Plenary Talk at NCTTVTE 2026: Beyond Measuring Outcomes

On Friday, 30 October 2026, I had the honour of sharing a talk titled Beyond Measuring Outcomes: Rethinking Program-Level Assessment and Continuous Improvement in Technology-Oriented Academic Programs at the 1st National Conference on Technology and Technical-Vocational Teacher Education (NCTTVTE 2026). The conference was hosted online by the College of Industrial Education (CIE), Technological University of the Philippines (TUP), Manila. The invitation followed the online iOBE workshop conducted for CIE earlier this month, and it reflects the relevance of iOBE to outcomes assessment at TUP.

The conference brought together more than 200 participants from universities and colleges across the Philippines, many of them teacher educators who prepare the next generation of technical and vocational teachers and trainers. Since their graduates will themselves assess and report learning outcomes, the central question of the talk carried added weight: how do you know whether your students have attained each outcome? The Commission on Higher Education (CHED) asks this of every program in the Philippines, the same as in Malaysia.

The talk showed that conventional reports reduce each outcome to a single number, such as an average or a pass rate, while two classes with the same average can tell very different stories. iOBE’s box plots and population charts reveal the whole class at once, and the same visuals apply from a single quiz to a course, a program and beyond. This richness also makes AI analysis genuinely useful: AI can compare, find patterns and help draft reports, while educators verify, interpret and decide.

The talk concluded that outcomes-based education works as a Plan–Do–Check–Act cycle, and the loop closes only when the Check is rich enough to tell the Act what to change, where, and for whom. Five principles summed up this approach: measure to see deeper, not only to report outputs; read distributions, not only averages; evaluate across various scales with the same visuals; use AI to analyse data, with educators to judge meaning; and close every loop with evidence.

Sincere thanks go to Assoc. Prof. Dr. Neil Andrew F. Calayag, Conference Chair, for the kind invitation and for coordinating the programme, and to Prof. Dr. Apollo P. Portez, Dean of the College of Industrial Education, for his continued support. Thanks also go to the organising committee and to all participants for their attention and interest.