Advancing school dropout early warning systems: the IAFREE relational model for identifying at-risk students - de Vasconcelos, Angelina Nunes; Freires, Leogildo Alves; Loureto, Gleidson Diego Lopes; Fortes, Gabriel; da Costa, Júlio Cezar Albuquerque; Torres, Luan Filipy Freire; Bittencourt, Ig Ibert; Cordeiro, Thiago Damasceno; Isotani, Seiji (Frontiers in Psychology, 2023)
There is a global effort to address the school dropout phenomenon. The urgency to act on it comes from the harmful evidence that school dropout has on societal and individual levels. Early Warning Systems (EWS) for school dropout at-risk student identification have been developed to anticipate and help schools have a better chance of acting on it. However, several studies point to a doubt that current EWS may come too late because they use only publicly available and general student and school information. We hypothesize that having a tool to assess more subjective and inter-relational factors would help anticipate where and when to act to prevent school dropout. This study aimed to develop a multidimensional measure for assessing relational factors for predicting school dropout (SD) risk in the Brazilian context. We performed several procedures, including (a) the specialized literature review, (b) the item development of the Relational Factors for the Risk of School Dropout Scale (IAFREE in Portuguese), (c) the content validity analysis, (d) a pilot study, and (e) the administration of the IAFREE to a large Brazilian sample of high school and middle school students (N = 15,924).