The school-dropout problem is a serious issue that affects both a country’s education system and its economy, given the substantial investment in education made by national governments. One strategy for counteracting the problem at an early stage is to identify students at risk of dropping out. The present study introduces a model to predict student dropout rates in the Escuela Politécnica Nacional leveling course. Data related to 2097 higher education students were analyzed; a logistic regression model and an artificial neural network model were trained using four variables, which incorporated student academic and socio-economic information. After comparing the two models, the neural network, with an experimentally defined architecture of 4–7–1 architecture and a logistic activation function, was selected as the model that should be applied to early predict dropout in the leveling course. The study findings show that students with the highest risk of dropping out are those in vulnerable situations, with low application grades, from the Costa regime, who are enrolled in the leveling course for technical degrees. This model can be used by the university authorities to identify possible dropout cases, as well as to establish policies to reduce university dropout and failure rates.

In Ecuador, affirmative action policies enable students from vulnerable groups to preferentially enter universities. However, these policies are limited to admission and do not include academic or socio-economic support mechanisms that, according to the literature, promote student insertion in the higher education system. In this study, the effects of socio-academic intervention on the academic performance of vulnerable students are presented. For this, 41 students were selected among 164 vulnerable students entering the Escuela Politécnica Nacional in the second term of 2019. The 41 students attended a socio-academic intervention course for one term, while the remaining 123 attended the Escuela Politécnica Nacional levelling course directly. Once both groups of students finished the levelling course, their performance in each of the course subjects was compared. The results showed that the academic performance of the students in the intervention was significantly higher in mathematics and geometry compared to the students who had no intervention. These results show that the socio-academic intervention promotes the real insertion of vulnerable students in the university system.

La ineficiencia de los métodos convencionales para remover tensoactivos y patógenos de aguas residuales ha derivado en la necesidad de desarrollar tratamientos alternativos, como el proceso Fenton y sus variantes. En este estudio se aplicó un proceso Fenton convencional y modificado con ácido etilendiaminotetraacético (EDTA) como tratamiento complementario para aguas residuales rurales de Quito, Ecuador. Inicialmente, se establecieron las condiciones de concentración de peróxido de hidrógeno (H₂O₂), la relación molar Fe²⁺:H₂O₂ y requerimiento de agitación para un proceso Fenton convencional. Estas condiciones se adaptaron a un proceso Fenton modificado con EDTA- en el cual se definieron las condiciones de relación molar Fe²⁺:EDTA y de pH. Las mejores condiciones establecidas fueron: concentración de H₂O₂ de 124,4 mM, agitación continua de 130 rpm, relación molar EDTA:Fe²⁺:H₂O₂ de 1:1:20 y pH de 6,41 (pH del efluente). Bajo estas condiciones, a partir de una muestra con concentración inicial de tensoactivos, coliformes fecales y DQO de 6,12 mg/L, 71000 UFC/mL y 980 mg/L, respectivamente, se alcanzó inactivación total de coliformes fecales y una reducción de 97% para tensoactivos y 93% para la demanda química de oxígeno a los 15 min de tratamiento. La concentración final de estos contaminantes cumplió con los estándares establecidos por la Agencia de Protección Ambiental (EPA). Este tratamiento podría, potencialmente, ser aplicado para complementar el tratamiento de aguas residuales que presenten problemas similares.

Since 2017, Secretaría Nacional de Educación Superior, Ciencia, Tecnología e Innovación (SENESCYT), has included, among the new students entering the Leveling Course of Escuela Politécnica Nacional (EPN), those from Affirmative Action population segment. These students tend to show low academic performance and high dropping out rates. Mathematics, of considerable importance for engineering training, is the subject that shows the lowest indicator of academic performance during high school, for this reason, EPN in response to this problem, proposes a Mathematics Pilot Program for students of engineering from vulnerable groups. To this end, it was conducted a descriptive analysis of the information of students enrolled in the Leveling Course between the semesters 2017-A and 2018-A, and based on the criteria of the teachers of the Leveling Course, a diagnostic test was designed and applied to the new students of the 2018-B semester, this test evaluated only basic Mathematics. It was determined that the students from Affirmative Action group presented low passing rate and high dropping out rate during the semesters under study, likewise, students of Affirmative Action group got a low average score in the diagnostic test which evidences poor academic level of these students prior to entering the Leveling Course. In this sense, it is proposed that the pilot program should be structured in 6 units, with special emphasis on Geometry and Trigonometry, and real-valued functions. It is recommended that the pilot program should be implemented as a course prior to the Leveling Course, so that the Government's Affirmative Action program fulfills its mission of effectively including students from vulnerable groups in the Higher Education System

REMOCIÓN DE TENSOACTIVOS Y COLIFORMES EN AGUAS RESIDUALES DOMÉSTICAS MEDIANTE PROCESOS FENTON