Monitoring Systems and Teacher Professionalization: Analysis of Practice Effectiveness Between Competency-Based Approach Requirements and AI Integration

Abstract

In a Cameroonian educational context marked by the transition to the Competency-Based Approach (CBA) and the rapid expansion of digital technologies, this study analyzes the effectiveness of teaching monitoring systems in teacher professionalization and examines their impact on student learning outcomes. Using a mixed-methods sequential explanatory design, data were collected from 50 secondary and higher education teachers and 68 students across three regions of Cameroon (Centre, Littoral, and West). Results reveal that only 38% of monitored teachers receive systematic formative feedback, while 72% report a substantiated need for artificial intelligence (AI) tools in their pedagogical practices. Hierarchical regression analyses demonstrate that monitoring effectiveness exploratorily suggests associations with teacher professional development (β = 0.61; p < 0.001) and student academic performance (β = 0.47; p < 0.01). A bootstrapping mediation model (5,000 iterations; Hayes, 2022, PROCESS macro v4.2) reveals that AI integration into monitoring systems positively mediates the relationship between monitoring and professionalization (indirect effect = 0.29; 95% CI [0.18; 0.42]; mediation ratio = 50.9%). These findings underscore the urgent need for a substantial reform of monitoring systems in Cameroon, integrating CBA requirements with the strategic opportunities offered by AI-enhanced pedagogical support.