Problem solving strategies: regression analysis on assessment

Effective assessment informs both students and instructors about learning progress and areas for improvement. Assessments point-out to students and teachers what to do to achieve the intended learning outcomes given the necessary support. This study aims to develop a predictive model that uses formative assessments to predict students’ success on summative assessments through cross-sectional analysis. Data are collected from the formative and summative performances of fourth year college students. The collected data are analyzed using Descriptive Statistics, Shapiro-Wilk test, Pearson Product Moment Correlation and One-Way ANOVA. To shed light on formative tests’ predictive power for summative outcomes, a linear equation model is created through linear regression analysis. Results show that when formative tests are used successfully to track students’ progress, identify learning gaps, give timely feedback, students will have better summative performances. In light of the study, practitioners are encouraged to carefully design classroom assessments putting premium on formative assessments and feedback mechanisms to yield better learning outcomes.