Teaching statistics to psychology students: Two strategies to overcome some limitations
DOI:
https://doi.org/10.52041/iase2023.115Abstract
Psychostatistics is a subject that is taught in the first year of the Psychology degree at the National University of Córdoba. The main difficulties that our students encounter are: understanding the usefulness of statistics in the profession and achieving an appropriation of the concepts and procedures that allow their application in subjects of subsequent courses, such as Psychometric Techniques and Research Methodology. To face these difficulties, two strategies are developed, the first is mandatory and consists of using real data to apply the techniques that are covered throughout the subject. The second is an optional "game", a competition in which problems are presented whose resolution leads to points. In this work we compare the results of the second partial exam between students who participated and did not participate in the optional activity. In order to homogenize the groups, the Propensity Score Matching technique is used.References
Brezavscek, A., Sparl, P., & Znidarsic, A. (2016). Factors influencing the behavioural intention to use statistical software: The perspective of the Slovenian students of social sciences. EURASIA Journal of Mathematics, Science and Technology Education, 13(3), 953–986. https://doi.org/10.12973/eurasia.2017.00652a
Chiesi, F., & Primi, C. (2010). Cognitive and non-cognitive factors related to students' statistics achievement. Statistics Education Research Journal. 9, 6-26. 10.52041/serj.v9i1.385.
Counsell, A., & Cribbie, R. (2020). Student attitudes toward learning statistics with R. Psychology Teaching Review, 26(2), 36–56. https://doi.org/10.31234/osf.io/76w2p
Emmioğlu, E.S.M.A. & Capa-Aydin, Y. (2012). Attitudes and achievement in statistics: A meta- analysis study. Statistics Education Research Journal, 11, 95–102.
Jatnika, R. (2015). The effect of SPSS course to students attitudes toward statistics and achievement in statistics. International Journal of Information and Education Technology, 5(11), 818–821. https://doi.org/10.7763/IJIET.2015.V5.618
Lavidas, K., Barkatsas, T., Manesis, D., & Gialamas, V. (2020). A structural equation model investigating the impact of tertiary students’ attitudes toward statistics, perceived competence at mathematics, and engagement on statistics performance. Statistics Education Research Journal, 19(2), 27–41. https://doi.org/10.52041/serj.v19i2.108
Nasser, F. (2004). Structural model of the effects of cognitive and affective factors on the achievement of Arabic-speaking pre-service teachers in introductory statistics. Journal of Statistics Education, 12(1). [Online: www.amstat.org/publications/ jse/v12n1/nasser.html]
Onwuegbuzie, A.J. (2004). Academic procrastination and statistics anxiety. Assessment & Evaluation in Higher Education, 29, 3–19. doi:10.1080/0260293042000160384
Rosenbaum, P. & Rubin, D. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika 70 (1): 41-55. doi:10.1093/biomet/70.1.41
Schau, C. (2003).Students’ attitudes: The “other” important outcome in statistics education. Presented at 2003 Joint Statistical Meetings - Section on Statistical Education, 2003.
Walker, E. R., & Brakke, K. E. (2017). Undergraduate psychology students’ efficacy and attitudes across introductory and advanced statistics courses. Scholarship of Teaching and Learning in Psychology, 3(2), 132–140. https://doi.org/10.1037/stl0000088