1 Introduction

As education plays a key role in human resource development of a country, countries around the world emphasize improvement in the quality of education. Traditionally, “education” has occurred in a classroom where teachers and students are required to meet face to face. But due to today’s technological advancements, education has evolved to the point where a classroom is no longer the only venue where learning can take place. Rather, education and learning can be carried out via the Internet through online courses or through other computer- and high-tech-assisted curricula. And since the world has so dramatically entered the digital realm, the relation between ICT and education has become more crucial in the twenty-first century (Oliver 2002).

However, despite how crucial information technology is to manpower development of a country, how much a country benefits from ICT utilization depends on ICT’s accessibility and to what extent its population is “competent” or “familiar” with ICT. Ilomäki et al. (2016) explained this quality as “Digital Competence,” which is one of the factors comprising core competence for economic development these days. Digital competence comprises (1) technical competence, (2) the ability to use digital technologies in a meaningful way for work, study, and in everyday life, (3) the ability to evaluate digital technologies critically, and (4) as generating motivation to participate and commit in the digital culture.

However, the ability to utilize ICT varies from country to country. In developed countries where ICT equipment is available to all students, the familiarity level is higher than it is for students in developing (or underdeveloped) countries, where access to ICT gadgets is still limited. For that reason, students in developed countries find it easier to become familiar with using information technology for the benefit of their education.

In developing countries, the prevalence of poverty means that not only may poor households lack access to ICT at home, but also that students from those countries may have limited ICT access even in the schools. In addition to many schools still lacking ICT infrastructure and other resources due to limited budgets, they also most likely lack ICT teachers. Such an environment results in students in developing countries lacking familiarity with ICT relative to their peers in developed countries. Such a lack constitutes an obstacle to learning and to keeping up with contemporary educational practices, in which ICT is crucial.

Nowadays, information and communication technology is widely used for most activities, including those related to education. The term ICT, in this case, stands for information and communication technologies and is defined, as a “diverse set of technological tools and resources used to communicate, and to create, disseminate, store, and manage information among students”. This provides an increasing demand for schools to produce technologically literate students. Information and communication technologies have also changed the ways in which students access and process information and the ways in which they communicate with each other, providing educators with an impetus to modify and adapt curriculum to ensure capitalizing on the power of these technologies and the engagement of students with them.

Utilizing ICT in classroom education definitely enhances teaching proficiency. And Kingsley (2017) states that ICT will play a key role in enhancing education proficiency in developing countries. For example, Suryani (2010) discovered that when ICT (movie-making software) was utilized in a school in Indonesia, the students were encouraged to help each other in using the computers to learn how pictures related to sound and to develop creativity by producing movies around themes in which they were interested.

The objective of our research here is to study the level of ICT familiarity among Thai students and its impacts on educational outcomes in developing countries such as Thailand. Our research is divided into five sections. The second section is a literature review of ICT familiarity level and education outcomes. The third section is an introduction to the descriptive statistics on data used in the research. The fourth section will discuss econometrics estimation models used to study the impacts of ICT familiarity on education outcomes with controlled multi-dimension factors. And the final section presents the conclusion and a policy proposal.

2 ICT familiarity and education outcomes

Studies on the relationship between ICT familiarity and education outcomes have been conducted in many developed countries, and most have analyzed data from the Program for International Student Assessment (PISA). The majority of the studies discovered positive impacts between ICT utilization and education outcomes. One such study is that of Kubiatko and Vickova (2010), carried out to investigate the relation between ICT familiarity and the science scores of 5932 students in the Czech Republic, using data from PISA 2006. The authors found that ICT familiarity positively influenced science scores with statistical significance. This finding indicated that even though ICT familiarity has a positive, significant impact on science scores, students who utilized ICT related directly to their education had higher scores than students who utilized ICT for non-educational purposes.

Similarly, using data from PISA 2009, Delen and Bulut (2011) studied the relation between ICT familiarity and science and mathematics scores of 4996 students in Turkey. Results indicated that ICT utilization both at home and school significantly boosted science and mathematics scores. This coincides with a study conducted by Wittwer and Senkbeil (2008) involving home computer utilization and mathematics scores of German students (using the data from PISA 2003), indicating that students who used a computer at home had higher scores than students who did not. Another study, by Luu and Freeman (2011) on the relation between ICT utilization and the science scores of students in Canada and Australia (employing data from PISA 2006), indicated that computer experiences of students helped increase science scores.

Apart from the impacts on science and mathematics scores, there have been impacts on other academic skills. For example, Leino (2014) found that the relationship between ICT and the reading skills of students in Finland indicated that Internet browsing increased reading skill, depending on one’s familiarity with Internet data searching. Individuals who were more familiar with such searching had a higher-level reading skill than those who were less familiar. All of this empirical evidence shows that young people who use technologies in the online environment would do well to familiarize themselves with such skills in order to boost their learning potential (Shields and Chugh 2018).

By using cross-country comparisons, a study by Eickelmann et al. (2017) examined the relationship between ICT use and the performance of Grade 9 students in mathematics from five countries—Australia, Germany, the Netherlands, Norway, and Singapore. Using PISA-2012 and including school-level data such as the availability of IT equipment of schools, school leadership, aspects of school goals, and educational strategies, as well as teachers’ attitudes, the authors found that the relationships among these factors affected students’ mathematics achievement when they were synchronously assessed in the various countries’ educational systems. The results show that characteristics at the school level do play a major role in the integration of ICT into teaching and learning and turn out to be relevant across educational systems.

From various studies, we can conclude that the impacts of ICT use on educational outcomes can vary, depending on the types of use to which ICT is put, the level of confidence and familiarity in using ICT, and attitudes towards using ICT for education and overcoming learning difficulties in school. In terms of types of usage, different uses of ICT can produce different educational outcomes. As an example, Zhang and Liu’s study (2016) of the relation of ICT utilization and mathematics/science scores of students in China (employing data from PISA 2000–2012) indicates that in 2000–2009 ICT utilization for entertainment purposes had negative impacts on mathematics and science scores, but such utilization had positive impacts in 2012. Even more puzzling, Internet utilization for educational purposes in the schools in 2009 and 2012 had negative impacts on the scores of both subjects.

Furthermore, a study from Bulut and Cutumisu (2017), which aimed to explain the relationship between ICT and mathematics/science scores of students in Finland and Turkey, found that although ICT utilization for entertainment purposes had significant negative impacts on Finnish mathematics and science scores, such utilization had positive impacts for students in Turkey, where ICT utilization at home and in schools had significant positive impacts on mathematics and science scores. But Aypay (2010) discovered that ICT utilization had no significant impact on the scores of the 4942 Turkish students from 160 schools who were tested in PISA 2006. On the other hand, similar to the Finnish students, students in Canada and Australia who used ICT for entertainment purposes too often exhibited lower science scores (Luu and Freeman 2011).

Results in the above paragraph, however, contradict those of Biagi and Loi (2013), who used an econometric model to measure the relationship between students’ computer use and their achievement in reading, mathematics, and science in 23 countries. Biagi and Loi (2013) found that students’ PISA test scores in reading, mathematics, and science increased with intensity of computer use for gaming activities while they decreased with intensity of computer use for activities that are more related to school curricula. However, the number of activities (and hence the diversification of activities) is positively correlated with students’ proficiency in all three PISA domains in the vast majority of countries, indicating that computers breadth of use, as opposed to intensity of use in a given activity, should have a positive effect on students’ learning outcomes.

Another possible factor to explain why various ICT usages can have different impacts on students’ educational outcomes is the extent to which students are confident using ICT for a particular purpose. For the most part, students in developed countries seem to be highly confident in using ICT. Results from Thomson and De Bortoli (2007), for example, indicate just how extensive the access to ICT is in schools, homes, and other places for students in Australia. However, this study focused on the aspects of the “digital divide,” and examined access and use of ICT in Australia by state, gender, socioeconomic background, and geographic location. It indicated that Australian students were highly confident of being able to perform routine ICT tasks such as opening, saving, and deleting files by themselves, and that they were among the most confident in the world at performing Internet tasks. Although fewer students from low socioeconomic backgrounds had access to a computer at home, there was little difference between students from low and high socioeconomic backgrounds in their use of computers and their confidence in using computers.

Attitudes toward educational technology are also important. A study from Petko et al. (2017) indicates that, using PISA-2012 data and combining frequency of use and positive perceptions with regard to educational technology as predictors for student test scores, positive attitudes toward using technology for education are associated with higher test scores in the large majority of countries. The authors therefore argue that ICT usage quality is more important than ICT usage quantity if the aim is to achieve a positive impact of ICT on education performance.

In both developed and, especially, developing countries, the need to address learning difficulties can be another important factor that supports the use of ICT. The term “learning difficulties” is used to refer to conditions experienced by children who need extra assistance with schooling due to any number of a vast range of cognitive and physical impairments. Therefore, any tool that could make learning easier and more interesting and that could enthuse and inspire such students would lead to better educational outcomes for them. To test this idea, Adam and Tatnall (2017) conducted research in two Special Schools in metropolitan Melbourne and investigated whether ICT could be used to support school communities involving students with learning difficulties and help them to improve their learning. They found that ICT certainly did ameliorate learning difficulties among students by equipping them with adequate skills to allow them to enter the workforce or continue with further study through various pathways.

This review of the literature indicates both positive and negative impacts of ICT familiarity in developed countries, while the studies in developing countries are still limited, and the effect of ICT on education remains uncertain. Therefore, in the next section we will use data from PISA-Thailand as a case study for developing countries. The data was conducted in the year 2015.

3 Data

This study employed secondary data obtained from a questionnaire filled out for PISA-Thailand. Conducted by the OECD and in cooperation with the Thai government, the PISA-2015 evaluated achievement in reading, mathematics, and science among 8249 randomly chosen students from 237 schools. The advantage of employing PISA data used in this study are the following:

  1. 1)

    PISA data comes from a national survey of students. It generates better data than do other studies in developing countries that often select particular schools or communities and thus do not provide good national data.

  2. 2)

    In 2015, PISA added many ICT familiarity-related questions compared to the previous surveys, enabling it to be used in more detailed ICT familiarity analysis.

  3. 3)

    In this 2015 PISA survey session, the science test was weighted as the main criterion for assessment vs. reading and mathematics. Hence, the 2015 survey contained many science and technology questions suitable for more detailed analysis.

Initial analysis of the ICT utilization ratio indicates (Fig. 1) that while 75.55% of Thai students surveyed had access to the Internet at home and 79.78% had access at school, only 16.05% had access to e-books at home and 28.12% at school. Laptops were the most-used devices at home (among 55.42% of students), and desktop computers were the most used at school (76.7%).

Fig. 1
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Percentage of students having and using ICT equipment. Source: Calculated by the researcher from 2015 PISA student questionnaire data

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In terms of ICT experience (Table 1), data indicate that 32.96% of students had used digital devices for the first time at age 7–9, and 44.9% had used computers for the first time at that age. And 38.36% had first accessed the Internet at age 10–12. While 20.42% used the Internet outside of school on weekdays for 2–4 h per day, 34.35% used it more than six hours a day on weekends (Table 2). This shows that (in terms of usage time) Thai students use ICT during weekends 2–3 times more than on weekdays (when they go to school).

Table 1 Experience with a digital device, computer, and accessing the Internet (percent)
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Table 2 ICT use per day (percent of students per time period)
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Time spent with ICT by Thai students outside school is mostly spent on social media platforms such as Facebook (50.68%), followed by Line or MSN chats (41.43%) and browsing the Internet to watch videos such as those found on YouTube (39.67%) (Table 3). It can be concluded that Thai students use ICT for many activities, such as email and social media communication and entertainment. And while they do use the Internet for educational purposes such as following up on classes, communicating with teachers, learning foreign languages and mathematics, or doing homework assignments, they also use ICT for entertainment, such as gaming, watching videos, or uploading shared user-created content.

Table 3 Frequency of ICT activities outside school (percent)
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An analysis of 2015 PISA reading, mathematics, and science scores categorized by access to ICT devices indicates that scores for students who use devices such as home desktop computers, school desktop computers, home laptops or notebooks, or home tablets, and have a home Internet connection and a school Internet connection are higher for reading, mathematics, and science than they are for students who do not use ICT (Figs. 2, 3, and 4, respectively).

Fig. 2
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Reading scores classified by the use of various ICT devices. Source: Calculated by the researcher from 2015 PISA student questionnaire data

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Fig. 3
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Mathematics scores classified by the use various ICT devices. Source: Calculated by the researcher from 2015 PISA student questionnaire data

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Fig. 4
figure 4

Science scores by using various information communication technology. Source: Calculated by the researcher from 2015 PISA student questionnaire

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Classified by the use of various ICT devices, Table 4 also indicates that Thai students who had been familiar with ICT from the age of six years or younger were likely to have higher scores for the three subjects than were students who only became acquainted with ICT at the age of 13 years or older (or who had never used ICT until the date of the survey). Also, those who used ICT for an average of 2–4 h on weekdays tended to have higher scores in the three subjects, while students who used ICT an average of 4–6 h on weekends tended to have higher scores. Apart from that, if students used the Internet for educational purposes 1–2 times a week, the scores were higher than for those who never or almost never used the Internet for educational purposes.

Table 4 Educational achievement classified by the use of various ICT devices
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From what is indicated in Table 4, it is still not possible to determine whether non-educational uses of ICT have positive or negative impacts on educational outcomes. This is because in addition to the different scores for reading, mathematics, and science correlated with the particular ICT usage of each person, there are also multiple factors, such as household factors, school factors, and area factors that affect educational outcomes. Thus, it is necessary to eliminate those factors by econometric evaluation and controlling other factors in the dimensions, which are presented in the next section.

4 Model estimations

The focused methodology of this paper is based on descriptive statistics and econometrics estimation that aim to quantify the impacts of ICT familiarity among Thai students on their education outcomes with controlled multi-dimension factors. Based on Fasih (2008), factors affecting education outcomes can be classified into two aspects:

  1. 1)

    Demand-Side Factors

    1. 1.1)

      Family Characteristics: parents’ highest education, household equipment, careers of the parents, and family’s financial status

    2. 1.2)

      Student Characteristics, which are gender, student’s attitude, health and lifestyles of students, including their ICT usage

  2. 2)

    Supply-Side Factors

  3. 2.1)

    School Characteristics: school location, number of students in a classroom, school support such as school activities, IT equipment shortage, IT equipment quality problems, teacher characteristics, availability of teachers, education level of teachers, amount of teacher training, and teacher support program

It can be noticed that factors related to ICT familiarity among students fall into both demand-side and supply-side categories. Therefore, in this case, the variables used to explain ICT familiarity factors will be classified into: 1) Access to the ICT equipment, 2) ICT use experience, 3) Internet usage duration, and 4) Types of ICT usage.

The econometrics models are estimated in the following forms:

$$ Log\ \left({PISA\ Score}_i\right)=\alpha +\beta\ {ICT}_i+\gamma\ {Family}_i+\delta\ {Student}_i+\theta\ {School}_i+{\varepsilon}_i $$

Where the dependent variables are test scores (log-form) of the students i on Reading subject (Model 1), Mathematics subject (Model 2), and Science subject (Model 3) by controlling family characteristics (Familyi), student characteristics (Studenti), and school characteristics and teacher factors (Schooli). And εi is the error term.

Estimated results from Table 5 show that male students had significantly higher mathematics and science scores than did female students by 3.2% and 2.5%, respectively. But female students had higher reading scores than did male students by 1.4%. Students whose parents had “professional” occupations tended to have the highest scores than those whose parents engaged in general basic occupations.

Table 5 Estimation results of coefficients of variables representing ICT familiarity and impacts on PISA scores
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Apart from these factors, other statistically significant factors included whether a house had a quiet area for study, whether educational software was available, and whether there was a mobile phone with Internet access, a computer, and a musical instrument. Students for whom these factors were present tended to have statistically significantly higher scores in reading, mathematics and science than did students for whom these factors were absent.

A look at students’ before- and after-school activities indicates that students who read books before going to school had significantly better scores in reading, mathematics, and science than did students who did not read before going to school. In addition, students who finished their homework after coming home from school had better scores in mathematics (2.3%), science (2.5%), and reading (2.9%) than did students who did not finish their homework.

As for the school factor, students studying in classes of 15 or fewer persons got significantly better scores in reading (5.2%), mathematics (6.9%), and science (10.0%) than did students studying in classes containing more than 50 students.

Furthermore, students in schools that offered musical activities had significantly better scores in science (1.3%) and reading (1.8%) than did students in schools that did not offer musical activities. (There was no effect on mathematics scores, however.) And students in schools that had an art club had significantly better scores in reading (4.6%), science (4.7%), and mathematics (7.0%) than did students in schools without an art club.

With regard to teachers, students with science teachers who sometimes allowed an exchange of opinions among students enjoyed significantly better scores in reading (1.8%), science (2.6%), and mathematics (3.2%) than did students with science teachers who did not allow exchanges of opinions. This could be the result of knowledge sharing and debating, which can generate new learning.

Focusing on the analysis of ICT familiarity factors affecting education scores, factors are categorized in terms of: 1) Access to the ICT equipment, 2) ICT use experience, 3) Internet usage duration, 4) Types of ICT usage.

  • For Access to ICT Equipment (availability of home/school computers): results indicate that merely having computer equipment at home (if it is rarely used) does not contribute to better education scores. In fact, students who had access to a computer at home but who did not use it got lower scores in reading (1.5%), science (1.9%), and mathematics (2.1%) than did students who did not have a computer at home at all. Moreover, students who had a notebook computer at home but who did not use it had lower scores in mathematics (1.8%), reading (2.4%), and science (2.5%) than did students who did not have a notebook at home. In contrast, students who used computers in school had better scores in mathematics (1.5%), reading (1.8%), and science (1.8%) than did students who had no access to school computers.

Although computer availability/unavailability seemed to have no positive impact on education in Thailand, students who had school Wi-Fi access tended to have better scores in reading (2.4%), science (2.5%), and mathematics (4.7%) than did students who had no access to school Wi-Fi. This is consistent with Delen and Bulut’s study (2011) indicating that Internet access is important for useful data searching, which is important for improvements in educational quality.

  • As for ICT use experience, students who had ICT experience since childhood would be more familiar with adapting it for educational purposes than would students who had just begun using ICT or who had never used it before. Findings reveal that students who had used digital gadgets from age six or younger had better scores in reading (3.9%), mathematics (4.0%), and science (4.6%) than did students who only began to use such devices from age 13 or later or who had never used such devices. Furthermore, students who had used a computer from age six or earlier had better scores in reading (2.2%) and mathematics (3.0%) than did students who had begun to use a computer from age 13 or later or who had never used one, which is consistent with Leino’s study (2014) indicating that students who are familiar with reading from a computer also have good reading scores.

  • In terms of the duration of Internet usage on weekdays in schools, students who used the Internet 1–30 min per day had better scores in reading (1.2%), science (1.4%), and mathematics (2.1) than did students who did not use the Internet at all. And an examination of Internet usage on weekends indicates that students who used the Internet 2–4 h per day had better scores in science (2.7%), reading (3.0%), and mathematics (3.4%) than did students who did not use the Internet at all.

  • An analysis of types of usage finds that students who played single-player games almost every day had better scores in mathematics (1.5%), reading (2.2%), and science (2.6%) than did students who never or almost never played a single-player game. But students who played social platform multi-player games every day (or often) suffered negative impacts on education outcomes, especially in reading (a 2.1% decrease) and science (a 1.6% decrease) than did students who never played a social platform multi-player game. We also find that students who surfed the Internet for entertainment, such as watching YouTube once or twice per week, had better scores in mathematics (2.5%), science (2.8%), and reading (3.5%) than did students who never or almost never watched YouTube, which is consistent with Zhang and Liu’s (2016) study of the 2000–2012 PISA results, indicating that students who used ICT for entertainment had a positive relationship with mathematics and science because entertainment helps to relieve stress and enhance concentration as they study and to thus enhance their thinking. Similarly, Bulut and Cutumisu’s study (2017) indicates that ICT utilization for entertainment purposes had positive impacts on the mathematics and science scores of Turkish students. However, ICT should not be used for entertainment purposes for too long a time since doing so can decrease science scores.

As for study-related communication, students who used ICT lessons and exercises to follow up on their classroom and other studies had better scores in reading (2.1%), science (2.2%), and mathematics (2.3%) than did students who never or almost never used ICT to follow up on their study of a subject. Similarly, students who checked information on their school website almost every day had better scores in mathematics (1.6%), science (2.2%), and reading (2.3%) than did students who never or almost never checked information on their school website. Furthermore, students who did their homework on a computer once or twice per week had better scores in reading (1.5%), science (1.8%), and mathematics (2.4%) than did students who never or almost never did homework on a computer. Moreover, students who did their homework on a mobile phone almost every day had better scores in reading (1.6%), mathematics (1.8%), and science (1.9%) than did students who never or almost never did homework on a mobile phone, which is consistent with Kubiatko and Vickova’s study (2010) stating that students who used the Internet and engaged in ICT activities for educational purposes had better science scores than did students who did not and that students who used email at their schools every day had better scores in reading (2.5%), mathematics (2.8%), and science (2.8%) than did students who never or almost never used email at their schools.

As for ICT utilization for non-educational purposes (such as emails, online chats, receiving important data from the Internet or uploading user-created content for sharing), results indicate that students who uploaded user-created content for sharing almost every day turned out to have lower scores in reading (3.2%), mathematics (3.2%), and science (3.8%) than did students who never or almost never uploaded such content. Moreover, we find that students who chatted online almost every day did have 1.6% lower mathematics and science scores than did students who never or almost never chatted online.

Furthermore, reading news, receiving useful information, downloading songs, movies, games, or software from the Internet, and downloading new applications on mobile phones nevertheless had no significant effect on education outcomes. Therefore, in general, it may be concluded that ICT has significant positive impacts on education outcomes when used mainly for educational purposes, while utilization for communication or data searching (including sharing and updating data) has no impact on education outcomes. On the other hand, using emails, online chats, receiving important information from the Internet or uploading user-created content for sharing can have a negative impact on education outcomes.

5 Conclusion and policy recommendations

ICT familiarity plays a key role making it possible to successfully enter into the new economic system that requires technology and digital media (an Innovative and Digital-Driven-Economy). Upgrading ICT familiarity will directly impact human resources of a country, as measured by the education outcomes. Previous studies have dealt mainly with developed countries and have not investigated the impacts of ICT familiarity on education outcomes in developing countries, given their limited access to such technology. This study uses national survey data from Thailand as a case study for developing countries to study ICT familiarity’s impacts on education outcomes.

Findings here indicate that students who gain experience and familiarity with ICT from childhood get higher scores in reading, mathematics, and science than do students who are just beginning to use ICT or who have never used it at all. In terms of daily usage, we find that there is a positive effect on education scores as long as usage is limited to 1–30 min per day on weekdays in schools and 2–4 h per day on weekends.

Moreover, interesting study results are found and are consistent with studies done in developed countries. Namely, we find that utilization of ICT that is directly related to education has significant positive impacts on education outcomes while utilization of ICT that is not related to education has no impact in any way (or may even create negative impacts depending on the type of usage) on education outcomes.

Therefore, in order to upgrade education quality for children and youths of the country, the government and related organizations (including families) should ensure that children and youths have an opportunity to utilize ICT mainly for educational purposes and control non-educational use to ensure that it is used appropriately.

As a foundation for specific policy recommendations, we must keep in mind that ICT provides Thailand, as well as other developing countries, many opportunities to transform teaching, learning, and management practices in schools. In a developing country like Thailand, ICT fosters not only critical and creative thinking, capabilities to solve real-world problems, ability to work collaboratively, engagement in ethical decision-making, and adoption of a global perspective towards issues and ideas, but it also provides students from remote areas access to expert teachers and learning resources and gives administrators and policy makers the data and expertise they need to work more efficiently. Therefore, policy recommendations should address both supply-side and the demand-side concerns.

As for the supply side, our results show that merely having computer equipment at home does not contribute to better education scores. But students who used computers in school had better scores in mathematics, reading, and science than did students who had no access to school computers. Therefore, the government should focus on providing better access to ICT in school, especially in rural schools that face infrastructure constraints that impede the use of ICT in the classroom along with a lack of capacity in terms of teachers and school leaders to promote and use ICT to enhance the quality of teaching and learning. In addition, building the capacity of teachers, administrators, and other education leaders to use and integrate ICT in education systems is crucial. In addition, government can boost schools’ effective use of ICT by working with tertiary institutions that act as capacity-building providers. In this case, the governments should create incentives for universities to provide training to schools about how to use ICT in education.

In terms of the demand side, since our results show that students who have more experience in using ICT, have better access to the Internet, and use ICT primarily for the purpose of education tend to have better scores in reading, mathematics, and science, the government should provide students, as well as their parents, guidelines on how to utilize ICT in the most appropriate ways. Providing better Internet access, especially to remote areas, would benefit underprivileged students by making it easier for them to gather information from websites, access online education, and use email/text messages for education purposes. This would improve their learning outcomes and narrow thesocioeconomic gaps caused by educational inequality.

In conclusion, ICT provides a developing country like Thailand the opportunity to transform teaching, learning, and management practices in schools. The need for this transformation is urgent, given the increasingly globalized world in which students and teachers now live. Without it, as future graduates they could end up as part of a workforce that cannot keep up with the demands of the twenty-first century.