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RESUMENLa deserción estudiantil universitaria es uno de los mayores problemas con el que se enfrenta el sistema de educación superior. Las autoridades de las universidades han venido presentando gran preocupación debido a que ante el aumento en la demanda de la educación superior, el número de alumnos que logra culminar sus estudios superiores no es el esperado, evidenciándose el abandono de un gran número de estudiantes en los primeros semestres. Esto genera problemas financieros en las universidades. La finalidad de este artículo es mostrar, luego de una exhaustiva revisión bibliográfica, los modelos existentes en relación con la deserción estudiantil en la universidad y responder las cuestiones que giran en torno a este tema. Palabras clave: deserción, deserción estudiantil, permanencia, retención ABSTRACTCollege student dropout is one of the greatest problems faced by the higher education system. University authorities have been showing great concern because, in spite of the increase in demand for higher education, the number of students that complete their education is not as expected, demonstrating that a large number of students abandons school, mainly during the initial semesters. This generates financial problems to the universities. This paper aims to show, after a comprehensive literature review, existing models in connection with college student dropout and answer the questions to this regard.

In this research, we present the essential principles of an authentic outcome based educational model related to the development of learning outcomes, performance indicators and their rubrics with a focus on measurement of specific skills related to Bloom's 3 learning domains and their learning levels for engineering specializations. An analysis of culminating ABET Engineering Accreditation Commission student outcomes is made with reference to Bloom's 3 learning domains and their learning levels. A hypothetical model is presented for this analysis. The correlation of ABET student outcomes, course learning outcomes and performance indicators is clearly outlined. The necessity of the use of performance indicators is highlighted especially in reference to the measurement of course learning outcomes, development of assessments, teaching and learning activities. The importance of scientific constructive alignment of learning outcomes, performance indicators, assessments, teaching and learning strategies is discussed. A novel hybrid rubric for accurate assessment and scoring of student performances is also presented. Actual examples of implementation of this theory to program, course and student level performance evaluations using state of the art web based digital technology are shown. In summary, the benefits of specific performance indicators over generic ones are explained in detail with respect to support of authentic OBE principles, scientific constructive alignment, accurate measurement of student performances in specific engineering learning activities, performance failure analysis and continuous quality improvement.

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Engineering accreditation agencies and governmental educational bodies worldwide require programs to evaluate specific learning outcomes information for attainment of student learning and establish accountability. Ranking and accreditation have resulted in programs adopting shortcut approaches to collate cohort information with minimally acceptable rigor for Continuous Quality Improvement (CQI). With tens of thousands of engineering programs seeking accreditation, qualifying program evaluations that are based on reliable and accurate cohort outcomes is becoming increasingly complex and is high stakes. Manual data collection processes and vague performance criteria assimilate inaccurate or insufficient learning outcomes information that cannot be used for effective CQI. Additionally, due to COVID19 global pandemic, many accreditation bodies have cancelled onsite visits and either deferred or announced virtual audit visits for upcoming accreditation cycles. In this study, we examine a novel meta-framework to qualify state of the art digital Integrated Quality Management Systems for three engineering programs seeking accreditation. The digital quality systems utilize authentic OBE frameworks and assessment methodology to automate collection, evaluation and reporting of precision CQI data. A novel Remote Evaluator Module that enables successful virtual ABET accreditation audits is presented. A theory based mixed methods approach is applied for evaluations. Detailed results and discussions show how various phases of the meta-framework help to qualify the context, construct, causal links, processes, technology, data collection and outcomes of comprehensive CQI efforts. Key stakeholders such as accreditation agencies and universities can adopt this multi-dimensional approach for employing a holistic metaframework to achieve accurate and credible remote accreditation of engineering programs.

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