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All Journal International Journal of Evaluation and Research in Education (IJERE) Indonesian Journal of Electrical Engineering and Computer Science
Omar Chamorro-Atalaya
Universidad Nacional Tecnológica de Lima Sur
Education

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Text mining and sentiment analysis of teacher performance satisfaction in the virtual learning environment Omar Chamorro-Atalaya; Dora Arce-Santillan; José Antonio Arévalo-Tuesta; Lilia Rodas-Camacho; Genaro Sandoval-Nizama; Rosa Valle-Chavez; Yadit Rocca-Carvajal
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp525-534

Abstract

Although it is true that artificial intelligence and data science have become key tools that contribute to the improvement of many processes, identifying patterns and contributing to decision making, however, there are environments in which they are not yet being using it relevantly and effectively. The objective of this study is to identify the relevant factors, based on the opinions expressed by the students through the social network Twitter regarding the perception of satisfaction with the teaching performance during the virtual learning environment. For which sentiment analysis and text mining are used under the Python programming language environment, through JupyterLab. As results, it was determined that a predominance of 57.27% of positive polarity, identifying that the relevant factors of student satisfaction with teaching performance, are related to the development of the teacher in the class sessions that contributes to the learning of the process control subject through the use of simulation tools such as simulink and tools linked to proportional integral derivative (PID) controllers; on the other hand, there is a percentage of negative polarity of 15.45% that belongs to the factors linked to the laboratory sessions in which graphic representation and block diagrams were used to explain the class session.
Evaluation of the functionality of the virtual platform in the teaching process: analysis based on the usability factor Omar Chamorro-Atalaya; Dora Arce-Santillan; Guillermo Morales-Romero; Beatriz Caycho-Salas; Teresa Guía-Altamirano; César León-Velarde; Risley Rengifo-Tello
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp583-590

Abstract

The use of virtual platforms has been increasing exponentially during the context of distance education, however, there are still limitations to innovate in pedagogical proposals. This can hinder the assurance of student learning, either due to the little planning that occurred in its incorporation, the little knowledge of teachers and students in the educational use or the lack of use of the functionalities that they have incorporated for communication. The purpose of the research is to evaluate the operability of the virtual platform in the teaching-learning process through analysis based on the usability factor, the results will allow us to continue improving the tools linked to distance higher education. At the development of the investigation, a reliability value of 0.985 was obtained by means of Cronbach's Alpha. It was found as findings that 73.8% perceive an improvement in communication and in the exchange of information. Regarding the usability factor, 73.9% fully agree with the information available on the virtual platform and its accessibility. From what was determined, it is concluded that 65.98% of students consider that the functionality of the virtual platform with respect to the usability factor positively influences the teaching-learning process.
Student satisfaction in the context of hybrid learning through sentiment analysis Omar Chamorro-Atalaya; Lisle Sobrino-Chunga; Rosemary Guerrero-Carranza; Ademar Vargas-Díaz; Claudia Poma-Garcia
International Journal of Evaluation and Research in Education (IJERE) Vol 13, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v13i2.26717

Abstract

With the incursion of data science into the academic field and the massification of social networks, it is possible to extract information on student satisfaction that contributes to feedback on teacher teaching strategies and methods. This article aims to determine student satisfaction with teaching performance, through sentiment analysis. Methodologically, the research is of a non-experimental longitudinal design, with a quantitative approach. Data collection was carried out through the social network Twitter, and data analysis was carried out through the sentiment analysis technique. As a result, it was identified that in the first week of class, the highest level of satisfaction was obtained, reaching 96.3% of the total number of students. Meanwhile, in the evaluation weeks, the highest level of dissatisfaction was reaching 29.17%. It is concluded that when going from totally virtual learning to hybrid learning, students express a certain level of dissatisfaction typical of a process of progressive adaptation. Therefore, teachers should take advantage of these findings to redesign assessment rubrics in the context of hybrid teaching. Aspects such as collecting opinions through social networks and extracting a degree of satisfaction through them apply in a crossed way to other professional fields.
Co-Authors Abel Tasayco-Jala Abel Tasayco-Jala Ademar Vargas-Díaz Adrián Quispe-Andía Alicia Jeri-Sandoval Beatriz Caycho-Salas Belmira Marcelo-Veliz Carlos Aliaga-Valdez César León-Velarde César León-Velarde Claudia Poma-Garcia Daniel López-Borjas Darío Villar-Valenzuela Dora Arce-Santillan Elizabeth Auqui-Ramos Elizabeth Auqui-Ramos Erika Zevallos-Vera Evelyn Anicama-Navarrete Florcita Aldana-Trejo Genaro Sandoval-Nizama Guillermo Morales-Romero Guillermo Morales-Romero Gutember Peralta-Eugenio Irma Aybar-Bellido Irma Aybar-Bellido Jesús Ramos-Cruz José Antonio Arévalo-Tuesta José Farfán-Aguilar Lilia Rodas-Camacho Lilly Rocío Moreno-Chinchay Lisle Sobrino-Chunga Lourdes Quevedo-Sánchez Maritte Fierro-Bravo Max Melgarejo-Jara Miguel Levano-Stella Nestor Alvarado-Bravo Nicéforo Trinidad-Loli Orlando Ortega-Galicio Primitiva Ramos-Salaza Risley Rengifo-Tello Ronald Fernando Dávila-Laguna Rosa Valle-Chavez Rosemary Guerrero-Carranza Rufino Alejos-Ipanaque Teresa Guía-Altamirano Vidalina Chaccara-Contreras Yadit Rocca-Carvajal Yeferzon Meza-Chaupis Yeferzon Meza-Chaupis Yurfa Medina-Bedón