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Despite the difficulties faced during Emergency Remote Teaching (ERT) because of the COVID-19 pandemic, it is also true that such a situation has left a series of learnings that educational institutions around the world should capitalize on. Under this scenario, interest arose in studying three delivery modalities (face-to-face, hybrid, and remote) at the university level, aiming to compare the students’ learning level and their perceptions of each delivery modality. The present study was developed in a private university in Mexico, following a quantitative methodological approach involving 360 students and 14 professors from various schools and geographical locations. Data were collected through pre-and post-tests and a perception questionnaire for students. Findings suggest that the students’ learning level in every modality varies by school and that students positively perceive the three delivery modalities, albeit identifying factors that foster and hinder their learning process in each one. The results of this study contribute to strengthening the research field on teaching during ERT, allowing educational institutions to make better decisions regarding the quality of the educational offer.

Predicting and understanding different key outcomes in a student's academic trajectory such as grade point average, academic retention, and degree completion would allow targeted intervention programs in higher education. Most of the predictive models developed for those key outcomes have been based on traditional methodological approaches. However, these models assume linear relationships between variables and do not always yield accurate predictive classifications. On the other hand, the use of machine-learning approaches such as artificial neural networks has been very effective in the classification of various educational outcomes, overcoming the limitations of traditional methodological approaches. In this study, multilayer perceptron artificial neural network models, with a backpropagation algorithm, were developed to classify levels of grade point average, academic retention, and degree completion outcomes in a sample of 655 students from a private university. Findings showed a high level of accuracy for all the classifications. Among the predictors, learning strategies had the greatest contribution for the prediction of grade point average. Coping strategies were the best predictors for degree completion, and background information had the largest predictive weight for the identification of students who will drop out or not from the university programs. Fil: Musso, Mariel Fernanda. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Centro Interdisciplinario de Investigaciones en Psicología Matemática y Experimental "Dr. Horacio J. A. Rimoldi". Grupo Vinculado CIIPME - Entre Ríos - Centro Interdisciplinario de Investigaciones en Psicología Matemática y Experimental "Dr. Horacio J. A. Rimoldi"; Argentina Fil: Rodríguez Hernández, Carlos Felipe. Katholikie Universiteit Leuven; Bélgica Fil: Cascallar, Eduardo C.. Katholikie Universiteit Leuven; Bélgica

Previous educational research has extensively investigated the relationship between socio-economic status (SES) and academic performance. In higher education, however, this relationship still deserves a comprehensive examination given both practical and conceptual reasons. To attend to this need, a mixed-methods systematic literature review of 42 studies has been carried out. In the first part, a summative content analysis examines how SES and academic performance are measured. In the second part, a meta-analysis estimates the effect size of the relationship between SES and academic performance in higher education. Findings suggest that SES is measured through education, occupation, income, household resources, and neighborhood resources, while academic performance in higher education is measured through achievement, competencies, and persistence. Furthermore, the meta-analysis reveals a positive yet weak relationship between SES and academic performance in higher education. Prior academic achievement, university experience, and working status are more strongly related to academic performance than SES.