Defining Recursive Feedback

In e-Learning Ecologies (Cope & Kalantzis, 2017), recursive feedback refers to a continuous, iterative process of assessment where learners receive ongoing responses that guide their learning journey. Unlike traditional end-of-unit exams, recursive feedback provides learners with immediate, personalized insights, allowing them to adjust their strategies and improve progressively.

What is Computer Adaptive Testing?

Computer Adaptive Testing (CAT) is a digital assessment approach that exemplifies recursive feedback. In CAT, the system adapts the difficulty of test questions in real-time based on the learner’s previous responses. If a student answers correctly, the system presents a more challenging item; if incorrect, it adjusts to an easier one. This creates a personalized feedback loop where assessment both measures and supports learning.

Example in Practice (Philippine Context)

In the Philippines, computer adaptive testing is beginning to emerge through online learning platforms and national initiatives:

DepEd Commons and Online Quizzes
Some DepEd teachers use adaptive online quizzes via tools like Quizizz and Kahoot, which adjust question difficulty and provide instant scores, explanations, and leaderboards. This keeps learners engaged while offering recursive feedback at every stage.

Civil Service and Licensure Review Platforms
Review centers for board exams and the Civil Service Exam increasingly adopt adaptive practice tests. Platforms analyze test-takers’ weak areas and generate follow-up questions targeting those competencies—helping learners focus their review strategically.

Higher Education Case
Universities like the University of the Philippines Open University (UPOU) experiment with adaptive testing in LMS platforms like Moodle. Here, recursive feedback ensures students are constantly aware of their progress and areas for improvement.

Why It Matters

CAT demonstrates how recursive feedback makes learning more personalized, efficient, and motivating. It reduces test anxiety by tailoring the difficulty to the learner’s level while ensuring mastery of essential skills. This aligns with the vision of e-Learning Ecologies: transforming assessment from a one-time judgment into a continuous learning process.

References

Cope, B., & Kalantzis, M. (2017). e-Learning Ecologies: Principles for New Learning and Assessment. Routledge.

Wainer, H. (2000). Computerized Adaptive Testing: A Primer. Lawrence Erlbaum Associates.

DepEd Commons – Official learning platform of the Philippine Department of Education.