This study presents the state of data on access to digital devices and internet connectivity among Thai students at school and home and assesses school readiness for eLearning. It analyzed available secondary data from the National Statistics Office (NSO), Office of Basic Education Commission (OBEC), Ministry of Digital Economy and Society (MDES), National Broadcasting and Telecommunication Commission (NBTC) to identify schools’ readiness for eLearning.
Executive Summary
COVID-19 affected approximately 60.5% of the total enrolled learners globally and over 15 million in Thailand alone (UNESCO, 2020a). Twelve million Thai students enrolled at pre-primary, primary, lower-secondary, and upper-secondary education levels were affected by schools’ delayed reopening. The government of Thailand imposed a nationwide temporary closure of educational institutions on March 18, 2020. The students were required to adapt to distance education’s new norms during the school closures. The challenge resurfaced when the second wave returned in December 2020, resulting in school closures in 28 provinces. Over a short time, schools had to go online posing adaptation challenges. The government realized the importance of digital infrastructure for school education and accorded high priority. On the UN resident coordinator’s initiative, this study was undertaken by the ITU, together with UNESCO and UNICEF, to map the digital divide in the context of school education in Thailand with support from the Government of Thailand.
This study presents the state of data on access to digital devices and internet connectivity among Thai students in the school, home, and school’s readiness for eLearning. It analyzed available secondary data from the National Statistics Office (NSO), Office of Basic Education Commission (OBEC), Ministry of Digital Economy and Society (MDES), National Broadcasting and Telecommunication Commission (NBTC) to identify schools’ readiness for eLearning.
The data on access and use of digital devices and internet connectivity in the school remains fragmented, and availability is limited.
Thailand’s education system governance involves various public and private institutions. In addition to the Ministry of Education, fourteen other public bodies oversee their own institutions. The study accessed data on desktop computers’ availability for management purposes from only six out of seventeen jurisdictions. The unavailable data accounts for six percent of the educational institutions where twenty percent of the students study. A similar issue was observed with data regarding the number of desktop computers for the pedagogical purpose where only five jurisdictions’ data was available. Surprisingly, the information about internet connectivity in the school is available only for schools under the jurisdiction of OBEC, MoE which accounts for seventy-nine percent of the educational institutions where fifty-two percent of students study. Internet connectivity information for nearly half of the students was unavailable.
Access to digital devices and internet connectivity among students at school
MOE reports 99.18 percent of the schools are connected to the internet. However, the study (covering 29871 out of 37981 schools (79% schools) found subtle connectivity differences among the schools across different regions reflecting the digital divide. Schools from the Central and Southern regions of the country are connected relatively better than the schools in the North and North East region. Provinces with a higher Gross Provincial Product (GPP) Per Capita saw a lower percentage of schools without internet. This indicates the traditional economic fault lines were also visible when it came to connectivity. Differences were also observed across regions regarding access to devices, such as the number of computers shared by a student.
Access to digital devices and internet access among students at home
As the learning environment shifts to home during a pandemic, the study analyzed PISA 2018 survey data to assess students’ access to digital devices and internet access at home. Approximately four out of ten 15-year-old students in Thailand do not have access to either a tablet or desktop computer at home. Both the number are below the OECD and non-OECD averages. This study found a difference between the socioeconomic statuses of the students. Only two out of ten socioeconomically disadvantaged students had access to a computer for schoolwork at home, while nine out of ten advantaged students had access.
On the positive side, NSO data shows that the percentage of internet users in different age groups is increasing steadily. The highest growth in users’ percentage is observed among 25 – 49 years old user, followed by 25 – 34, greater than 50, and among 15 – 24 years old users. In the meantime, the five-year average annual growth rate of school going aged population (6-14) years internet users was 4 percent, and nearly a quarter of the people still do not use the internet (National Statistical Office, 2020a).
Access to digital devices at the household level
Access to digital devices at household level serves as an important indicator to reflect the state of readiness to undertake eLearning. Approximately 16.1 million (25.3 percent) of 63.6 million Thai residents above the age of 6 years use computers, and the number of internet users has reached 42.4 million (66.7 percent) in 2019. However, nearly one in three residents still do not use the internet (National Statistical Office, 2020a). Television was used to deliver classes in Thailand during the pandemic, making it a vital distance learning device. The penetration of TV in the household remains one of the highest in the ASEAN region. 97% percent of the household have access to TV in their home (National Statistical Office, 2020b).
During 2015-2019, the number of computer users continues to decline while the proportion of people using the internet continues to climb up. Despite the low penetration of computers, internet connectivity is available at the household level using mobile devices. However, the study also observed mobile access disparities across different socio-economic strata. Only 59 percent of households from the provinces in the bottom quartile of GPP per capita had an internet connection in their home compared to 79 percent of the top quartile households. Similarly, only 11 percent of the household from the lowest quartile had access to a computer in their household as opposed to 20 percent from the top quartile. This difference in access to a computer and internet connectivity at home signifies that the majority of the households in the bottom quartile will be left behind in eLearning initiatives that require a computer and internet.
Adequacy of digital devices and teachers’ readiness
eLearning initiatives’ success is also contingent on the quality of digital resources, qualified technical staff, and a robust online learning support platform. The PISA 2018 survey data analysis suggests significant gaps persisted in school principals’ opinion on the adequacy of computing device and internet bandwidth across geography, socioeconomic status, and public and private schools. 64 percent of rural school principals think the school’s digital devices’ computing capacity is sufficient compared to 72 percent of schools in the urban area. Similar gaps were observed across public and private schools. Only 56 percent of public school principals feel their school has sufficient internet bandwidth than 83 percent from private schools. Hence, it is vital to address these gaps to ensure equitable access to eLearning resources post COVID-19.
Recommendations
As digital connectivity becomes paramount to the education sector, it is vital for the government (MOE, MDES, and NBTC) to connect the unconnected schools and communities and ensure that students have equitable access to devices, learning content, and opportunities. Some of the other specific recommendations in this regard are:
a) Improve the availability of data on the status of school connectivity:
- The availability of data specifically on students and school is limited. MoE collects data on digital devices and internet connectivity in the schools under the jurisdiction of OBEC. However, not all the collected information is readily available for the analysis. Datasets containing the school location, state of access to digital devices, and internet connectivity, including the internet’s quality, must be compiled at a centralized location to help researchers and other agencies identify schools requiring special attention.
- It is vital to collect recent data on the usage of internet and digital devices and the teachers, students, and administrators’ skills. The government should prioritize collecting data on how the devices and connectivity are used and what skills do students and teachers possess at the school level. A pilot study using a bottom-up approach in understanding these gaps in schools across different jurisdiction is recommended.
b) Set guidelines for internet and devices in schools:
- The responsible government agencies overseeing educational institutions should establish criteria to assess the bandwidth’s adequacy in the schools by setting per capita student bandwidth targets and measuring progress. It is recommended to undertake a pilot in a few schools of Thailand under different jurisdictions to understand and estimate the bandwidth and digital devices needs.
c) Improve digital device to student ratio in schools:
- The relatively larger student to computer ratio in the school can pose a challenge in learning digital skills and other subjects that require the usage of devices in the schools. Hence, MoE should emphasize strengthening the students’ access to computing devices instrumental for learning.
d) Enhancing connectivity information to include community:
- The compatibility and visualization of data across different jurisdictions within MoE and between MDES, NBTC, Ministry of Interior, and other relevant agencies that have schools under their jurisdiction should be enhanced. In digital environment, the learning environment expands from schools to community. It is important that assessment of connectivity is undertaken considering the student’s experiences more holistically. For this purpose, school-based data needs to be mapped with the existing telecom coverage connecting schools and communities. This should include access to fiber and high-speed broadband (mobile and fixed) coverage, preferably using a GIS platform. It should also bring together various initiatives, including the MDES Net Pracharat project, NBTC USO coverage, and other initiatives.
e) Increase availability of traffic information and bandwidth use from schools:
- OBEC, MOE should enhance the quality of data collected through its EMIS on computer, networking, and internet and make the information publicly available for further analysis.
- OBEC, MoE and other jurisdictions overseeing the schools should consider partnering with internet service providers to accurately track internet usage in the schools.
- MDES, through its Net Pracharat project, can collect data on the usage of the internet in schools. However, at this moment, the project does not identify the schools clearly. As a result, crucial internet and network usage data are missed out. Hence, Net Pracharat project should identify and collect network usage data from all educational institutions that have access to its network.
- Net Pracharat location and usage data analysis reveals that students did not use the community-based network for learning purposes during the pandemic. Hence, the rural connectivity projects should expand their focus to incentivize household level connection wherever possible.
f) Improve affordability of internet connectivity for students:
- Internet affordability, particularly mobile data, remains expensive for students, particularly for low socioeconomic status. Also, online learning would require much longer and stable internet access than other applications. Commercial telecommunication providers and government agencies should consider means to subsidize internet cost for students from low-income families to provide equal learning opportunities.
g) Assess the impact of eLearning on education outcomes
- Further study should be undertaken to assess the impact of e-learning on education outcomes and see if the differential access to the internet and devices impacts students’ educational achievements.
The full report can be downloaded from here: https://thailand.un.org/en/140320-mapping-digital-divide-school-education-thailand
