Purpose:The objective of this work is to investigate the effect of synchronous and asynchronous activities on the academic performance of university students. For this purpose, the academic results obtained and the involvement and motivation of the student and the teacher in the different learning methodologies involved are analyzed. Students' perception of the effectiveness of the flipped class with the face-to-face classroom and online methodologies is compared to that of the traditional learning methodology.Design/methodology: Data were collected from undergraduate students in three marketing courses and were analyzed through a quantitative descriptive, quasi-experimental and cross-sectional study. Academic performance with the different learning methodologies and the effect of synchronous and asynchronous activities on academic performance were compared using logistic regression on each course and methodology. Findings:The results showed that academic performance in synchronous and asynchronous activities was better in the flipped class, except for synchronous activities in the online flipped class. In addition, the best academic performance was obtained in the face-to-face inverted classes. The explanatory effect of asynchronous activities on academic performance was also identified. The greatest predictive capacity and the best prognosis were obtained in the online inverted classes. Students expect to obtain satisfactory results with the inverted class methodology and perceive it as effective, although they prefer a mixture of inverted classes and the traditional methodology.Originality/value: We contribute to theoretical and practical research with this new model to study the influence of the flipped learning methodology and asynchronous and synchronous activities on academic performance. We believe that these results, despite the specific and limited scope of the study, will be of great interest to the teaching community and contribute to improving the motivation and performance of students, which constitutes a main challenge in the higher education system.
The objective of this study was to identify university student profiles with different levels of predisposition and usage of digital competences in social communication and collaborative learning (CSCCL) as well as technology use in information search and treatment (CSTI). The sample comprised 383 students from three state universities in Spain. The study employed a questionnaire called “basic digital competences 2.0 in university students” (COBADI). Chi-squared automatic interaction detection (CHAID) algorithm was used for data analysis due to its capability to handle both quantitative and qualitative variables, enabling profiling and the generation of predictive models with easily interpretable graphical representations (decision trees). The results revealed a high level of digital competence in socialization and execution of tasks online, managing digital tools for planning study time, and using resources for information searching and browsing. These findings align with previous works on collaborative writing on the Internet and digital competence. However, students demonstrated low digital competence in data analysis processes and image production using social software apps, which has been linked to task complexity and heavy workload in other studies. Interestingly, the students’ sociodemographic characteristics (age, sex, and university attended) did not influence their predisposition towards the analyzed digital competences. In conclusion, enhancing effective digital teaching in higher education can be achieved by incorporating the teaching of critical analysis of information, addressing information overload, providing instruction on social software apps, and emphasizing collaborative learning. These strategies aim to help students acquire and apply knowledge relevant to the current job market.
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