Sep 2026· Advances in Social Behavior Research· Vol 17, pp. 63-68· 0 citations
Abstract
Put forward by Thomas L. Saaty in the 1970s, the Analytic Hierarchy Process (AHP) has become one of the most widely used multi‑criteria decision‑making tools around the world. Despite its solid theoretical foundation and broad application scope, the conventional AHP workflow requires constructing full pairwise comparison matrices, solving eigenvalue values and calculating consistency ratios. These steps create high learning barriers for adult learners without professional operations‑research training. This paper develops a Simplified AHP Teaching Model (SAHP‑TM), which targets rational decision‑making education for ordinary adults. Within each evaluation criterion, this model cuts down pairwise comparison times from n(n‑1)/2 to n‑1. It replaces eigenvalue calculation with a normalized ratio‑sum approximation approach and introduces a three‑step consistency check that works without specialized software. This study builds the pedagogical framework for this simplified model, demonstrates its practical use through three real‑life decision scenarios, and tests its performance via a small‑scale teaching workshop. Experimental results indicate that this revised model keeps the ranking stability of standard AHP, while greatly shortening decision‑making duration and lowering learners' perceived cognitive burden. For adult participants dealing with time‑limited, frequent yet moderately important daily choices, this pedagogically optimized AHP is more than just a technical compromise; it serves as a better‑fitted practical instrument for this user group.
Conventional single-dimensional scoring methods for Massive Open Online Course (MOOC) teaching systems often fail to capture holistic learning efficiency and suffer from low evaluation accuracy. To address these limitations, this paper proposes a novel learning efficiency evaluation method integrating Kirkpatrick’s fou...
Yang-Bo Wu, Ng Giap Weng, Beng Yu Leau et al.· International Journal of Inf...· 0 citations
Applied education models aim to prepare students for professional careers by bridging the gap between theoretical knowledge and practical experience. However, existing literature on these models has mostly focused on expert and institutional perspectives, with limited consideration given to students' perceptions and ex...
Sema Çiftçi, Serpil Özer· International Journal of Ass...· 0 citations
This study designs a Decision Support System (SPK) using the Simple Additive Weighting method which is integrated with sensitivity analysis, and proves that the model not only functions as aranking tool, but also as a precise early warning system for university management to carry out data-driven preventive interventio...
A. Arribathi, Haerudin, Danang Rifai· sensi· 0 citations
This paper presents two web-based applications developed as educational tools for teaching Multi-Criteria Decision-Making (MCDM) methods. Despite their widespread use in technical and security domains, MCDM methods remain insufficiently represented in education due to their conceptual complexity and the lack of accessi...
D. Šaur, Jan Albrecht· Automation, Control, and Inf...· 0 citations
Purpose: This follow-up methodological study translates the five domains and 15 criteria of the Integrated Comparative Statement Analysis Model(I-CSAM), proposed by Gong(2025), into a case-centered procedure and a set of practical record forms. It also clarifies the framework’s intended scope and boundary conditions. M...
Jung Hyun Mun, J. Gong· Forum of Public Safety and C...· 0 citations
A web-based decision support system using the Simple Additive Weighting method to rank 21 students based on academic performance, attendance, attitude, and participation, weighted 40%, 25%, 20%, and 15%, respectively, provides a structured and reproducible ranking aid based on school-defined criteria and weights.
P. Sari, Fauriatun Helmiah, Wan Mariatul Kifti· Jurnal IPTEK Bagi Masyarakat· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.