Dataset of TPACK in teaching practice: Adversity quotient, attitude computer technology and self-efficacy among Indonesian teachers

This dataset describes the measurement of adversity quotient (AQ), attitude computer technology (ACT), and self-efficacy with computer technology (SCT) of Indonesian teachers in implementing the technological pedagogical content knowledge (TPACK) concept in their teaching practice. The online survey was distributed to collect data on demographic information (4 items), AQ (11 items), ACT (19 items), SCT (22 items), and TPACK (5 items). It was carried out from August to September 2022. A total of 901 teachers from 28 provinces in Indonesia were recruited using probability sampling technique. Data from the survey were analyzed using the statistical analysis of One Way Anova and Partial Correlation. This dataset can help teacher institutions design effective programs to develop teacher digital competencies in integrating technology. Future researchers can compare this dataset with more rigorous data from developing countries.


a b s t r a c t
This dataset describes the measurement of adversity quotient (AQ), attitude computer technology (ACT), and self-efficacy with computer technology (SCT) of Indonesian teachers in implementing the technological pedagogical content knowledge (TPACK) concept in their teaching practice. The online survey was distributed to collect data on demographic information (4 items), AQ (11 items), ACT (19 items), SCT (22 items), and TPACK (5 items). It was carried out from August to September 2022. A total of 901 teachers from 28 provinces in Indonesia were recruited using probability sampling technique. Data from the survey were analyzed using the statistical analysis of One Way Anova and Partial Correlation. This dataset can help teacher institutions design effective programs to develop teacher digital competencies in integrating technology. Future researchers can compare this dataset with more rigorous data from developing countries.  Table   Subject Social Sciencies Specific subject area Citizenship education, Educational techology Type of data

Value of the Data
• The data were collected in the context of Indonesia where Covid-19 pandemic is changing learning practices that encourage technology integration to meet the demands of digital competence for teachers. • The dataset is useful for teachers to develop and improve their digital competence and creativity regarding the use of technology as a form of adversity quotient and adaptation to all changes and developments in learning technology due to the impact of the Covid-19 pandemic. • This dataset is useful for policymakers in formulating teacher education programs that help student teachers to understand the motivations and effort s to improve their competencies in developing knowledge, skills, and experiences. • The data are helpful for researchers who want to compare the results of this study to similar research related to digital competence and the influence of the adversity quotient of teachers in seeking and finding solutions to overcome obstacles related to technology integration in learning.

Objective
The Internet transformed the entire educational system, particularly education in the twentyfirst century. All teachers in Indonesia are expected to integrate their pedagogical and digital competency skills as internet penetration raises. This dataset is crucial for assessing TPACK and its affecting aspects, such as adversity quotient, attitude toward computer technology, and selfefficacy with computer technology. According to the literature, there is few research about relationships among these variables. The dataset is influential to compare it to data from similar studies conducted in other regions. In addition, the data can inform the development of action plans, pedagogies, adjustments, or interventions to best support teacher education programs.

Data Description
In Indonesia, the Covid-19 pandemic has impacted teaching and learning practice, particularly face-to-face learning shifting to online learning, both using blended approach and game-based education [1 , 2] . Prior studies highlight the digital class using technology-rich design as a need for transforming learning [3 , 4] . However, there are few published studies that investigate the readiness of teacher education programs to implement learning technology. It is a struggle to be able to enhance outcomes and actions when developing new ways for enhancing teacher competency. For that reason, this paper presents a dataset that describes factors influencing teachers in implementing technological pedagogical content knowledge (TPACK). The data are divided into three groups: (1) demographic information, including grade level of teaching, gender, and age; (2) the determinants, including adversity quotient, attitude computer technology, self-efficacy with technology; and (3) TPACK. The survey involved 901 teachers from 28 provinces in Indonesia. All question items used to measure teachers' attitude, ability and expertise in using computer technology as a form of teacher digital competence and adversity quotient variables were measured using a Likert scale with 5-point intervals (Strongly Agree to Strongly Disagree). All demographic characteristics are presented in Table 1 .  Table 1 presents the characteristics of the respondents based on demographic information. The frequency distribution for each question item contained in the questionnaire is presented in Table 2 . In Table 3 to 6 , the relationship between respondents' demographic characteristics and variables is illustrated in a contingency table to show the interactions between respondents' demographic variables and the adversity quotient variable, attitude computer technology, selfefficacy with computer technology and TPACK.     0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Experimental Design, Materials and Methods
The research sample comprised teachers from 28 provinces in Indonesia and their various levels of teaching were selected by probability sampling. The sample is based on a convenient random sample for research [5] . Data collection was designed online using Google Forms due to the pandemic of Covid-19. Questionnaire links were distributed personally according to the respondents' selection criteria: having more than five years of teaching experience and having completed or enrolled in a teacher professional development program at several teacher institutions. The survey received a total of 901 responses, and all met the criteria for the statistical analysis stage.
The questionnaire was developed based on influential studies. Item questions for a variable of adversity quotient were guided by a notion from Stoltz [6] . The variables of attitude computer technology and self-efficacy with computers were developed from Milbrath and Kenzie [7] . The variable of TPACK was adapted from Schmidt et al. [8] . In the aspect of teacher demographic characteristics, descriptive statistical tests were carried out with analytical techniques using one-way ANOVA and partial correlations were carried out to determine the relationship and influence of these factors on the adversity quotient variable, computer technology attitude, self-efficacy with computer technology, and TPACK. Next, the instrument's reliability and validity analysis was carried out using statistical analysis of One Way Anova and Partial Correlation using Microsoft excel and SPSS version 25.0 application.
In the aspect of the demographic characteristics of the respondents, measurements were conducted regarding the aspects used as parameters of digital competence as well as the role and influence of the adversity quotient of teachers in integrating technology in the learning process. In this case, individual demographic characteristics are a potential source of data related to teachers' knowledge, attitudes, skills, and practices in utilizing digital technology in the learning process. The data were analyzed using frequency and percentage. The correlation analysis and One Way Anova test presented in Tables 3 to 6 describe the relationship and differences in experience and expertise as a form of teacher digital competence, including using computers to increase the effectiveness of teaching and learning. Table 7 presents data on the distribution  of the frequency. In The table shows the description of the level of respondent categories in each of the variables tested. As Table 8 indicates, for all the variables measured, the majority of the distribution of responses from respondents is in the high category for the Self-efficacy with Computer Technology variable by 57%, and TPACK by 46% included in the high category. The percentage of the frequency distribution of respondents' responses is 73% for the Advertising Quotient variable and 81% for the Attitude Computer Technology variable which belong to the medium category. In conclusion, when respondents have a high level of Self-efficacy with Computer Technology and the application of TPACK in the learning process in the classroom, effective learning can be created so that it is easier for students to understand the material and achieve learning objectives.

Ethics Statements
The authors ensured that the respondents provided their information voluntarily. All of the respondent's personal information is utilized for research purposes and will be kept in accordance with the anonymity principle. Prior the data collection, Universitas Muhammadiyah Surakarta has responsibility for this project by Research Ethic Committee and Granted the approval code of 215/A.3-III/FKIP/III/2022. Respondents could leave any time and for any reason, with no penalty and loss of benefits to which they were entitled, if any. The online survey was written anonymously to guarantee the confidentiality of their personal data.

Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data Availability
Dataset for Measuring Adversity Quotient, Digital Competence, Attitude Computer Technology and Self-Efficacy (Reference data) (Mendeley Data).