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Item type:Publication, Validation of the Spanish version of the Student Adaptation to College Questionnaire (SACQ-50) with Peruvian students(Taylor & Francis, 2022-11-03)To evaluate the psychometric properties of the short version of the Spanish Student Adaptation to College Questionnaire (SACQ-50, Spanish version). Participants: 1513 students from 14 universities in Peru, mainly females (61.5%), aged between 18 and 30 years. Method: Cross-sectional study with the questionnaire administered in person. Confirmatory factorial analysis was conducted to confirm the scale validity. Results: adequate fits were obtained for the multidimensional structure and for the second order factor of the test. Alpha and omega coefficients indicated adequate test reliability. Conclusions: The Spanish version of the SACQ-50 is a multidimensional scale displaying adequate reliability and validity. The scale may be useful for researchers and other professionals working in the university context. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Validity of the Engagement to Academic Tasks Questionnaire in Peruvian college students(Universidad Catolica del Uruguay, 2023-01-01)Students’ interest and involvement of students in their e-learning during the COVID-19 pandemic has been a little-studied reality. The manifestation of cognitive, emotional, and behavioral involvement has been particularly different in recent years, so having instruments that allow it to be done is necessary for educational research. Therefore, it was sought to adapt and validate an engagement instrument that allows measuring the involvement of students during the pandemic. For this, an engagement questionnaire was applied to 297 university students. The results indicate that the original factorial structure of the model is maintained when adapting to education in a virtual context. Likewise, it was possible to identify that there were no differences in the model according to the gender of the participant, which corroborates a factorial invariance of the model. That is, it has been possible to adapt and validate a psychometric instrument that measures the engagement of students online. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Perceptions About the Assessment in Emergency Virtual Education Due to COVID-19: A Study with University Students from Lima(MDPI, 2023-04-01)The COVID-19 pandemic forced a large section of Peruvian universities to design systems for emergency virtual education. This required professors to quickly learn how to use teaching platforms, digital tools and a wide range of technological skills. In this context, it is remarkable that formative assessment may have been the pedagogical action with the greatest number of challenges, tensions and problems, due to the lack of preparation of many professors to apply performance tests and provide effective feedback. Given this, it is presumed that these insufficiencies (previously exhibited in face-to-face education) were transferred to virtual classrooms in the framework of the health emergency. A survey study was carried out on 240 students from a private university in Lima to find out their perceptions and preferences regarding the tests that their professors administered in the virtual classrooms. It was found that the students were assessed, for the most part, with multiple choice tests. In addition, it was found that the students recognized that the essay tests were the most important for their education, but they preferred multiple choice tests. Finally, it was found that law school students were mostly assessed with essay tests and psychology students with oral tests. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Characterization of the stress level of university students using data mining algorithms(Frontiers Media, 2025-11-21)There is concern about the levels of stress faced by college students and their effects on mental health and academic performance. This study aimed to characterize academic stress levels in college students, using data mining algorithms to classify and predict risk patterns. Data were collected from 287 students using the SISCO Academic Stress Inventory, and classification algorithms and association rules were applied using WEKA software. The results revealed that 75.3% of the students experienced high stress levels, primarily linked to psychological reactions and academic demands. It also compared the predictive performance of 13 algorithms, where J48, LMT, and SimpleLogistic achieved classification accuracies above 89%, surpassing results previously reported in similar educational contexts. Association rule mining further showed that being single and childless was strongly correlated with elevated stress levels, highlighting demographic risk profiles often overlooked in earlier research. By integrating predictive modeling with demographic and behavioral factors, this study extended prior literature by showing how data mining can simultaneously classify and explain academic stress, offering actionable insights for universities to design targeted, evidence-based interventions.2