Document Type



Doctor of Philosophy (PhD)


Curriculum and Instruction

First Advisor's Name

Maria L. Fernandez

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Leonard Bliss

Second Advisor's Committee Title

Committee Member

Third Advisor's Name

Barbara King

Third Advisor's Committee Title

Committee Member

Fourth Advisor's Name

B.M Golam Kibria

Fourth Advisor's Committee Title

Committee Member


Statistics Education, Simulations, Bootstraps, Randomization Test, Hispanic Students

Date of Defense



This study analyzed the effects of a randomization-based inference teaching methodology on students’ content mastery in an introductory statistics college course. The sample was 125 undergraduate students from Miami Dade College, a large Hispanic Serving Institution in the Southeast. A pretest-posttest nonequivalent group design was used for the study. Students in the randomization-based teaching modality received exposure to simulation activities, specifically bootstrap confidence intervals and randomization test, that aim to enhance conceptual understanding of inferential statistics, an important component of statistical literacy. The instructional strategy was designed to trigger critical reflection that confronted students with their thinking and lead them through a process of reorganization, restructure, and improvement of their concepts. The 40 item Comprehensive Assessment of Outcomes in a first Statistics course (CAOS) instrument was used to measure students’ conceptual understanding of important statistical ideas along with a demographic and academic survey that collected data on student characteristics.

A stepwise linear regression method was used to look at the effects of group membership while controlling for Pre-CAOS scores, age, gender, first generation, prior experience with statistics, student status (part/full time), native speaker, STEM or not-STEM major, Hispanic, highest math course taken in high school, and GPA. The full model showed that only Group and Pre-CAOS score were the only significant predictors of Post CAOS scores. None of the other variables were significant. The model was a significant predictor of Post CAOS score, F(2, 121) = 16.96, p

The results supported the claim that the randomization-based teaching modality for inferential statistics help Hispanic students to achieve a better understanding of the learning outcomes associated with an undergraduate introductory statistics course.





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