Automated Formative Feedback for Learning Statistics and Cultivating Growth Mindset among College Students

This study examined the impact of automated formative feedback on college students’ independent learning skills, performance in hypothesis testing concept, and growth mindset. Grounded in Vygotsky’s social constructivist theory and Hattie and Timperley’s feedback model, the intervention addressed the lack of timely, meaningful feedback in large classroom settings. A pre-test/post-test quasi-experimental design was employed, involving two intact sections of Elementary Statistics students randomly selected through cluster sampling from six available sections. From each section, 30 students were randomly chosen for inclusion in the analysis. The experimental group received automated formative feedback embedded in hypothesis testing exercises developed using Microsoft PowerPoint and assignments delivered through Google Classroom. The control group completed the same tasks without feedback, receiving only marks indicating correct or incorrect answers. Data were collected using validated instruments for independent learning skills and growth mindset, and a 50-item test on hypothesis testing. Results indicated that the experimental group demonstrated significantly higher gains across all three outcome variables. Students who received feedback showed greater engagement, deeper conceptual understanding, stronger confidence in completing tasks independently, and increased motivation. Findings support the use of automated formative feedback to enhance independent learning and foster a growth mindset in statistics education.