B. N., & Ogbonnaya, U. I. (2022). Undergraduate students’ proficiencies in solving bivariate normal distribution problems. Journal of Pedagogical Sociology and Psychology, 4(1), 20-34. https://doi.org/10.33902/JPSP.202212259
Sarwadi, H. R. H., & Shahrill, M. (2014). Understanding Students’ Mathematical Errors and Misconceptions: The Case of Year 11 Repeating Students. Mathematics Education Trends and Research, 2014, 1–10. https://doi.org/10.5899/2014/metr-00051
Shojaie, S. R. H., Aminghafari, M., & Mohammadpour, A. (2012). On the expected absolute value of a bivariate normal distribution. Journal of Statistics Theory and Applications, 11(4), 371-377.
Tishkovskaya, S., & Lancaster, G. A. (2012). Statistical education in the 21st century: A review of challenges, teaching innovations and strategies for reform. Journal of Statistics Education, 20(2). https://doi.org/10.1080/10691898.2012.11889641
Downloads
Published
How to Cite
Issue
Section
License
License and Copyright Agreement
In submitting the manuscript to the journal, the authors certify that:
- They are authorized by their co-authors to enter into these arrangements.
- The work described has not been formally published before, except in the form of an abstract or as part of a published lecture, review, thesis, or overlay journal. Please also carefully read Journal of Honai Math Posting Your Article Policy at http://journalfkipunipa.org/index.php/jhm/about
- That it is not under consideration for publication elsewhere,
- That its publication has been approved by all the author(s) and by the responsible authorities – tacitly or explicitly – of the institutes where the work has been carried out.
- They secure the right to reproduce any material that has already been published or copyrighted elsewhere.
- They agree to the following license and copyright agreement.
Copyright
Authors who publish with Journal of Honai Math agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-NC-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
