Home⇛Psychology and Education: A Multidisciplinary Journal⇛vol. 21 no. 4 (2024)

Understanding Predictors of Statistical Competency: Exploring the Role of Attitude, Effort, Anxiety and Learning Approaches

Girlie Villanueva | Geraldine Abella

Discipline: Education

 

Abstract:

Statistical competency, characterized by the ability to analyze and interpret data, is crucial in today's research-driven world. This study investigated factors affecting this competency in college students. Using a correlational design, data were collected from 325 students via surveys using stratified random sampling. Results from ordinal logistic regression revealed that factors like effort, degree program (math-related vs. non-math), delivery type (blended vs. modular), and a deep learning approach positively influence competency. Conversely, a surface learning approach has a negative impact. Attitudes, anxiety, and strategic learning approach were not found to be significant predictors. These findings suggest that various factors contribute to statistical competency, and educational strategies should address these diverse influences.



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