Table of ContentsIntroductionResult and DiscussionConclusionAlthough there are measures of e-learning readiness students' online learning published in the literature and journal of Behavioral Sciences and Education, very few scales are available to measure students' readiness for online learning, especially in Indonesia. The purpose of this study was to validate an instrument intended to prepare high school students for online learning. The Online Learning Readiness Scale aimed to measure online learning readiness among Indonesian students. Data from 271 high school students (male = 126, female = 145) in Yogyakarta, Indonesia, were subjected to item response theory (IRT) analysis and the psychometric properties of the scale were examined. using the generalized partial credit model (GPCM). The results of the IRT analysis using GPCM revealed excellent psychometric characteristics of the Indonesian version of this scale. Evidence of construct validity is presented. Scores on the students' online learning readiness scale were highly reliable. Implications for future research are discussed. Say no to plagiarism. Get a tailor-made essay on “Why violent video games should not be banned”?Get the original essayIntroductionThe Republic of Indonesia is a country that has a very large and strategic geographical area, flanked by two oceans and two continents where the conditions of the majority zone consists of oceans and islands which have approximately 17,000 islands. This situation has caused various obstacles to national development, including the development of road infrastructure, educational institutions, health facilities and internet networks which have not been distributed evenly from Sabang (far west) to Merauke (far -East). In this case, human resource development is an important part of the world of education and cannot be released just like that. The demands of the advancement of times and technology encourage the government and all parties involved directly or indirectly to make synergies, adaptations and innovations in the face of this millennial era. In the digital age like today, the use of technology has dominated the world. of education. The development of the world of education today in Indonesia must be able to bring changes and innovations in order to catch up with other countries. The first national examination that still uses paper or paper will be replaced by an online or online national examination system. This could be proven when Indonesia started holding computer-based national exams. The use of computers is an opportunity to facilitate the administration of exams. The planned facilities include administrative facilities such as no manual correction, manual collection of answer sheets, slow delivery times to Jakarta where the UN is corrected and the most important is on the psychometric side where this can be the starting point for administering the exam with Computerize. Adaptive testing (CAT). The implementation of national online exams in all regions of Indonesia will definitely face many challenges. One of the challenges is preparing students to take the exam. Readiness for learning is studied in many research studies, none of which is in Indonesia. They define readiness for online learning in three aspects: (1) students' preference for forms ofdelivery such as face-to-face classroom teaching; (2) student confidence in using electronic communication for learning and, in particular, competence and confidence in using the Internet and computer-mediated communication; and (3) the ability to engage independently in learning. Although there have been studies focused on developing tools to assess students' online preparation, they appear to have overlooked an important detail about the psychometric quality of these instruments. The participants of this study were high school students with a total of 271 students, 126 female and 145 male students aged 15 to 18 who were selected using a non-probability sampling technique. The consideration in using the sampling technique is due to the limitations in terms of time to create a sampling frame containing data on active students who are actively attending school, so the sampling technique that allows it to be used is non-probabilistic. Other characteristics considered in determining research participants are high school students who will face computer-based or online exams. Respondents' willingness to participate in this research is voluntary. Generalized Partial Credit Model (GPCM) IRT is a powerful modeling approach used to evaluate the psychometric properties of survey questionnaires with categorical (ordered and unordered) responses. IRT models are similar to factor analytic models in that they both provide information about the dimensionality and fit of the model. A key difference between IRT and factor analytic approaches is how the data is processed. While factor analysis methods examine covariances between individual items, IRT models examine overall response patterns for all items. Following evaluation of item response patterns, the resulting parameter estimates provide insight into item functioning. This type of information can be particularly useful during the survey development process. Additionally, factor analysis approaches construct a linear relationship between the factor score and the item response. This contrasts with the IRT approach, which constructs a nonlinear relationship between latent traits and item responses. Likert scale format: This is an extension of the dichotomous response format and is used when more information can be obtained than from a dichotomous format. In elementary applications, categories in expected order are scored with successive integers, starting with zero (0), and a person's scores on multiple items on a test or questionnaire are summed to characterize a person. In more advanced applications, a probabilistic model, such as GPCM, is applied. A major advantage of using polytomically scored items is that they generally cover a wider range of the ability scale with sufficient information compared to an assessment with the same number of dichotomous items. For polytomous response models, parameter values ​​must be interpreted using graphical presentations. Inspection of ICRF, IRF, and element information function plots for each element is an essential element analysis procedure. Result and Discussion Analysis of 9 items of Online Learning Readiness Scale (OLRS) showed that the model fit with Pearson chi-square obtained was 4355. .967, df = 1952917 , p-value = 1000 and..