Self-directed learning and teaching of Statistics to improve student performance
DOI:
https://doi.org/10.64736/ueplc.2025.v8.n1.2Keywords:
learning, self-instruction, statistics, learning packages, group instructionAbstract
This study evaluated the effectiveness of self-directed learning in improving the performance of university students in Statistics, specifically in the unit on measures of dispersion, within the framework of the transition from a traditional teacher-centered model to a student-centered approach. A quasi-experimental design was applied with 80 Business Administration students (aged 20–25) from a private Ecuadorian university, divided into an experimental group (40 students with self-directed learning) and a control group (40 students with traditional methodology). The content was organized into three self-instructional modules (range, variance, and standard deviation) based on GAISE recommendations, with integrated formative assessments, and performance was measured through a project using real data and a multiple-choice test. Results showed that the experimental group achieved a mean score of 38.54 compared to 34.20 for the control group, representing a 12.7% improvement; the Student’s t-test indicated statistically significant differences (t = 3.21, p = 0.002), leading to the rejection of the null hypothesis. It is concluded that self-directed learning significantly enhances performance in Statistics by fostering student autonomy, metacognitive skills, and deep conceptual understanding, thereby supporting the implementation of student-centered educational models and providing empirical evidence for their adoption in university Statistics courses.
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