Design, Development, and Evaluation of a Critiquing-Based Mobile-Web Employment Recommender System

Randy C. Polancos and Ph.D. Cenie V. Malabanan
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Randy C. Polancos: Faculty, Mindanao State University – Main, Marawi City, Philippines
Ph.D. Cenie V. Malabanan: Professor, Mindanao State University – Iligan Institute of Technology Iligan City, Philippines

International Journal of Latest Technology in Engineering, Management & Applied Science, 2025, vol. 14, issue 4, 11-19

Abstract: With the growing availability of internet connectivity and the widespread use of smartphones and computers across the population, technology presents a powerful opportunity to bridge the communication gap between local household employers and skilled workers seeking employment. In response to this, the present research aims to design, develop, and evaluate a mobile-web application that serves as a platform connecting household employers with skilled workers. The main feature of the application is the use of a critiquing-based recommendation system, which assists employers in efficiently identifying workers who best match their needs and preferences. This mobile-web system is designed based on the Activity Theory Model (ATM) by Engeström (1987), which was utilized during the requirements-gathering phase. The design and development process were guided by the ADDIE model (Grafinger, 1988), ensuring a structured approach. The development process went through three iterative cycles, before producing the finalized version of the application. This version was then implemented and evaluated using the Usability Metric for User Experience (UMUX), a validated instrument by Finstad (2010), to assess effectiveness, efficiency, and user satisfaction. Results indicated strong user agreement regarding the application’s efficiency and effectiveness, with high levels of satisfaction reported. The application achieved a UMUX mean score of 94.3, indicating a high level of usability. Additionally, the critiquing feature achieved a weighted mean score of 6.8, indicating high user satisfaction with its functionality and relevance.

Date: 2025
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