A Personalized Brand Proposal Based on User’s Satisfaction and Curriculum Supported by an Intelligent Job Recommender System

Abstract

One of the main challenges’ universities are confronted is the personalization of education services to improve quality mechanisms and strategies for supporting and assisting students when entering the workforce. Although many universities try to narrow the gap between academic life and job market, it is a highly challenging task to identify the right job for the right graduate. Market strives to find the most talented people and universities attempt to enrich students’ personal brands, but these do not always align. Pitfalls are found in obtaining proper information that harmonize employment offers, course content and graduate’s profile. This research places a transversal analysis of job mismatch in Latin American (LATAM) countries, builds a personalized brand based on satisfaction and course content and offers descriptions for an intelligent job recommender system. Proposal considers that providing a targeted job match implies by picking quantitatively relevant technical knowledge and transversal competencies of individual graduates and matching them to knowledge, skills and attitudes of employment offers and course content, in an efficient manner. Competencies from employment offers obtained with text mining are related to those from a current curriculum to help graduates bring about a personal brand for an appropriate job. Contribution of this research is the construction of a framework to construct match patterns that benefits graduates to meet professional success and to achieve personalization and optimization of the universities’ offered services that represents an incremental improvement. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.