Monitoring General Education Course Performance Using Statistical Process Control Technique: A Multi-Program Analysis

Abstract

This study examines the use of Statistical Process Control (SPC), with a focus
on the P-chart, to monitor performance in General Education (GE) core
courses in higher education. GE courses help build students’ foundational
knowledge and skills, so a systematic and objective evaluation is needed. The
study used a quantitative research design and analyzed secondary data from
three academic programs: the Bachelor of Science in Marine Biology (BSMB),
the Bachelor of Science in Information Technology (BSIT), and the Bachelor
of Technology and Livelihood Education (BTLEd). Data covered three
academic years, from 2021 to 2024. The P-chart was used to determine the
proportion of nonconforming student performance and to assess process
variation and stability across programs and time. Results revealed a general
trend of improvement and increased process stability, particularly in the most
recent academic year. However, multiple out-of-control points were observed
during the pandemic period, which may be attributed to disruptions such as
limited face-to-face instruction and unstable internet connectivity. The
findings demonstrate that SPC techniques are effective in identifying
performance variability and pinpointing courses that require targeted
instructional interventions. This study underscores the value of SPC as a tool
for continuous quality improvement in GE instruction at USTP–Panaon and
proposes a replicable model for integrating statistical monitoring tools into
educational evaluation and quality assurance practices in higher education
institutions.