Case-Based Learning and Flipped Classroom for Teaching Administrative Processes

In times of confinement due to the COVID-19 pandemic, it was necessary for teachers and students to change the way they teach and learn;in that sense, this research work presents an experience of the application of Case-Based Learning and the Flipped Classroom. The work was applied with 26 students from the Professional School of Political Science and Governance of UNAMBA. The applied methodology was as follow: first, videos of 5 case studies were delivered to the students before the class session;second, in the class session each case was presented and analyzed;and third, the students created a video summary of the case to socialize with the other classmates. Subsequently, a 16-question satisfaction questionnaire was applied with 3 related factors: benefits of the Flipped Learning, use of videos, and collaboration and communication. Finally, the results show that 96.1% achieved positive evaluations in which the participants show their satisfaction with this applied strategy.

The management of rural remote teaching in Bilingual Intercultural Spaces

Problems and manifestations of Bilingual Intercultural Spaces (BIS) in rural areas of Peru as a consequence of social isolation due to Covid-19, are addressed and it seeks to stablish the ways non-face-to-face teaching process is managed. The study is focused on the Peruvian Amazon native communities in which the emergency educational program, "I learn at home", created by the Peruvian government in the context of the current global pandemic, is taught. The methodology is based on the interpretive paradigm with a qualitative approach, case study as design. It used the semi-structured interview technique and the questionnaire as an instrument. The sample includes interviews with eleven teachers of Intercultural Bilingual Education corresponding to Ashaninca, Shipibo Conibo, Nomatsiguenga and Yanesha cultures. For data processing, the NVivo software was used, which allowed the identification of follow-up, accompaniment, feelings of commitment, adversity, and integration. The conclusions of the study highlight that the monitoring and accompaniment of teachers from a BIS perspective are essential to achieve non-face-to-face learning in contexts affected by Covid 19, and there is evidence of inattention from educational authorities in rural areas of such cultures.

Tuberculosis detection architecture with image processing using the SIFT and K-means algorithm

Tuberculosis is a lethal disease that attacks the lungs in a similar way to COVID 19, according to the who, until 2018 there were more than 10 million people infected with tuberculosis and 1.5 million died with this disease. Artificial Intelligence algorithms allow detecting these diseases quickly and massively. We present an architecture to detect tuberculosis with image processing on lung radiographs, using the SIFT and K-means algorithms. We have tested the architecture with 300 radiographs, achieving 90.3% accuracy in classification. © 2020 Instituto Politecnico Nacional. All rights reserved.