About this Research Topic
Certainly, the impact of COVID-19 has not gone unnoticed within higher education settings. Importantly, we must also look at how the pandemic has impacted higher education communities. The change in the teaching-learning setting from face-to-face to online formats has undoubtedly influenced both teachers and students. Considering the pandemic, several questions have arisen, such as:
• Have there been barriers that have prevented adequate training?
• Have academic failure and higher education dropouts been affected by the new online education formats?
• Have the expectations of teachers and students been met during this atypical academic year?
• Have the right tools been used to carry out proper online training?
It is critical to consider solutions to reduce the phenomenon of higher education dropout. There are many proposed measures so far, including: improving the quality of higher education, improving the continuous training plans of teachers, promoting welcome programs for new students, tutoring programs, study grants and economic measures to reconcile professional and academic life, among others. These measures are aimed at improving the quality of higher education and promoting the continuous training of our students, thereby positively affecting professional qualifications and the well-being of individuals and society.
Therefore, the scope of this Research Topic can involve researchers and teachers from different academic disciplines, since the field of work encompasses affective, cognitive, and social variables that influence university dropout, a multi-causal phenomenon.
The goals of this Research Topic are diverse. Firstly, we aim to disseminate information about the phenomenon of university dropout so that the educational community knows the true scope of the problem, as well as its causes and consequences. Secondly, we aim to disseminate preventive or palliative measures regarding university dropout. We also welcome any educational experience that can shed light on the phenomenon of academic study abandonment and contribute to its understanding. Finally, we would like to include artificial intelligence techniques that are being applied in educational environments and assess what benefits they could have in the measurement of university dropout, as the use of tools based on artificial intelligence (e.g., neural networks, fuzzy sets) allows for the optimization of results.
Keywords: higher education, dropout, self-regulation, artificial intelligence, fuzzy
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