Level of Knowledge and Skills Proficiency and Attitude of Master of Science in Teaching Mathematics Students in Statistical Data Analysis
DOI:
https://doi.org/10.5281/zenodo.23252563Keywords:
Proficiency, Statistical Data Analysis, Statistical Tools, Attitude, Graduate SchoolAbstract
Although research on statistical data analysis among specialized graduate students remains limited, this study investigated the level of knowledge, skills proficiency, and attitude toward statistical data analysis among graduate students. It aims to provide a foundation to develop an academic program that can enhance the mastery of theoretical knowledge and practical applications of statistics. The study was conducted at Cagayan State University-Aparri by surveying 39 out of 54 randomly sampled graduate students enrolled from 2022 to 2025 using adopted and researcher-made online survey instruments. The study was delimited to the availability and internet access of the respondents. Generally, the study found that students demonstrated basic statistical proficiency in knowledge and skills. Although there was a stronger proficiency in fundamental statistical concepts, students experienced greater difficulty with more advanced statistical tools particularly regression analysis. In terms of attitude, students showed a generally favorable disposition toward statistics in interest, effort, and value, while lower scores in perceived difficulty showed that advanced statistical concepts remained challenging. Also, the correlational analysis revealed that affect, value, and effort were significantly associated with specific aspects of proficiency level. While moderately positive and statistically significant relationship with r = .433 and p = .006 was found between knowledge and skills proficiency, and the overall attitude of students. The results demonstrated that stronger statistical competence may be aligned with a more positive attitude toward the subject. Therefore, the Graduate School may review and strengthen its research and statistics curriculum by incorporating additional learning activities, workshops, and statistical software training that emphasize advanced statistical techniques, particularly regression analysis, which was identified as the weakest area of proficiency among the respondents.
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