One recent study is “Student Evaluation of Blended Learning Implementation and Faculty Performance with Online Components: A Comparative Analysis Across Senior High School Grade Levels and Academic Strands” by Co (2025). IJODL+1 The researchers surveyed 1,450 senior high school students across different academic strands (STEM, ABM, HUMSS, GAS) and grade levels to assess how students perceive blended learning implementation and the online components, as well as to evaluate faculty performance in delivering those online components. They used a mixed‑methods approach: quantitative tests (t‑tests, Kruskal‑Wallis, etc.) plus qualitative data from open‑ended responses. IJODL+1

Strengths: One major strength is the large sample size (1,450 students) which gives statistical power and helps in generalizing findings within the school population/study context. Also, including multiple academic strands allows the study to uncover differences among students in STEM vs. ABM vs. HUMSS vs. GAS, which is useful because not all fields experience online or blended learning equally. The use of mixed methods helps: the quantitative data provide measurable comparisons, while the qualitative data help explain students’ feelings, challenges, and suggestions in their own words. Another strength is its relevance: given how blended learning has become more widespread post‑COVID, insights into its implementation and how students perceive faculty performance are directly useful for policy, teacher training, and school improvements. The fact that they identify specific challenges (internet instability, workload, student mental health) makes their results actionable. IJODL

Weaknesses / Limitations: However, there are limitations. First, while the sample is large, it’s possibly limited to schools (or a particular region) so other schools with different resources might see different results. The study depends heavily on students’ perceptions, which are important but also subjective — perceptions may not always align with actual outcomes (e.g., student learning achievement, retention, etc.). Also, online components are evaluated from a student viewpoint; less is said about measuring actual faculty competence, teaching quality, or objective learning outcomes (e.g. test scores, performance tasks) in relation to blended learning. Moreover, challenges like unstable internet are context‑specific; the study could be limited in offering generalizable technical solutions where infrastructure is more or less advanced. Finally, because it is cross‑sectional (at one point in time), it may not capture change over time, e.g., if students/faculty adapt more over time, or issues resolve. These weaken its ability to show long‑term effectiveness.

I would propose conducting an evaluation titled “Longitudinal Impact of Blended Learning on Learning Outcomes, Engagement, and Equity in Public Secondary Schools of Central Luzon.” The purpose would be to understand not just how blended learning is currently being implemented and perceived, but how it affects student performance over time, whether it improves or worsens educational equity, and what institutional supports are most effective. The evaluation would follow several schools over two school years, collecting baseline data before blended learning implementation (or early in its implementation) and then mid‑ and end points across years. Mixed methods would be used: quantitative measures would include standardized test performance in key subjects (e.g. Math, English, Science), attendance, course completion, and also learning analytics (if online platforms are used) to track engagement (how often students access materials, participate, etc.). Qualitative data would come from student, teacher, and parent interviews/focus groups to understand challenges (e.g. technology access, home learning environment, motivation), successful practices, and perceptions of changes. An equity lens would be central: comparing outcomes by socioeconomic status, by rural vs urban schools, and by gender, to see whether blended learning helps narrow or widen gaps. The evaluation would include ongoing feedback loops, meaning that initial findings would be shared with schools so they can adjust practices. At the end of the evaluation, actionable recommendations would be given for policy (e.g. resource allocation, teacher training), infrastructure (internet, devices), and pedagogy (best instructional designs). While ambitious, the longitudinal design will help show cause‑and‑effect more clearly, including whether changes are sustained or transient, how adaptation happens, and how contextual factors mediate success.