Statistical Tools of Pedagogical Research
DOI:
https://doi.org/10.28925/2311-2409.2024.428Keywords:
задачі математичної статистики, е-ресурси длятистична гіпотеза, статистична статистичного аналізу, критерії узгодження, методи математичної статистики, стаAbstract
Due to the active development of scientific and technological progress, mathematical science has impacted
on all scientific fields, including pedagogy. A crucial element is enhancing the quality of pedagogical research
through the organization of experiments, the evaluation of acquired scientific data, and the validation of these
results employing methods of mathematical statistics. The complexities involved in the proper implementation
of statistical methods in pedagogical research arise from the necessity to investigate qualitative attributes
of phenomena and events, requiring the alignment of research objectives and content with the appropriate
mathematical and statistical techniques. Statistics seeks to provide relevant evidence to the claims of experts
in various fields using mathematical methods to reach a consensus on making appropriate decisions based
on statistical information.
The article theoretically highlights mathematical and statistical methods in pedagogical research when
organizing an experiment, evaluating acquired scientific data and verifying the reliability of these results usingmethods of mathematical statistics. It defines the main concepts of the research, namely: mathematical statistics,
problems of mathematical statistics, methods of mathematical statistics, statistical literacy, statistical hypothesis,
criteria of agreement, e-resources for statistical analysis.
The main mathematical methods used in pedagogical research have been selected, and the algorithm for testing
statistical hypotheses in pedagogical research has been provided. The statistical criteria of agreement have been
identified for testing the hypothesis about the type of distribution of a random variable (Pearson, Fisher, Student),
and modern e-resources for calculating the criteria of agreement (JASP, PSPP, DataMelt, Sisense and others),
as well as some online calculators, have been discussed
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Gonda, D., Pavlovičová, G, Ďuris, V, & Tirpáková, A. (2022). Implementation of Pedagogical
Research into Statistical Courses to Develop Students’ Statistical Literacy. Mathematics 2022, 10 (11), 1793
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https://doi.org/10.3390/math10111793
Jonathon Love, Ravi Selker, Maarten Marsman, et al (2019). JASP: Graphical Statistical Software
for Common Statistical Designs. Journal of Statistical Software, January 2019, 88(2), DOI:10.18637/jss.
v088.i02 [in English]
Pierce, R., Chick, H., Watson, J., Les M., & Dalton, M. (2014). A Statistical Literacy Hierarchy
for Interpreting Educational System Data. Aust. J. Educ. 2014, 58, 195–217 [in English].
Wagenmakers, E., Love, J., Marsman, M., Jamil, T., Ly, A., Verhagen, J., et al (2018). Bayesian inference
for psychology. Part II: Example applications with JASP». Psychonomic Bulletin & Review, 25 (1): 58–76
[in English].
doi:10.3758/s13423-017-1323-7 PMC 5862926. PMID 28685272
Watson, J. (1997). Assessing Statistical Literacy through the Use of Media Surveys. In The Msessment
Chullenge in Statistics Education; Gal, I., Garfield, J., Eds.; International Statistical Institutel IOS Press:
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