Education System Based on Algorithm (ESBOA): Design and Simulation-Based Evaluation of an Algorithmic Framework for Teaching, Learning, Assessment, and Educational Management
DOI:
10.29303/jppipa.v12i10.16401Published:
2026-10-15Downloads
Abstract
Universities have teaching, assessment, feedback, and management, yet these parts are rarely joined into one explicit and repeatable process. This paper presents the Education System Based on Algorithm (ESBOA), a framework that treats the educational lifecycle as an algorithm: Input, Objective, Instructions, Teaching, Learning, Assessment, Feedback, and Output, with planning, monitoring, reporting, and improvement running through every stage. The study has three distinct parts. First, framework development: using a design-science approach, recurring problems of traditional teaching were traced to six governing principles, an eight-stage architecture, an input–process–output model, and pseudocode for a bounded corrective-learning loop with teacher referral. Its contribution is not a new learning theory but an explicit, auditable procedure that joins objective-level assessment, a capped feedback cycle, and management reporting, which mastery learning, outcome-based education, adaptive systems, and learning analytics each address only in part. Second, computational verification: because the planned pilot has not yet taken place, the loop was verified in a Monte Carlo simulation of 200 synthetic students over 500 replications, followed by sensitivity analyses of feedback gain, ability, difficulty, cycle cap, assessment error, forgetting, and objective dependency. Under assumed parameters, simulated mean mastery was 0.57 in a single-pass course, 0.83 with the feedback loop, and 0.86 with student-level analysis added; these values follow from the model’s assumptions and are not independent evidence of effectiveness. The benefit of the loop disappeared when feedback carried no information, and the loop required about 2.3 to 2.4 corrective cycles per student. Third, educational effectiveness has not been tested. A twelve-month pilot roadmap, evaluation indicators, a risk register, and ethical safeguards are proposed for computer science courses. The findings support the conceptual and computational feasibility of ESBOA only; whether it improves learning must be established empirically.
Keywords:
Algorithmic education Computer science education Design-science research Educational management Feedback loop Monte Carlo simulation Objective-based assessmentReferences
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