Digital divide to virtual education : evidence from Argentina
Resumen COVID-19 forced an abrupt change in the teaching-learning process. From a scheme based on face-to-face teaching, we moved to a unique and exclusive system of virtual education. This change in the educational system involved forced adaptations of both students and teachers without a prior ana...
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| Autor*in: |
Catalán, María José [verfasserIn] Merlo, Juan José [verfasserIn] |
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| Format: |
E-Artikel |
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Englisch |
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2024 |
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Enthalten in: Atlantic review of economics - La Coruña : [Verlag nicht ermittelbar], 2011, 7(2024), 1 vom: Juli, Seite 1-35 |
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| Übergeordnetes Werk: |
volume:7 ; year:2024 ; number:1 ; month:07 ; pages:1-35 |
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| 520 | |a Resumen COVID-19 forced an abrupt change in the teaching-learning process. From a scheme based on face-to-face teaching, we moved to a unique and exclusive system of virtual education. This change in the educational system involved forced adaptations of both students and teachers without a prior analysis of the required technological feasibility.This work studies the problem of digital division existing in Argentina, related to the access and use of technology and infrastructure in its educational system. From an empirical point of view, it seeks to answer the following questions: are students and teachers prepared to face a virtual learning process from a technological point of view? And what variables and factors determine technological access to the virtual education process?For this, two Virtual Education Indices are built, one aimed at students and the other at teachers, based on the access and use of PCs and mobile phones. Then, they are used to estimate a logit model for technological access for students and another for technological access for teachers.Using data from the EPH, it is analyzed how technologically prepared students and teachers are to participate in the virtual education process, at its three levels. A Technological Index of Virtual Education is built for students and another for teachers, based on the possession of a PC and the Internet and through the use of the Internet, PC and cell phone.The analysis reveals that students are better prepared from a technological point of view than teachers to be able to face the virtual education process.The most important variables that positively affect the probability of having technological access to virtual education in the case of students are: the age of the student, the total family income, the education of the student's mother, work in the labor market of the mother of the student, the number of people employed within the home and the number of inhabitants of the residential area. The negative effects on the probability of technological access to virtual education come from: attendance at public education establishments, overcrowding within the home and the number of children under 10 years of age.The probability of having technological access to virtual education in the case of teachers is positively affected by: the teacher's years of education and individual income. While the age of the teacher, overcrowding within the home and the number of inhabitants of the residential area negatively affect the probability of technological access to virtual education for teachers. | ||
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(DE-627)1898492824 (DE-599)KXP1898492824 DE-627 ger DE-627 rda eng I21 R50 O33 jelc Catalán, María José verfasserin aut Digital divide to virtual education evidence from Argentina María José Catalán, Juan José Merlo 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Resumen COVID-19 forced an abrupt change in the teaching-learning process. From a scheme based on face-to-face teaching, we moved to a unique and exclusive system of virtual education. This change in the educational system involved forced adaptations of both students and teachers without a prior analysis of the required technological feasibility.This work studies the problem of digital division existing in Argentina, related to the access and use of technology and infrastructure in its educational system. From an empirical point of view, it seeks to answer the following questions: are students and teachers prepared to face a virtual learning process from a technological point of view? And what variables and factors determine technological access to the virtual education process?For this, two Virtual Education Indices are built, one aimed at students and the other at teachers, based on the access and use of PCs and mobile phones. Then, they are used to estimate a logit model for technological access for students and another for technological access for teachers.Using data from the EPH, it is analyzed how technologically prepared students and teachers are to participate in the virtual education process, at its three levels. A Technological Index of Virtual Education is built for students and another for teachers, based on the possession of a PC and the Internet and through the use of the Internet, PC and cell phone.The analysis reveals that students are better prepared from a technological point of view than teachers to be able to face the virtual education process.The most important variables that positively affect the probability of having technological access to virtual education in the case of students are: the age of the student, the total family income, the education of the student's mother, work in the labor market of the mother of the student, the number of people employed within the home and the number of inhabitants of the residential area. The negative effects on the probability of technological access to virtual education come from: attendance at public education establishments, overcrowding within the home and the number of children under 10 years of age.The probability of having technological access to virtual education in the case of teachers is positively affected by: the teacher's years of education and individual income. While the age of the teacher, overcrowding within the home and the number of inhabitants of the residential area negatively affect the probability of technological access to virtual education for teachers. Analysis of education (dpeaa)DE-206 Regional analysis (dpeaa)DE-206 Technological change (dpeaa)DE-206 Merlo, Juan José verfasserin aut Enthalten in Atlantic review of economics La Coruña : [Verlag nicht ermittelbar], 2011 7(2024), 1 vom: Juli, Seite 1-35 Online-Ressource (DE-627)663843308 (DE-600)2616322-6 (DE-576)347002854 2174-3835 nnns volume:7 year:2024 number:1 month:07 pages:1-35 http://www.aroec.org/ojs/index.php/ARoEc/article/download/166/128/ Verlag kostenfrei http://www.aroec.org/ojs/index.php/ARoEc/article/view/166 Verlag kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2050 GBV_ILN_2111 GBV_ILN_2129 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 7 2024 1 7 1-35 26 01 0206 4565589222 x1z 13-08-24 2403 01 DE-LFER 4574099887 00 --%%-- --%%-- n --%%-- l01 03-09-24 2403 01 DE-LFER http://www.aroec.org/ojs/index.php/ARoEc/article/download/166/128/ |
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(DE-627)1898492824 (DE-599)KXP1898492824 DE-627 ger DE-627 rda eng I21 R50 O33 jelc Catalán, María José verfasserin aut Digital divide to virtual education evidence from Argentina María José Catalán, Juan José Merlo 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Resumen COVID-19 forced an abrupt change in the teaching-learning process. From a scheme based on face-to-face teaching, we moved to a unique and exclusive system of virtual education. This change in the educational system involved forced adaptations of both students and teachers without a prior analysis of the required technological feasibility.This work studies the problem of digital division existing in Argentina, related to the access and use of technology and infrastructure in its educational system. From an empirical point of view, it seeks to answer the following questions: are students and teachers prepared to face a virtual learning process from a technological point of view? And what variables and factors determine technological access to the virtual education process?For this, two Virtual Education Indices are built, one aimed at students and the other at teachers, based on the access and use of PCs and mobile phones. Then, they are used to estimate a logit model for technological access for students and another for technological access for teachers.Using data from the EPH, it is analyzed how technologically prepared students and teachers are to participate in the virtual education process, at its three levels. A Technological Index of Virtual Education is built for students and another for teachers, based on the possession of a PC and the Internet and through the use of the Internet, PC and cell phone.The analysis reveals that students are better prepared from a technological point of view than teachers to be able to face the virtual education process.The most important variables that positively affect the probability of having technological access to virtual education in the case of students are: the age of the student, the total family income, the education of the student's mother, work in the labor market of the mother of the student, the number of people employed within the home and the number of inhabitants of the residential area. The negative effects on the probability of technological access to virtual education come from: attendance at public education establishments, overcrowding within the home and the number of children under 10 years of age.The probability of having technological access to virtual education in the case of teachers is positively affected by: the teacher's years of education and individual income. While the age of the teacher, overcrowding within the home and the number of inhabitants of the residential area negatively affect the probability of technological access to virtual education for teachers. Analysis of education (dpeaa)DE-206 Regional analysis (dpeaa)DE-206 Technological change (dpeaa)DE-206 Merlo, Juan José verfasserin aut Enthalten in Atlantic review of economics La Coruña : [Verlag nicht ermittelbar], 2011 7(2024), 1 vom: Juli, Seite 1-35 Online-Ressource (DE-627)663843308 (DE-600)2616322-6 (DE-576)347002854 2174-3835 nnns volume:7 year:2024 number:1 month:07 pages:1-35 http://www.aroec.org/ojs/index.php/ARoEc/article/download/166/128/ Verlag kostenfrei http://www.aroec.org/ojs/index.php/ARoEc/article/view/166 Verlag kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2050 GBV_ILN_2111 GBV_ILN_2129 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 7 2024 1 7 1-35 26 01 0206 4565589222 x1z 13-08-24 2403 01 DE-LFER 4574099887 00 --%%-- --%%-- n --%%-- l01 03-09-24 2403 01 DE-LFER http://www.aroec.org/ojs/index.php/ARoEc/article/download/166/128/ |
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(DE-627)1898492824 (DE-599)KXP1898492824 DE-627 ger DE-627 rda eng I21 R50 O33 jelc Catalán, María José verfasserin aut Digital divide to virtual education evidence from Argentina María José Catalán, Juan José Merlo 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Resumen COVID-19 forced an abrupt change in the teaching-learning process. From a scheme based on face-to-face teaching, we moved to a unique and exclusive system of virtual education. This change in the educational system involved forced adaptations of both students and teachers without a prior analysis of the required technological feasibility.This work studies the problem of digital division existing in Argentina, related to the access and use of technology and infrastructure in its educational system. From an empirical point of view, it seeks to answer the following questions: are students and teachers prepared to face a virtual learning process from a technological point of view? And what variables and factors determine technological access to the virtual education process?For this, two Virtual Education Indices are built, one aimed at students and the other at teachers, based on the access and use of PCs and mobile phones. Then, they are used to estimate a logit model for technological access for students and another for technological access for teachers.Using data from the EPH, it is analyzed how technologically prepared students and teachers are to participate in the virtual education process, at its three levels. A Technological Index of Virtual Education is built for students and another for teachers, based on the possession of a PC and the Internet and through the use of the Internet, PC and cell phone.The analysis reveals that students are better prepared from a technological point of view than teachers to be able to face the virtual education process.The most important variables that positively affect the probability of having technological access to virtual education in the case of students are: the age of the student, the total family income, the education of the student's mother, work in the labor market of the mother of the student, the number of people employed within the home and the number of inhabitants of the residential area. The negative effects on the probability of technological access to virtual education come from: attendance at public education establishments, overcrowding within the home and the number of children under 10 years of age.The probability of having technological access to virtual education in the case of teachers is positively affected by: the teacher's years of education and individual income. While the age of the teacher, overcrowding within the home and the number of inhabitants of the residential area negatively affect the probability of technological access to virtual education for teachers. Analysis of education (dpeaa)DE-206 Regional analysis (dpeaa)DE-206 Technological change (dpeaa)DE-206 Merlo, Juan José verfasserin aut Enthalten in Atlantic review of economics La Coruña : [Verlag nicht ermittelbar], 2011 7(2024), 1 vom: Juli, Seite 1-35 Online-Ressource (DE-627)663843308 (DE-600)2616322-6 (DE-576)347002854 2174-3835 nnns volume:7 year:2024 number:1 month:07 pages:1-35 http://www.aroec.org/ojs/index.php/ARoEc/article/download/166/128/ Verlag kostenfrei http://www.aroec.org/ojs/index.php/ARoEc/article/view/166 Verlag kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2050 GBV_ILN_2111 GBV_ILN_2129 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 7 2024 1 7 1-35 26 01 0206 4565589222 x1z 13-08-24 2403 01 DE-LFER 4574099887 00 --%%-- --%%-- n --%%-- l01 03-09-24 2403 01 DE-LFER http://www.aroec.org/ojs/index.php/ARoEc/article/download/166/128/ |
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(DE-627)1898492824 (DE-599)KXP1898492824 DE-627 ger DE-627 rda eng I21 R50 O33 jelc Catalán, María José verfasserin aut Digital divide to virtual education evidence from Argentina María José Catalán, Juan José Merlo 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Resumen COVID-19 forced an abrupt change in the teaching-learning process. From a scheme based on face-to-face teaching, we moved to a unique and exclusive system of virtual education. This change in the educational system involved forced adaptations of both students and teachers without a prior analysis of the required technological feasibility.This work studies the problem of digital division existing in Argentina, related to the access and use of technology and infrastructure in its educational system. From an empirical point of view, it seeks to answer the following questions: are students and teachers prepared to face a virtual learning process from a technological point of view? And what variables and factors determine technological access to the virtual education process?For this, two Virtual Education Indices are built, one aimed at students and the other at teachers, based on the access and use of PCs and mobile phones. Then, they are used to estimate a logit model for technological access for students and another for technological access for teachers.Using data from the EPH, it is analyzed how technologically prepared students and teachers are to participate in the virtual education process, at its three levels. A Technological Index of Virtual Education is built for students and another for teachers, based on the possession of a PC and the Internet and through the use of the Internet, PC and cell phone.The analysis reveals that students are better prepared from a technological point of view than teachers to be able to face the virtual education process.The most important variables that positively affect the probability of having technological access to virtual education in the case of students are: the age of the student, the total family income, the education of the student's mother, work in the labor market of the mother of the student, the number of people employed within the home and the number of inhabitants of the residential area. The negative effects on the probability of technological access to virtual education come from: attendance at public education establishments, overcrowding within the home and the number of children under 10 years of age.The probability of having technological access to virtual education in the case of teachers is positively affected by: the teacher's years of education and individual income. While the age of the teacher, overcrowding within the home and the number of inhabitants of the residential area negatively affect the probability of technological access to virtual education for teachers. Analysis of education (dpeaa)DE-206 Regional analysis (dpeaa)DE-206 Technological change (dpeaa)DE-206 Merlo, Juan José verfasserin aut Enthalten in Atlantic review of economics La Coruña : [Verlag nicht ermittelbar], 2011 7(2024), 1 vom: Juli, Seite 1-35 Online-Ressource (DE-627)663843308 (DE-600)2616322-6 (DE-576)347002854 2174-3835 nnns volume:7 year:2024 number:1 month:07 pages:1-35 http://www.aroec.org/ojs/index.php/ARoEc/article/download/166/128/ Verlag kostenfrei http://www.aroec.org/ojs/index.php/ARoEc/article/view/166 Verlag kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2050 GBV_ILN_2111 GBV_ILN_2129 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 7 2024 1 7 1-35 26 01 0206 4565589222 x1z 13-08-24 2403 01 DE-LFER 4574099887 00 --%%-- --%%-- n --%%-- l01 03-09-24 2403 01 DE-LFER http://www.aroec.org/ojs/index.php/ARoEc/article/download/166/128/ |
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evidence from Argentina |
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digital divide to virtual educationevidence from argentina |
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Digital divide to virtual education evidence from Argentina |
| abstract |
Resumen COVID-19 forced an abrupt change in the teaching-learning process. From a scheme based on face-to-face teaching, we moved to a unique and exclusive system of virtual education. This change in the educational system involved forced adaptations of both students and teachers without a prior analysis of the required technological feasibility.This work studies the problem of digital division existing in Argentina, related to the access and use of technology and infrastructure in its educational system. From an empirical point of view, it seeks to answer the following questions: are students and teachers prepared to face a virtual learning process from a technological point of view? And what variables and factors determine technological access to the virtual education process?For this, two Virtual Education Indices are built, one aimed at students and the other at teachers, based on the access and use of PCs and mobile phones. Then, they are used to estimate a logit model for technological access for students and another for technological access for teachers.Using data from the EPH, it is analyzed how technologically prepared students and teachers are to participate in the virtual education process, at its three levels. A Technological Index of Virtual Education is built for students and another for teachers, based on the possession of a PC and the Internet and through the use of the Internet, PC and cell phone.The analysis reveals that students are better prepared from a technological point of view than teachers to be able to face the virtual education process.The most important variables that positively affect the probability of having technological access to virtual education in the case of students are: the age of the student, the total family income, the education of the student's mother, work in the labor market of the mother of the student, the number of people employed within the home and the number of inhabitants of the residential area. The negative effects on the probability of technological access to virtual education come from: attendance at public education establishments, overcrowding within the home and the number of children under 10 years of age.The probability of having technological access to virtual education in the case of teachers is positively affected by: the teacher's years of education and individual income. While the age of the teacher, overcrowding within the home and the number of inhabitants of the residential area negatively affect the probability of technological access to virtual education for teachers. |
| abstractGer |
Resumen COVID-19 forced an abrupt change in the teaching-learning process. From a scheme based on face-to-face teaching, we moved to a unique and exclusive system of virtual education. This change in the educational system involved forced adaptations of both students and teachers without a prior analysis of the required technological feasibility.This work studies the problem of digital division existing in Argentina, related to the access and use of technology and infrastructure in its educational system. From an empirical point of view, it seeks to answer the following questions: are students and teachers prepared to face a virtual learning process from a technological point of view? And what variables and factors determine technological access to the virtual education process?For this, two Virtual Education Indices are built, one aimed at students and the other at teachers, based on the access and use of PCs and mobile phones. Then, they are used to estimate a logit model for technological access for students and another for technological access for teachers.Using data from the EPH, it is analyzed how technologically prepared students and teachers are to participate in the virtual education process, at its three levels. A Technological Index of Virtual Education is built for students and another for teachers, based on the possession of a PC and the Internet and through the use of the Internet, PC and cell phone.The analysis reveals that students are better prepared from a technological point of view than teachers to be able to face the virtual education process.The most important variables that positively affect the probability of having technological access to virtual education in the case of students are: the age of the student, the total family income, the education of the student's mother, work in the labor market of the mother of the student, the number of people employed within the home and the number of inhabitants of the residential area. The negative effects on the probability of technological access to virtual education come from: attendance at public education establishments, overcrowding within the home and the number of children under 10 years of age.The probability of having technological access to virtual education in the case of teachers is positively affected by: the teacher's years of education and individual income. While the age of the teacher, overcrowding within the home and the number of inhabitants of the residential area negatively affect the probability of technological access to virtual education for teachers. |
| abstract_unstemmed |
Resumen COVID-19 forced an abrupt change in the teaching-learning process. From a scheme based on face-to-face teaching, we moved to a unique and exclusive system of virtual education. This change in the educational system involved forced adaptations of both students and teachers without a prior analysis of the required technological feasibility.This work studies the problem of digital division existing in Argentina, related to the access and use of technology and infrastructure in its educational system. From an empirical point of view, it seeks to answer the following questions: are students and teachers prepared to face a virtual learning process from a technological point of view? And what variables and factors determine technological access to the virtual education process?For this, two Virtual Education Indices are built, one aimed at students and the other at teachers, based on the access and use of PCs and mobile phones. Then, they are used to estimate a logit model for technological access for students and another for technological access for teachers.Using data from the EPH, it is analyzed how technologically prepared students and teachers are to participate in the virtual education process, at its three levels. A Technological Index of Virtual Education is built for students and another for teachers, based on the possession of a PC and the Internet and through the use of the Internet, PC and cell phone.The analysis reveals that students are better prepared from a technological point of view than teachers to be able to face the virtual education process.The most important variables that positively affect the probability of having technological access to virtual education in the case of students are: the age of the student, the total family income, the education of the student's mother, work in the labor market of the mother of the student, the number of people employed within the home and the number of inhabitants of the residential area. The negative effects on the probability of technological access to virtual education come from: attendance at public education establishments, overcrowding within the home and the number of children under 10 years of age.The probability of having technological access to virtual education in the case of teachers is positively affected by: the teacher's years of education and individual income. While the age of the teacher, overcrowding within the home and the number of inhabitants of the residential area negatively affect the probability of technological access to virtual education for teachers. |
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