Survey data of internet skills, internet attitudes, computer self-efficacy, and digital citizenship among students in Indonesia

Dataset provides wide measurement data on internet skills, internet attitudes, computer self-efficacy of the students related to the digital citizenship in Indonesia. Due to the pandemic of Covid-19, the survey was conducted online by considering the informant consent on assessing demographic information (7 items), internet skills (9 items), internet attitude (5 items), expertise and skills in using a computer (5 items), respect (6 items), educate (5 items), and protect (4 items), which was carried out from March to April. There were a total of 581 respondents selected through probability sampling based on random convenient sample from 12 public and private senior high schools which spread throughout 5 cities in Central Java, Indonesia. The survey data were analyzed using multivariate analysis and partial least structure with the analysis technique of Structural Equation Modelling (SEM). In the future, this data can help educators, researchers, and educational policy makers to determine the level of readiness of students' digital citizenship attributes and efforts to conduct further research on efforts to strengthen digital citizenship in curricular programs.


a b s t r a c t
Dataset provides wide measurement data on internet skills, internet attitudes, computer self-efficacy of the students related to the digital citizenship in Indonesia. Due to the pandemic of Covid-19, the survey was conducted online by considering the informant consent on assessing demographic information (7 items), internet skills (9 items), internet attitude (5 items), expertise and skills in using a computer (5 items), respect (6 items), educate (5 items), and protect (4 items), which was carried out from March to April. There were a total of 581 respondents selected through probability sampling based on random convenient sample from 12 public and private senior high schools which spread throughout 5 cities in Central Java, Indonesia. The survey data were analyzed using multivariate analysis and partial least structure with the analysis technique of Structural Equation Modelling (SEM). In the future, this data can help educators, researchers, and educational policy makers to determine the level of readiness

Value of the Data
• The dataset helps provide empirical evidence on digital citizenship readiness among students in Indonesia. The main attributes of digital citizenship include respect, educate, and protect (REP) and the factors that have an impact on digital citizenship are also presented. • The dataset will be useful for the researchers who want to make comparison with similar research, specifically the preparation for the digital citizenship aspect to face the era of Society 5.0. • The dataset can be used to enlighten Indonesian educators and educational policymakers in taking further efforts to equip students with the knowledge of how to respond to the abundance and ease of access to technology in a responsible manner, especially in the aspects of technology literacy and ethics when using the internet.

Data Description
The data in this article provides in-depth information about the level of digital citizenship readiness of Indonesian students by looking at the factors such as internet skills, internet attitudes, and computer-self efficacy. The survey in this study involved 581 students that spread across 12 senior high school consisted of private and public school in Central Java, Indonesia. The focus of data collection consists of three groups of variables, including (A) Demography and Socio-Economy of individuals, including gender, age, school of origin, parents' educational background, frequency of internet usage in one day, types of gadgets used in accessing the internet, and the monthly internet budget that the students spend in using the internet. (B) The variable of computer and internet competence which includes the ability and expertise of students in using/operating a computer which are outlined in 19 question items that are aimed at measuring students' internet skills, internet attitudes, and self-efficacy. And (C) 15 question items to measure the level of digital citizenship of students based on three main components, namely respect, educate, and protect (REP). All question items used to measure the two variables of the computer group, internet competence, and student digital citizenship were measured using a Likert scale with 5-point intervals (Strongly Agree to Strongly Disagree) which are presented in Tables 1-8 . Table 1 presents the characteristics of the respondents based on the demography and socioeconomy of the respondents. Previous studies denote users' individual background such as gender, age, frequency of internet usage, and parents' educational level have influential relationship with digital citizenship. Choi et al. [1] reported that individual background has narrowly impacted to digital literacy. Hargittai [2] found that parental education has no longer related to digital tools use but it is imperative in explaining variation in user skill. Besides, Wang and Xing [3] examined that parents' socioeconomic status includes parents' income and education level as a significant predictor of digital citizenship.
Meanwhile, Table 2 describes the frequency distribution for each question item in the questionnaire. In Table 3 , the data on the relationship between the demographic characteristics of the respondents and the variables are presented in a contingency table to show the interactions that occur between the demographic and socio-economic variables of the respondents and the variables of internet skills, internet attitude, computer self-efficacy, and digital citizenship which were reviewed from 3 components including respect, educate and protect in details.     Table 3 Statistic descriptive on demographic characteristics of respondents and internet skill ( n = 581). Variable  Category  IS1  IS2  IS3  IS4  IS5  IS6  IS7  IS8

Experimental Design, Materials and Methods
The context in this study is digital citizenship competence of senior high school students. The research samples came from 12 schools located in Central Java, Indonesia which were selected by probability sampling, in which the samples were allowed to choose based on random convenient sample to be used in research [4] . Because the pandemic of Covid-19 forced schools to close, the data collection was carried out through an online questionnaire. The questionnaires were distributed to respondents according to the criteria determined by the researcher using the Google Form platform. This was carried out with the aim of being able to measure the digital citizenship readiness of students in accordance with the Nine Elements parameter of digital citizenship including protection (protect), education (educate), and respect that was developed by Al-Zahrani [5] based on the assumption of Ribble [6] . Jones and Mitchell [8] also developed Digital Citizenship Scale (DCS) based on the criteria of online respect and online civic engagement with the total of 11 question items using 5-point scale from "not all like me" to "very much like me". In this study, the point scale was the same as the DCS by Al-Zahrani [5] with 5-point Likert Scale (5 = Strongly Agree, 1 = Strongly Disagree). In addition, the question items for the variables of internet attitude and computer self-efficacy were also based on the study by Al-Zahrani [5] . As for the variable of internet skills, it was adapted from van Deursen et al. [7] .
A total of 581 responses were received by the researcher, and all of them met the criteria for the next stage in the form of statistical analysis. In the aspect of demographic characteristics of the students, the descriptive statistical test was carried out with analytical technique using oneway ANOVA to determine the relationship and the influence of these demographic factors on the variables of internet skills, internet attitudes, computer self-efficacy, and the basic components that form the digital citizenship. Meanwhile, the analysis of the reliability and validity of the instrument was carried out using the Structural Equation Model (SEM) analysis technique with the SmartPLS version 3 program.
On the demographic characteristics of the respondents, measurements were made regarding the aspects used as parameters for the level of digital citizenship of the students. Individual demographic data is a potential source of data related to the students' knowledge, attitude, skills, and practices in utilizing digital technology within their daily lives which were analyzed using frequency and percentage. One-Way ANOVA was carried out to determine the relationship between different experiences and expertise in using computers and how they utilize it to facilitate activities in their daily lives. In Table 8 , the category level of the respondents is described in each of the tested variables. The majority of the distribution of responses fell under the high category in which the variable of internet attitude obtained 54.22%, that of internet skills obtained 56.28% which was included in the high category, and the percentage of frequency distribution of the respondents' responses was 54.56% for the variable of protect, 53.18% for computer self-efficacy and 51.64% for educate, thus the three of them belonged to the medium category. Meanwhile, the variable of respect fell under the very high category with 57.31%. Therefore, the respondents had a very high level of respect in utilizing computers and accessing internet within their daily lives.

Ethics Statement
Universitas Muhammadiyah Surakarta has responsibility for this project. The study process has been approved and adheres to the ethical guidelines and regulations the organisation in charge. The study used a tix box in the online consent form for underage participants to discuss the study with their parents and understand the study procedure, risks, and benefits to allow their children to be included. The study was conducted with the agreement and the volunteer of school managers and local administrators. All respondents were informed relate to the research before conducting the survey. The online survey was written anonymously to guarantee the confidentiality of their personal data.