Exploring the Pre-service Elementary School Teachers’ Predictive Factors for the Satisfaction of Non-face-to-face Online Classes based on Machine Learning Algorithms

2021 ◽  
Vol 34 (1) ◽  
pp. 113-129
Author(s):  
Chul-hyun Lee
Keyword(s):  
Machine Learning ◽  
Elementary School ◽  
Elementary School Teachers ◽  
Predictive Factors ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Online Classes ◽  
School Teachers ◽  
Face To Face

scholarly journals Teleconsultations between Patients and Healthcare Professionals in Primary Care in Catalonia: the Evaluation of Text Classification Algorithms Using Machine Learning

2019 ◽  
Author(s):  
Francesc López Seguí ◽  
Ricardo Ander Egg Aguilar ◽  
Gabriel de Maeztu ◽  
Anna García-Altés ◽  
Francesc García Cuyàs ◽  
...  
Keyword(s):  
Machine Learning ◽  
Primary Care ◽  
Text Classification ◽  
Learning Strategy ◽  
Care Service ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Face To Face ◽  
Classification Tool ◽  
The Impact

Background: the primary care service in Catalonia has operated an asynchronous teleconsulting service between GPs and patients since 2015 (eConsulta), which has generated some 500,000 messages. New developments in big data analysis tools, particularly those involving natural language, can be used to accurately and systematically evaluate the impact of the service. Objective: the study was intended to examine the predictive potential of eConsulta messages through different combinations of vector representation of text and machine learning algorithms and to evaluate their performance. Methodology: 20 machine learning algorithms (based on 5 types of algorithms and 4 text representation techniques)were trained using a sample of 3,559 messages (169,102 words) corresponding to 2,268 teleconsultations (1.57 messages per teleconsultation) in order to predict the three variables of interest (avoiding the need for a face-to-face visit, increased demand and type of use of the teleconsultation). The performance of the various combinations was measured in terms of precision, sensitivity, F-value and the ROC curve. Results: the best-trained algorithms are generally effective, proving themselves to be more robust when approximating the two binary variables "avoiding the need of a face-to-face visit" and "increased demand" (precision = 0.98 and 0.97, respectively) rather than the variable "type of query"(precision = 0.48). Conclusion: to the best of our knowledge, this study is the first to investigate a machine learning strategy for text classification using primary care teleconsultation datasets. The study illustrates the possible capacities of text analysis using artificial intelligence. The development of a robust text classification tool could be feasible by validating it with more data, making it potentially more useful for decision support for health professionals.

scholarly journals Media Evaluasi Pembelajaran Berbasis Kahoot! Untuk Guru SD di Kabupaten Tanah Bumbu

2021 ◽  
Vol 3 (4) ◽  
pp. 349
Author(s):  
Mitra Pramita ◽  
R Ati Sukmawati ◽  
R Ati Sukmawati ◽  
Muhammad Hifdzi Adini ◽  
Muhammad Hifdzi Adini ◽  
...  
Keyword(s):  
Elementary School ◽  
Elementary Teachers ◽  
Elementary School Teachers ◽  
Positive Response ◽  
School Teachers ◽  
Face To Face ◽  
Active Involvement ◽  
Creative Learning ◽  
Partner Schools ◽  
Technology In Learning

Permasalahan yang dialami guru-guru di sekolah mitra yaitu kurangnya pengetahuan terhadap teknologi dalam pembelajaran yang dapat membantu pekerjaan guru menjadi lebih mudah dan menarik. Hal ini menjadi catatan untuk guru agar bisa membuat pembelajaran yang menarik dan lebih kreatif. Pada pembelajaran maupun latihan evaluasi guru bisa memberikan pembelajaran yang menarik dan kreatif dengan menggunakan aplikasi. Aplikasi yang memungkinkan untuk guru salah satunya adalah Aplikasi Kahoot!. Penggunaan aplikasi Kahoot! yang memanfaatkan teknologi dirasa akan lebih menarik dan efisien dibandingkan peserta didik harus menuliskan jawabannya dikertas. Kegiatan pengabdian ini bertujuan untuk memberikan pengetahuan tentang Aplikasi Kahoot! sebagai media evaluasi yang dapat digunakan oleh guru-guru SD di Kabupaten Tanah Bumbu dalam pembelajaran. Pelatihan dilaksanakan pada hari Rabu, 23 Juni 2021 secara tatap muka dengan mematuhi protokol kesehatan dihadiri oleh 29 orang guru SD di Kabupaten Tanah Bumbu. Metode yang digunakan yaitu metode ceramah, metode demonstrasi, diskusi dan tanya jawab. Hasil kegiatan yang telah dilaksanakan untuk guru-guru SD di Kabupaten Tanah Bumbu yaitu pelatihan dapat memberikan manfaat, pemahaman dan kemampuan guru dalam membuat media evalusi menggunakan aplikasi Kahoot! melalui keterlibatan secara aktif dan rata-rata peserta memberikan respon positif terhadap pelatihan yang diberikan.The problem experienced by teachers in partner schools is the lack of knowledge of technology in learning that can help teachers' work become more accessible and more interesting. This is a record for teachers to be able to make learning exciting and more creative. In learning and evaluation exercises, teachers can provide interesting and creative learning by using applications. The application that allows for teachers of them is the Kahoot! Application. Kahoot Applications that utilize technology are felt to be more attractive and efficient than learners must write the answers on the thread. This devotional activity aims to provide knowledge about Kahoot Application as an evaluation medium that elementary teachers can use in Tanah Bumbu Regency in learning. On Wednesday, June 23, 2021, the training was face-to-face by complying with health protocols attended by 29 elementary school teachers in Tanah Bumbu Regency. The methods used are lecture methods, demonstration methods, discussions and Q&A. The results of activities that have been carried out for elementary school teachers in Tanah Bumbu Regency, namely training, can provide benefits, understanding and ability of teachers in making evalusion media using kahoot application through active involvement and the average participant gives a positive response to the training provided. 

scholarly journals Perception of elementary school teachers on Laro Ng Lahi in Quirino, Isabela

2020 ◽  
Vol 6 (3) ◽  
Author(s):  
Mark-Jhon R. Prestoza ◽  
Chrismarie P. Paludipan ◽  
Arvinjay E. Abad
Keyword(s):  
Qualitative Research ◽  
Elementary School ◽  
Elementary School Teachers ◽  
Generation X ◽  
Thematic Analysis ◽  
School Teachers ◽  
Health Culture ◽  
Face To Face ◽  
Advanced Technologies ◽  
Classroom Integration

The purpose of this study is to determine the Perception of Selected Elementary School Teachers on Laro ng Lahi in Quirino, Isabela. The participants of this study were ten (10) selected Elementary School Teachers, five (5) from Generation X and five (5) from the Millenials. The researchers utilized qualitative research through face to face interviews. The responses were analyzed through descriptive coding using the thematic analysis. Based on the gathered data’s, Laro ng Lahi is still being played by pupils despite their access to advanced technologies and some of these are Tumbang Preso, Sipa, Patintero, Tagu-Taguan, Chinese Garter, Sungka, Luksong Tinik, Luksong Baka, Holen, Tug of War, Agawang Sisiw, Bum-Bum Lata, Agawan ng Panyo, Agawan ng Base, and Siyato. The importance of Laro ng Lahi can be classified according to its benefit in terms of health, culture, social aspiration, and values. Laro ng Lahi can be preserved employing continuous engagement in the respective houses and classroom integration by considering the use of native materials.

scholarly journals Teleconsultations between Patients and Healthcare Professionals in Primary Care in Catalonia: The Evaluation of Text Classification Algorithms Using Supervised Machine Learning

2020 ◽  
Vol 17 (3) ◽  
pp. 1093 ◽  
Author(s):  
Francesc López Seguí ◽  
Ricardo Ander Egg Aguilar ◽  
Gabriel de Maeztu ◽  
Anna García-Altés ◽  
Francesc García Cuyàs ◽  
...  
Keyword(s):  
Machine Learning ◽  
Primary Care ◽  
Text Classification ◽  
Learning Strategy ◽  
Care Service ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Supervised Machine Learning ◽  
Face To Face ◽  
The Impact

Background: The primary care service in Catalonia has operated an asynchronous teleconsulting service between GPs and patients since 2015 (eConsulta), which has generated some 500,000 messages. New developments in big data analysis tools, particularly those involving natural language, can be used to accurately and systematically evaluate the impact of the service. Objective: The study was intended to assess the predictive potential of eConsulta messages through different combinations of vector representation of text and machine learning algorithms and to evaluate their performance. Methodology: Twenty machine learning algorithms (based on five types of algorithms and four text representation techniques) were trained using a sample of 3559 messages (169,102 words) corresponding to 2268 teleconsultations (1.57 messages per teleconsultation) in order to predict the three variables of interest (avoiding the need for a face-to-face visit, increased demand and type of use of the teleconsultation). The performance of the various combinations was measured in terms of precision, sensitivity, F-value and the ROC curve. Results: The best-trained algorithms are generally effective, proving themselves to be more robust when approximating the two binary variables “avoiding the need of a face-to-face visit” and “increased demand” (precision = 0.98 and 0.97, respectively) rather than the variable “type of query” (precision = 0.48). Conclusion: To the best of our knowledge, this study is the first to investigate a machine learning strategy for text classification using primary care teleconsultation datasets. The study illustrates the possible capacities of text analysis using artificial intelligence. The development of a robust text classification tool could be feasible by validating it with more data, making it potentially more useful for decision support for health professionals.

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