Freedom of Master's Degree Students to Study in Health Curricula: Switching to Optimized Blended Learning as a Solution!

Abstract

Summary Objectives: The Grenoble (France) Master's degree in health includes 17 sub-specialty programs, 120 separate teaching units (TUs) and caters for up to 400 students per year. We present the pedagogical transition to blended learning based on flipped classroom initiated in 2010 to overcome the pedagogical limitations of classical lectures. Methods: The pedagogical organization of each TU is based on the weekly and sequential implementation of five sequences. The first three sequences comprise the learning stages of (1) self-learning on knowledge capsules, (2) interactive on-line questions and votes of interest, and (3) interactive on-site training and explanation meetings. The last two sequences include the evaluation stages with (4) positioning tests, and (5) an anonymous evaluation of the TU allowing access to personalized follow-ups. This pedagogical sequence is completed with a final certification on a tablet computer. Results: The systematic evaluation and debriefing sessions of TUs gave us a clear SWOT vision of the revised Master's degree in health. The feedback was very positive from students, teachers, and the institution, which encourages us to move forward in this transition. Nonetheless, some of this positive feedback was unexpected, such as the ease of managing mobile learners (e.g. Erasmus, International internship) or personalized reinforcement. Conclusion: Our results indicate that a switch to blended learning is feasible in a large Master program, with improvements on student/teacher equity and for the institution.

Aprendizaje desde la virtualidad en el modelo de aula invertida: una experiencia en la educación universitaria

“…Complementario a esto, Di Marco et al (2020) identifican que el ambiente de aprendizaje; desde la transición pedagógica al blended learning, se basa en el aula invertida. Esto inicio el año 2010 para superar las limitaciones pedagógicas de las clásicas clases magistrales en forma de conferencia.…”

An Open-Source Intelligence-Driven Analysis of International Students’ Blended Learning in China

“…NLP algorithm: The accuracy and recall rate of existing language models are updated through the use of self-supervised learning cognition of artificial intelligence models such as BERT, LSTM, and CRF, as well as through the construction of large-scale machine learning datasets and manually labelling sample data (Qi, 2020a;Qi et al, 2022;Zhao et al, 2021). As a result, significant heterogeneous text data processing and risk information mining are made visible (Di Marco et al, 2020;Dias & Diniz, 2012;Ding et al, 2021).…”

Business English blended learning of non-linguistic students: the flipped classroom teaching model

“…Такой формат давал им преимущество перед студентами контрольной группы, которые знакомились с новым грамматическим материалом в аудитории, соответственно однократно, а при условии отсутствия на уроке должны были самостоятельно изучить вопрос, и помогал легко и быстро повторить любую тему. Возможность работать в проектных группах удаленно, находясь дома, способствовала экономии времени, которое можно было потратить на непосредственное выполнение проекта, а не на проезд, положительно сказалась на качестве выполнения такого рода заданий [25].…”

“…Перспективы дальнейших исследований мы видим в применении смешанной модели обучения у студентов 1-2 курса колледжа и сравнении полученных результатов с результатами успеваемости студентов старших курсов в связи с отсутствием однозначного мнения относительно возрастных ограничений имплементации данной технологии в учебный процесс [25].…”