Score analysis for health area student's of an active teaching methodology for hypothesis testing content

Authors

DOI:

https://doi.org/10.5902/2179460X40424

Keywords:

Statistics Teaching, Test Analysis, Active Teaching Methodology

Abstract

An analysis of the performance of the hypothesis testing content for the population average of health students who participated in the active teaching methodology called Problem Based Learning adapted to the teaching context and supported by the Conceptual Fields Theory is presented. This performance was compared with that of students who took traditional classes through an instrument created for this purpose that sought to replicate typical questions of this content. The instrument was applied to 99 students from a higher education institution in southern Brazil, by the Moodle environment, in person and using Excel and Bioestat software. Scores were analyzed by Exploratory Data Analysis, the Classical Test Theory and Hypothesis Tests and were higher for students who did not participate in the PBL, but the differences were not significant at α = 5%. Possible causes are the better adaptation of the instrument to the traditional education system, contextual limitations to the application of the active methodology such as low workload and resistance to new methodologies. It is concluded that the difference in scores is not large enough to discourage the effort to adapt active methodologies to biostatistics, given its advantages other than yield.

Downloads

Download data is not yet available.

Author Biographies

Rodrigo Fioravanti Pereira, Universidade Franciscana

Aluno do curso de doutorado em Ensino de Ciências da UBU

Aluno do curso de graduação em Estatística da UFSM

Professor de Matemática da UFN

Fernando de Jesus Moreira Junior, Universidade Federal de Santa Maria

Professor do Departamento de Estatística

Ileana Maria Greca, Universidad de Burgos

Professora na Universidad de Burgos | UBU · Departamento de Didácticas Específicas

Jesus Meneses Villagra, Universidad de Burgos

Professor na Universidad de Burgos | UBU · Departamento de Didácticas Específicas

References

AMRHEIN, V.; GREENLAND, S.; MCSHANE, B. Scientists rise up against statistical significance. Nature, v. 567, n. 7748, p. 305–307, 20 mar. 2019.

BATANERO, C.; ESTEPA, A.; GODINO, J. D. Análisis Exploratorio de Datos: Sus Posibilidades en la Enseñanza Secundaria. Suma, v. 9, p. 25–31, 1991.

BEHRENS, J. T. Principles and Procedures of Exploratory Data Analysis. Psychological Methods, v. 2, n. 2, p. 131–160, 1997.

BORGATTO, A. F.; ANDRADE, D. F. DE. Análise clássica de testes com diferentes graus de dificuldade. Estudos em Avaliação Educacional, v. 23, n. 52, p. 146, 30 ago. 2012.

COHEN, H. W. P Values: Use and Misuse in Medical Literature. American Journal of Hypertension, v. 24, n. 1, p. 18–23, 1 jan. 2011.

CRONBACH, L. J. Coefficient Alpha And The Internal Structure Of Tests. PSYCHOMETRIKA, v. 16, n. 3, p. 297–334, 1951.

ESTATCAMP. Estimação não paramétrica de densidades: método do núcleo - Análise de Capacidade. Disponível em: http://www.portalaction.com.br/analise-de-capacidade/431-estimacao-nao-parametrica-de-densidades-metodo-do-nucleo. Acesso em: 25 set. 2019.

GIL, A. C. Como Elaborar Projetos de Pesquisa/Antonio Carlos Gil. 3a ed. São Paulo: Atlas, 2002.

MAROCO, J.; GARCIA-MARQUES, T. Qual a fiabilidade do alfa de Cronbach? Questões antigas e soluções modernas? Laboratório de Psicologia, v. 4, n. 1, p. 65–90, 2006.

MOREIRA, M. A. A Teoria dos Campos Conceituais de Vergnaud, O Ensino de Ciências e a Pesquisa nesta Área. Investigações em Ensino de Ciências, n. 1, p. 7–29, 2002.

ORANGE DATA MINING. Distributions. Disponível em: https://docs.biolab.si//3/visual-programming/widgets/visualize/distributions.html. Acesso em: 26 set. 2019.

PANAGIOTAKOS, D. B. Value of p-value in biomedical research. The open cardiovascular medicine journal, v. 2, p. 97–9, 2008.

PEREIRA, R. F.; GRECA, I. M..; VILLAGRA, J. A. M. Caminhos do ensino de estatística para a área da saúde. Revista Latinoamericana de Investigación en Matemática Educativa, v. 22, n. 1, p. 67–96, 31 mar. 2019.

POST, W. J.; VAN DUIJN, M. A. J. Teaching Hypothesis Testing: a Necessary Challenge. The 9th International Conference on Teaching Statistics. 2014.

SOARES, J. A. R.; AMORIM, A. F.; SILVA, C. R. DA. Avaliação Educacional em Larga Escala e Algumas Considerações Sobre a TCT e a TRI. Revista Ciências Exatas e Naturais, v. 20, n. 1, p. 119–125, 2018.

TUKEY, J. W. Exploratory Data Analysis. [s.l.] Addison-Wesley, 1977.

WASSERSTEIN, R. L.; LAZAR, N. A. The ASA’s Statement on p-Values: Context, Process, and Purpose. The American Statistician, 2016.

Published

2020-12-29

How to Cite

Pereira, R. F., Moreira Junior, F. de J., Greca, I. M., & Villagra, J. M. (2020). Score analysis for health area student’s of an active teaching methodology for hypothesis testing content. Ciência E Natura, 42, e50. https://doi.org/10.5902/2179460X40424

Most read articles by the same author(s)

<< < 1 2 3 > >>